New Technologies, Development and Application VI: Volume 1 3031310659, 9783031310652

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Lecture Notes in Networks and Systems 687

Isak Karabegovic Ahmed Kovačević Sadko Mandzuka   Editors

New Technologies, Development and Application VI Volume 1

Lecture Notes in Networks and Systems

687

Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

Advisory Editors Fernando Gomide, Department of Computer Engineering and Automation—DCA, School of Electrical and Computer Engineering—FEEC, University of Campinas—UNICAMP, São Paulo, Brazil Okyay Kaynak, Department of Electrical and Electronic Engineering, Bogazici University, Istanbul, Türkiye Derong Liu, Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, USA Institute of Automation, Chinese Academy of Sciences, Beijing, China Witold Pedrycz, Department of Electrical and Computer Engineering, University of Alberta, Alberta, Canada Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Marios M. Polycarpou, Department of Electrical and Computer Engineering, KIOS Research Center for Intelligent Systems and Networks, University of Cyprus, Nicosia, Cyprus Imre J. Rudas, Óbuda University, Budapest, Hungary Jun Wang, Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong

The series “Lecture Notes in Networks and Systems” publishes the latest developments in Networks and Systems—quickly, informally and with high quality. Original research reported in proceedings and post-proceedings represents the core of LNNS. Volumes published in LNNS embrace all aspects and subfields of, as well as new challenges in, Networks and Systems. The series contains proceedings and edited volumes in systems and networks, spanning the areas of Cyber-Physical Systems, Autonomous Systems, Sensor Networks, Control Systems, Energy Systems, Automotive Systems, Biological Systems, Vehicular Networking and Connected Vehicles, Aerospace Systems, Automation, Manufacturing, Smart Grids, Nonlinear Systems, Power Systems, Robotics, Social Systems, Economic Systems and other. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution and exposure which enable both a wide and rapid dissemination of research output. The series covers the theory, applications, and perspectives on the state of the art and future developments relevant to systems and networks, decision making, control, complex processes and related areas, as embedded in the fields of interdisciplinary and applied sciences, engineering, computer science, physics, economics, social, and life sciences, as well as the paradigms and methodologies behind them. Indexed by SCOPUS, INSPEC, WTI Frankfurt eG, zbMATH, SCImago. All books published in the series are submitted for consideration in Web of Science. For proposals from Asia please contact Aninda Bose ([email protected]).

Isak Karabegovic · Ahmed Kovaˇcevi´c · Sadko Mandzuka Editors

New Technologies, Development and Application VI Volume 1

Editors Isak Karabegovic Academy of Sciences and Arts of Bosnia and Herzegovina Sarajevo, Bosnia and Herzegovina

Ahmed Kovaˇcevi´c City University of London London, UK

Sadko Mandzuka Faculty of Traffic and Transport Sciences University of Zagreb Zagreb, Croatia

ISSN 2367-3370 ISSN 2367-3389 (electronic) Lecture Notes in Networks and Systems ISBN 978-3-031-31065-2 ISBN 978-3-031-31066-9 (eBook) https://doi.org/10.1007/978-3-031-31066-9 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Interdisciplinary Research of New Technologies, Their Development and Application

This book features papers focusing on the implementation of new and future technologies, which were presented at the International Conference on New Technologies, Development and Application, held at the Academy of Science and Arts of Bosnia and Herzegovina in Sarajevo on 22nd–24th June 2023. It covers a wide range of future technologies and technical disciplines, including complex systems such as Industry 4.0; patents in industry 4.0; robotics; mechatronics systems; automation; manufacturing; cyber-physical and autonomous systems; sensors; networks; control, energy, renewable energy sources; automotive and biological systems; vehicular networking and connected vehicles; intelligent transport, effectiveness and logistics systems, smart grids, nonlinear systems, power, social and economic systems, education, IoT. Majority of organized conferences are usually focusing on a narrow part of the issues within a certain discipline while conferences such these are rare. There is a need to hold such conferences. The value of this conference is that a various researchers, programmers, engineers and practitioners come to the same place where ideas and latest technology achievements are exchanged. Such events lead to the creation of new ideas, solutions and applications in the manufacturing processes of various technologies. New coexistence is emerging, horizons are expanding, unexpected changes and analogies arise. Best solutions and applications in technologies are critically evaluated. The first chapter covers mechanical design, industry 4.0, robotics, cyber-physical systems, mechatronic systems, automation of production processes, 3D printing, advanced production and metallurgy. The first article is about robotic technology as the basis of implementation of industry 4.0 in production processes in China. The second article presents kinesthetic trajectory learning of a collaborative robot UR 10e with APLC S7-1500. This article shows that with the help of kinesthetic learning the trajectory can be easily modified where programming knowledge for robots is not required. In one of the articles is analysed and developed a robotic arm for space applications. This article illustrates and analyses the design phases, the choice of the kinematics, the static verification, and the modal analysis in different setups of a robotic arm attached to a minisatellite. For this purpose, the propulsion system was carefully chosen, whereas control systems for the arm movement were developed and a feedback controller was chosen. The arm under study was designed to fit a minisatellite, be resistant during orbit, and be able to stabilize the attitude of the robot in orbit. One article aim is to analyse improvement of the technique of optimal technological routes planning for machining of the machine parts surfaces. The developed technique of technological routes planning for the treatment of the parts surfaces by machining allows to analyse of the degree of their material degradation using the LM-hardness method and is realized during the manufacturing of the drum’s shaft of the belt conveyor. The last articles are about mathematics in engineering.

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Interdisciplinary Research of New Technologies

The second chapter covers computer science, information and communication technologies, internet of things, cyber security. The first work is about FPGA based logistics service robot control in e-commerce warehouse system. This article proposes an ecommerce warehousing management concept based on the service mobile robot with a controller implemented on the Altera FPGA Cyclone IV board and Android application for remote control. Second article gives an overview of maintenance strategies using petri net models. The third article is about machine learning model for student drop-out prediction based on student engagement. Article demonstrates how a student drop-out could be predicted through a student’s performance using different Machine Learning techniques, i.e., supervised learning and unsupervised learning. The results show that various types of student engagement are essential factors in predicting drop-out and the final ECTS points achievements. The one article provides edge detection algorithm for biological slice images based on empirical wavelet transform and morphology. The last articles are about application of load cell sensor data collection for strength training and musculoskeletal rehabilitation and mobile applications. The third chapter is devoted to traffic and transport systems, logistics and intelligent systems. Chapter starts with simulation platform for the analysis of motorway traffic safety management systems. Simulation platform is realised in the microsimulation traffic model. The behaviour of drivers in the simulation model is based on Widemann’s car following model. The second work explains that an urban consolidation center is a solution in city logistics that promises traffic-related, environmental, and operational benefits. The third article is about implementation of smart road technologies in the function of road traffic safety management. Another article explains selection of environmentally sustainable means of urban mobility during daily population migration in order to satisfy the need for transportation using methods of multicriteria analysis. Last article examines possibilities of queuing system at postal operators. The fourth chapter is devoted to New Technologies in the Energy, Fluids, Power Quality, and Advanced Electrical Power Systems. The first article analyses important characteristics of hybrid heating systems, such as interoperability, scalability, and availability of energy sources. The purpose is to determine how the availability of different energy sources within a hybrid heating system affects sustainability and environmental impact, as well as how interoperability and scalability can affect the overall performance of the hybrid heating system. The second article is about energy efficiency of industrial drying machine and effects to natural gas consumption and carbon footprint. The third article is about renewable energy sources photovoltaic power plants and constructive solutions related to locality and climate. Another article explains qualitative analysis of the structure of NOx emissions during combustion of pulverized coal and biomass and staged air supply conditions in furnace. Last work is about flue gas emissions on the oxygen-enriched combustion of brown coal and woody biomass. Chapter Five is devoted to new methods in the agriculture, ecology and chemical processes of a wide range of topics. The first article analyses biomedical application of nanocomposites based on fullerenes-C60. Fullerene-C60 nanocomposites are widely used in biomedicine as antioxidants, antiviral agents, HIV-1 protease inhibitors, drug carriers, but also in carcinoma diagnostics and photodynamic therapy. They are also

Interdisciplinary Research of New Technologies

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used as electrochemical sensors and biosensors. Some other topics are chemical analysis of pomegranate fruits taken from different locations in Herzegovina (Bosnia and Herzegovina), the relationship between folic acid and healthy reproduction, effect of baking conditions and recipes on the quality of cookies, review of parasitic nematodes of fish from the Una river (Bosnia and Herzegovina), an investigation of the anthropogenic impact on chemistry, quality indicators and concentrations of selected chemical elements of the river Bregava, the quantum-chemical prediction for some NMR spectral parameters in systems based on aromatic polyamides, contribution to the knowledge of grapevine production in Southeastern Europe – case study of Montenegro. The sixth chapter focuses on the field of geodesy, construction, new materials and sustainable innovation and others. The first article is about structural dynamics of steel frames with the application of friction isolators. In this study, it is proposed to study the dynamic behaviour of ideal regular and irregular structures subjected to seismic actions using a flexible multibody model developed in Simscape within the Simulink environment. The second article presents fire resistance of steel girders. One of article is about design and technology of construction of reinforced soil structures. One other article explains sustainability of the structural construction materials of family houses in Bosnia and Herzegovina and possible alternatives up to sustainable construction principles. The last article is the role of heat pumps in the energy efficiency of buildings: Review. The seventh chapter covers Economics, E-Business, and Entrepreneurships. The chapter starts with the influence of the quality of electronic learning platforms on improving the competences and performance of employees. Second article gives analysis of perception differences of electronic learning quality and content in service businesses. One article is about new technologies and updating of higher education. The paper presents the starting points and guidelines for the reform of higher education for a green and sustainable transition to Society 5.0. The outcomes of the reform should be suitable for those educated in regular programmes, as well as for those who want to acquire additional necessary knowledge and competences. The last articles are about assessment of the readiness of companies for the application of industry 4.0 with the help of an expert system and the impact of digitalization and digital consumption on social development. The whole content of this book is intended to a wide range of technical systems; different technical disciplines in order to apply the latest solutions and achievements in technologies and to improve manufacturing processes in all disciplines where systemic thinking have a very important role in the successful understanding and building of human, natural and social systems. We hope this content will be the first in a series of publications that are intended to the development and implementation of new technologies in all industries. Isak Karabegovi´c

Contents

New Technologies in Mechanical Engineering, Metallurgy, Mechatronics, Robotics and Embedded Systems Robotic Technology as the Basis of Implementation of Industry 4.0 in Production Processes in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Isak Karabegovi´c, Ermin Husak, Edina Karabegovi´c, and Mehmed Mahmi´c Kinesthetic Trajectory Learning of a Collaborative Robot UR 10e with APLC S7-1500 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rok Belšak, Janez Gotlih, Lucijano Berus, and Timi Karner Application of the PFMEA Methodology in a Production Flow with Collaborative Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aurel Mihail T, ît, u, Cristian Vasile Doicin, Nicolae Ionescu, and Vasile Gusan Analysis and Development of a Robotic Arm for Space Applications . . . . . . . . . Carmela Franco, Rosario La Regina, and Carmine Maria Pappalardo Robot-Assisted 3D Laser Surface Hardening of Medium-Carbon Steel: Surface Roughness Parameters and Hardness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dmytro Lesyk, Matej Hruska, Bohdan Mordyuk, Pawel Kochmanski, and Bartosz Powalka

3

19

27

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Nonlinear Control of a Robotic Arm in the Electromechanical Domain . . . . . . . . Rosario La Regina, Maria Curcio, and Carmine Maria Pappalardo

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A New Hybrid PSO-JAYA Algorithm for Function Optimization . . . . . . . . . . . . . Lucijano Berus, Jernej Hernavs, Tadej Peršak, David Potoˇcnik, Simon Klanˇcnik, Janez Gotlih, Timi Karner, and Mirko Ficko

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Characterisation of 17-7PH Steel of Modified State RH 950 with Modified Chemical Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ´ Belma Faki´c and Diana Cubela Gauss-Based Honey Badger Algorithm for Step-Cone Pulley Optimization Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . - Mijodrag Miloševi´c, Dejan Luki´c, Aco Anti´c, Mi´ca Ðurdev, - c Borivoj Novakovi´c, and Luka Ðordevi´

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78

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Contents

Comparison of the Main Parameters of the Steel and Carbon-Fiber-Reinforced Plastic Band Traction Units for Long-Stroke Oil Well Pumps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bogdan Kopei, Ihor Kopei, Volodymyr Kopei, Oleh Onysko, and Vasyl Mykhailiuk Tool Wear in the Process of Drill-String Connector Thread Lathe Machining . . . Oleh Onysko, Volodymyr Kopei, Yaroslav Kusyi, Lolita Pituley, and Iryna Taras

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Simulation of the Structure and Formation Kinetics of a Metastable Modification of Cerium Upon Quenching from a Liquid State . . . . . . . . . . . . . . . . 112 Oleksandr Lysenko, Kalinina Tetiana, Iryna Zagorulko, Predrag Daši´c, and Oleg Popil Designing the Optimal Geometry of Multi-stage Tools . . . . . . . . . . . . . . . . . . . . . . 123 Mirna Noži´c and Himzo Ðuki´c Research of the Surface Oil Absorption Processed by Vibration Rolling and Deforming Broaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Ihor Shepelenko, Evhen Solovykh, Oleh Bevz, Stanislav Katerynych, and Andrey Solovuch Genetic Algorithams Modeling of Cutting Forces During Turning Hard Steel for Economic Sustanable Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Pavel Kovaˇc, Mirfad Tari´c, Borislav Savkovi´c, Dušan Ješi´c, and Branislav Dudi´c Analysis of Some Parameters in Explosive Forming . . . . . . . . . . . . . . . . . . . . . . . . 149 Darko Šunji´c, Stipo Buljan, and Eduarda Gomes Design and Manufacturing of Conformal Cooling Channels for Injection Molding: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 Janez Gotlih, Timi Karner, Rok Belšak, Mirko Ficko, Lucijano Berus, Tomaž Brajlih, Snehashis Pal, and Miran Brezoˇcnik Mind Maps for Key Points of a Reverse Engineering Project . . . . . . . . . . . . . . . . . 170 Svitlana Ivanova, Lubomir Dimitrov, Viktor Ivanov, Galyna Urum, and Olena Olefir Heuristic Search for the Design of Silent Chain Transmissions Using Graphs . . . 182 Svitlana Ivanova, Lubomir Dimitrov, Viktor Ivanov, Anatolii Konoplov, and Natalia Cheredarchuk

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Continuous Improvement and Performance Assessment in Knowledge-Based Organizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Aurel Mihail Titu, Andreea Maria Ungureanu, and Florin-Alexandru Lungu Cognitive Cyber-Physical Production Systems: A New Concept of Manufacturing Systems on the Route to Industry 5.0 . . . . . . . . . . . . . . . . . . . . . 201 Elvis Hozdi´c and Zoran Jurkovi´c Construction of an Automated Door as a Smart Device . . . . . . . . . . . . . . . . . . . . . . 213 Mehmed Cobo, Alma Žiga, and Malik Cabaravdic Improvement of the Technique of Optimal Technological Routes Planning for Machining of the Machine Parts Surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Yaroslav Kusyi, Oleh Onysko, Andrii Kuk, Olha Kostiuk, and Bohdan Solohub 3D Printed Souvenir with Mechanical Iris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Žiga Alma, Kaˇcmarˇcik Josip, and Behadarevi´c Ismir Multi-response Optimization of FDM Process Parameters Using Taguchi Based Grey Relational Analysis Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Kenan Muhamedagic, Ahmet Cekic, Derzija Begic-Hajdarevic, and Amina Ramljak Development and Design of Air Purifier Device Prototype . . . . . . . . . . . . . . . . . . . 249 Vedad Saletovi´c, Adis J. Muminovi´c, Isad Šari´c, and Nedim Pervan The Influence of Technological Parameters on the Geometric Product Specification of the Parts Manufactured by the Fused Deposition Modeling . . . . 260 Vladimir Blanuša, Dejan Movrin, Branko Štrbac, Miodrag Hadžistevi´c, and Miloš Ranisavljev Dimensional and Positional Control of Industrial Workpiece Using CMM and Optical 3D Scanner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Kenan Varda, Almira Softi´c, Nermina Zaimovi´c-Uzunovi´c, and Sabina Serdarevi´c-Kadi´c 3D Printed Toys for Children with Disabilities – Study Case in Montenegro . . . . 276 Mihailo Jovanovic, Milena Djukanovic, Anita Maric, and Andrea Medin Calibration of Test and Measuring Equipment in Pandemic Conditions . . . . . . . . 283 Belma Faki´c, Samir Lemeš, Branka Muminovi´c, Omer Beganovi´c, Mustafa Hadžali´c, and Kenan Varda

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Numerical Simulation of Viscoelastic Fluid Flow in a Channel . . . . . . . . . . . . . . . 291 Almin Halaˇc and Ejub Džaferovi´c Using Fractal Dimensions in Modeling Complex Systems in Engineering . . . . . . 298 Maryna Holofieieva, Volodymyr Tonkonogyi, Iraida Stanovska, Andrii Pavlyshko, and Sergii Klimov Vibration Infrared Thermal Method of Defectoscopy of Non-metallic Heterogeneous Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Volodymyr Tonkonogyi, Oleksandr Stanovskyi, Maryna Holofieieva, Oleksandr Levynskyi, and Sergii Klimov The Possibility of Applying ChatGPT (AI) for Calculations in Mechanical Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313 Dragi Tiro Performance Comparison of the Simscape Multibody Solvers for Articulated Mechanical Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 Ömer Ekim Genel, Rosario La Regina, and Carmine Maria Pappalardo Virtual Prototyping of a Dynamic Vibration Absorber for the Vibration Control of a Frame Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 Giuseppe Isola, Rosario La Regina, Carmine Maria Pappalardo, and Valentino Paolo Berardi Conditions for Amorphization of Ce-Ag Alloys During Quenching from a Liquid State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 Tetiana V. Kalinina, Oleksandr B. Lysenko, Vladeta Jevremovi´c, Anton V. Khliebnikov, and Tetiana N. Dorozhka System Identification of a Nonlinear One-Degree-of-Freedom Vibrating System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 ˙ S¸ efika Ipek Lök, Carmine Maria Pappalardo, Rosario La Regina, and Levent Malgaca Multibody Modeling of a Serial Manipulator for In-Space Applications . . . . . . . 356 Salvio Veneziano and Marco Claudio De Simone Design of an Instrumented Rail Seat Test-Rig for Continuous Vehicle Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365 Giampiero Celenta, Tony Luigi Leopoldo Lenza, and Marco Claudio De Simone

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Analysis and Design of Test-Rigs for Laboratory Tests Under Microgravity Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 Salvio Veneziano, Giampiero Celenta, and Marco Claudio De Simone Contributions Regarding the Implementation of the Digital Archiving Process in a Public Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381 Constantin Dorin Olteanu, Cristian Vasile Doicin, Nicolae Ionescu, and Aurel Mihail T, ît, u Industry 4.0 Readiness Assesment: Human Resource Readiness and Active Role of Government Administration for Transitional Context of Bosnia and Herzegovina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 ´ Savo Stupar, and Munira Šesti´c Isak Karabegovi´c, Mirha Biˇco Car, Strategies for Reducing Excess and Obsolete Inventory . . . . . . . . . . . . . . . . . . . . . 396 Emir Halilovi´c, Hadis Bajri´c, Kristian Melin, and Ermin Neimarlija Product Life Cycle in Automotive Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411 Adrian Bogorin-Predescu, Stefan T, ît, u, and Aurel Mihail T, ît, u Assembly and Maintenance of High Bay Warehouses on a Practical Example of a Metal Structure Installation Project . . . . . . . . . . . . . . . . . . . . . . . . . . 418 Ismar Alagi´c Global Dynamics of a Certain Nonlinear System of Differential Equations with the Appearance of Hopf Bifurcation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 427 Vahidin Hadžiabdi´c, Midhat Mehulji´c, Jasmin Bekteševi´c, Adnan Maši´c, and Nedim Pervan The Global Behavior of a Certain General Difference Polynomial Equation . . . . 434 Jasmin Bekteševi´c, Vahidin Hadžiabdi´c, Midhat Mehulji´c, Adnan Maši´c, and Fatih Destovi´c Local Dynamics and Global Behavior of Certain Second Order Nonlinear Difference Equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 442 Midhat Mehulji´c, Jasmin Bekteševi´c, Vahidin Hadžiabdi´c, Sadjit Metovi´c, and Adnan Maši´c An Approach to Dynamic Modelling of Industrial Robots Based on 3D Cad Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 450 Maida Cohodar Husic, Mirko Ficko, Derzija Begic-Hajdarevic, Tadej Persak, Ahmet Cekic, and Simon Klancnik

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Contents

Electrical Engineering, Computer Science, Information and Communication Technologies, Control Systems FPGA Based Logistics Service Robot Control in E-Commerce Warehouse System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 461 Lejla Banjanovi´c-Mehmedovi´c, Lejla Husi´c, Anel Husakovi´c, and Nermin Sarajli´c An Overview of Maintenance Strategies Using Petri Net Models . . . . . . . . . . . . . 470 Ilija Hristoski and Tome Dimovski Digital Twins Data Visualization Methods. Problems of Human Interaction: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478 Yevhen Palazhchenko, Vira Shendryk, and Sergii Shendryk Machine Learning Model for Student Drop-Out Prediction Based on Student Engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486 Lucija Brezoˇcnik, Giacomo Nalli, Renato De Leone, Sonia Val, Vili Podgorelec, and Sašo Karakatiˇc Prototyping IoT Technology Solutions Using LoRaWAN Infrastructure . . . . . . . 497 Amir Hajdar and Samim Konjicija A Review of Research Progress and Application of Wavelet Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504 Tonghao Wang, Vincenzo Guercio, Piercarlo Cattani, and Francesco Villecco Motion Synchronization for Bilateral Control Systems . . . . . . . . . . . . . . . . . . . . . . 516 - Viteški´c, Amel Ramdedovi´c, Šejla Džakmi´c, Nada and Mohammad Adnan Diab Alrefaee Edge Detection Algorithm for Biological Slice Images Based on Empirical Wavelet Transform and Morphology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524 Yafei Liu, Vincenzo Guercio, Piercarlo Cattani, and Francesco Villecco Cybersecurity Challenges in Modern Supply Chain . . . . . . . . . . . . . . . . . . . . . . . . . 534 ˇ cak Gordana Zeba and Mirjana Ciˇ The Effect of Online Learning Setting on Motivation, Intended Effort, Emotional Engagement, and Language Learning Strategies Among Non-english Majors in Croatia – A Pilot Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 542 Zrinka Fišer

Contents

xv

Cyber Violence Form of Domestic Violence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 550 Petric˘a Tertereanu, Mihai Dragomir, and Aurel Mihail T, ît, u Anomaly Detection and Classification in Agricultural Produce Using Image Processing and CNN Assisted by a Robotic Arm . . . . . . . . . . . . . . . . . . . . . 557 Varsha Viswanathan, Supraajha Murali, and Venkatakrishnan Veeraraghavan On the Optimal Design of a Scale-Free Supply Network . . . . . . . . . . . . . . . . . . . . 562 Piercarlo Cattani and Francesco Villecco Remote Liquid Level Monitoring Based on IoT Technology . . . . . . . . . . . . . . . . . 571 Vito Tiˇc Internet of Things in the Construction Industry: A General Overview . . . . . . . . . 577 Angelo Lorusso and Giampiero Celenta Challenges and Benefits of Using Digital Twin Technology . . . . . . . . . . . . . . . . . . 585 ´ and Munira Šesti´c Savo Stupar, Mirha Biˇco Car, Application of Load Cell Sensor Data Collection for Strength Training and Musculoskeletal Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596 Amir Hajdar, Ensar Abazovi´c, and Armin Paravli´c Mobile Application mScheduler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 602 Suad Su´ceska Intelligent Transport Systems, Logistics, Traffic Control Simulation Platform for the Analysis of Motorway Traffic Safety Management Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 609 Sadko Mandžuka, Luka Dedi´c, Goran Kos, and Krešimir Vidovi´c Virtual Urban Consolidation Center . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 616 Reinhold Schodl and Sandra Eitler Implementation of Smart Road Technologies in the Function of Road Traffic Safety Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 621 Osman Lindov and Adnan Omerhodži´c Sustainable Mobility: Conceptual Aspects of Development and Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 628 Natalya Shramenko and Christoph Hupfer

xvi

Contents

Application of Innovative Technologies to Improve Urban Delivery in the City of Sarajevo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 639 Ermin Muharemovi´c, Amel Kosovac, Belma Memi´c, and Elma Avdagi´c-Golub Application of Intelligent Transport Systems in Road Traffic: A Review . . . . . . . 646 Nadica Stojanovic, Ivan Grujic, and Bojana Boskovic Creating Ontologies Concept in Transport and Traffic Research Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 652 Pero Škorput and Krešimir Vidovi´c Estimating Urban Air Quality According to Sustainable Development Goal 11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 659 Belma Memi´c, Elma Avdagi´c-Golub, Amel Kosovac, and Ermin Muharemovi´c Application of the ITS System in Limiting the Access of Road Vehicles to Parts of Urban Zones in Sarajevo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 667 Mirzet Sarajli´c, Drago Ezgeta, and Ajdin Džananovi´c The Possibility of Using Drones in the Process of Delivery in the Area of the City of Sarajevo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675 Amel Kosovac, Adisa Medi´c, Muharem Šuli´c, and Haris Mehiˇci´c Selection of Environmentally Sustainable Means of Urban Mobility During Daily Population Migration in Order to Satisfy the Need for Transportation Using Methods of Multicriteria Analysis . . . . . . . . . . . . . . . . . 683 Mirzet Sarajli´c, Adnan Omerhodži´c, Ajdin Džananovi´c, and Adnan Tatarevi´c Advanced Traffic Management System in the Function of Improving Mobility in the City of Sarajevo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 690 Kamenjaševi´c Nedim, Mehanovi´c Mustafa, and Mirzet Sarajli´c Challenges of Physical and Digital Integration of Transport Infrastructure in Bosnia and Herzegovina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 696 ˇ Drago Ezgeta, Samir Cauševi´ c, and Mustafa Mehanovi´c Dynamic Traffic Flow Assignment on Parallel Networks . . . . . . . . . . . . . . . . . . . . 702 Armen Bagdasaryan, Antonios Kalampakas, and Mansoor Saburov Sustainable Mobility: Changing Mindsets and Rethinking Paradigms . . . . . . . . . 712 Natalya Shramenko and Christoph Hupfer

Contents

xvii

Model of Optimization of Cargo Space Volume Utilization in Delivery Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 722 Maida Eljazovi´c and Ermin Muharemovi´c Mobility-as-a-Service and the Future of Urban Mobility: A Human-Centered Approach to Multimodal Journey Planning . . . . . . . . . . . . . . 729 Bia Mandžuka, Marinko Jurˇcevi´c, and Krešimir Vidovi´c Possibilities of Queuing System at Postal Operators . . . . . . . . . . . . . . . . . . . . . . . . 739 Mladenka Blagojevi´c, Dragana Šarac, Amel Kosovac, and Ermin Muharemovi´c Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 747

List of Contributors

Ensar Abazovi´c Faculty of Sport and Physical Education, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Ismar Alagi´c International University of Sarajevo, Ilidža - Sarajevo, Bosnia and Herzegovina; Faculty of Mechanical Engineering, University of Zenica, Zenica, Bosnia and Herzegovina Žiga Alma Faculty of Mechanical Engineering, University of Zenica, Zenica, Bosnia and Herzegovina Mohammad Adnan Diab Alrefaee Electrical and Electronics Engineering, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina Aco Anti´c Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia Elma Avdagi´c-Golub Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Armen Bagdasaryan College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait Hadis Bajri´c Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Lejla Banjanovi´c-Mehmedovi´c Faculty of Electrical Engineering, University of Tuzla, Tuzla, Bosnia and Herzegovina Omer Beganovi´c University of Zenica, Institute “Kemal Kapetanovi´c”, Zenica, Bosnia and Herzegovina Derzija Begic-Hajdarevic Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Jasmin Bekteševi´c Faculty of Mechanical Engineering, Department of Mathematics and Physics, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Rok Belšak Faculty of Mechanical Engineering, Laboratory for Robotisation, University of Maribor, Maribor, Slovenia Valentino Paolo Berardi Department of Industrial Engineering, University of Salerno, Fisciano, Italy Lucijano Berus Faculty of Mechanical Engineering, Production Engineering Institute, Laboratory for Robotisation, University of Maribor, Maribor, Slovenia Oleh Bevz Central Ukrainian National Technical University, Kropyvnytskyi, Ukraine

xx

List of Contributors

´ Mirha Biˇco Car School of Economics and Business, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Mladenka Blagojevi´c Faculty of Transport and Traffic Engineering, University of Belgrade, Beograd, Serbia Vladimir Blanuša The Higher Education Technical School of Professional Education, Novi Sad, Serbia Adrian Bogorin-Predescu University POLITEHNICA of Bucharest, Bucures, ti, Romania Bojana Boskovic Department in Trstenik, Academy of Professional Studies Šumadija, Kragujevac, Serbia Tomaž Brajlih Faculty of Mechanical Engineering, University of Maribor, Maribor, Slovenia Lucija Brezoˇcnik Intelligent Systems Laboratory, Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia Miran Brezoˇcnik Faculty of Mechanical Engineering, University of Maribor, Maribor, Slovenia Stipo Buljan Federal Ministry of Energy, Mining and Industry, Mostar, Bosnia and Herzegovina Malik Cabaravdic Faculty of Mechanical Engineering, University of Zenica, Zenica, Bosnia and Herzegovina Piercarlo Cattani Department of Computer, Control and Management Engineering, University of Rome “La Sapienza”, Roma, Italy ˇ Samir Cauševi´ c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Ahmet Cekic Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Giampiero Celenta MEID4 Academic Spin-Off of the University of Salerno, Fisciano, Italy Natalia Cheredarchuk Odesa National Maritime University, Odesa, Ukraine ˇ cak Mechanical Engineering Faculty, University of Slavonski Brod, Mirjana Ciˇ Slavonski Brod, Croatia Mehmed Cobo FabLab, Sarajevo, Bosnia and Herzegovina Maida Cohodar Husic Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina ´ Diana Cubela Metallurgical and Technological Faculty, University of Zenica, Zenica, Bosnia and Herzegovina

List of Contributors

xxi

Maria Curcio MEID4 Academic Spin-Off of the University of Salerno, Fisciano, Italy Predrag Daši´c Academy of Professional Studies Šumadija – Department in Trstenik, Trstenik, Serbia Marco Claudio De Simone Department of Industrial Engineering, University of Salerno, Fisciano, Italy Luka Dedi´c Promettis Ltd, Zagreb, Croatia Renato De Leone School of Science and Technology, University of Camerino, Camerino, Italy Fatih Destovi´c Faculty of Educational Sciences, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Lubomir Dimitrov Technical University of Sofia, Sofia, Bulgaria Tome Dimovski Faculty of Information and Communication Technologies – Bitola, “St. Kliment Ohridski” University – Bitola, Bitola, North Macedonia Milena Djukanovic Faculty of Electrical Engineering, University of Montenegro, Podgorica, Montenegro Cristian Vasile Doicin Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest, Bucharest, Romania - c Technical Faculty “Mihajlo Pupin” Zrenjanin, University of Novi Sad, Luka Ðordevi´ Zrenjanin, Serbia Tetiana N. Dorozhka Dniprovsk State Technical University (DSTU), Kamianske, Ukraine Mihai Dragomir Technical University of Cluj-Napoca, Cluj-Napoca, Romania Branislav Dudi´c Faculty of Management, Comenius University in Bratislava, Bratislava, Slovakia; Faculty of Economics and Engineering Management, University Business Academy, Novi Sad, Serbia Himzo Ðuki´c University of Mostar FSRE, Mostar, Bosnia and Herzegovina Mi´ca Ðurdev Technical Faculty “Mihajlo Pupin” Zrenjanin, University of Novi Sad, Zrenjanin, Serbia Ejub Džaferovi´c Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Šejla Džakmi´c Electrical and Electronics Engineering, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina Ajdin Džananovi´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Sandra Eitler University of Applied Sciences BFI Vienna, Vienna, Austria

xxii

List of Contributors

Maida Eljazovi´c Nelt Ltd., East Sarajevo, Bosnia and Herzegovina; Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Drago Ezgeta Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Belma Faki´c Institute “Kemal Kapetanovi´c” of Zenica, University of Zenica, Zenica, Bosnia and Herzegovina Mirko Ficko Faculty of Mechanical Engineering, Production Engineering Institute, University of Maribor, Maribor, Slovenia Zrinka Fišer University of Slavonski Brod EDUDpt, Slavonski Brod, Croatia Carmela Franco MEID4 Academic Spin-Off of the University of Salerno, Fisciano, Italy Ömer Ekim Genel Department of Mechanical Engineering, Istanbul Technical University, Istanbul, Turkey Eduarda Gomes proMetheus, Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal Janez Gotlih Faculty of Mechanical Engineering, Production Engineering Institute, Laboratory for Robotisation, University of Maribor, Maribor, Slovenia Ivan Grujic Faculty of Engineering, University of Kragujevac, Kragujevac, Serbia Vincenzo Guercio Engineering School, Deim, University of Tuscia, Largo dell’Università, Viterbo, Italy Vasile Gusan Faculty of Industrial Engineering POLITEHNICA of Bucharest, Bucharest, Romania

and

Robotics,

University

Mustafa Hadžali´c University of Zenica, Institute “Kemal Kapetanovi´c”, Zenica, Bosnia and Herzegovina Vahidin Hadžiabdi´c Faculty of Mechanical Engineering, Department of Mathematics and Physics, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Miodrag Hadžistevi´c Faculty of Technical Sciences, Novi Sad, Serbia Amir Hajdar Institute for Geodesy and Geoinformatics, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Almin Halaˇc Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Emir Halilovi´c Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Jernej Hernavs Faculty of Mechanical Engineering, Production Engineering Institute, University of Maribor, Maribor, Slovenia

List of Contributors

xxiii

Maryna Holofieieva Department of Digital Technologies in Engineering, Department of Information Technologies in Design, Odessa National Polytechnic University, Odessa, Ukraine Elvis Hozdi´c Faculty of Mechanical Engineering, University of Novo mesto, Novo mesto, Slovenia Ilija Hristoski Faculty of Economics – Prilep, “St. Kliment Ohridski” University – Bitola, Prilep, North Macedonia Matej Hruska New Technologies Research Centre, University of West Bohemia, Pilsen, Czech Republic Christoph Hupfer Baden-Württemberg Institute of Sustainable Mobility, Hochschule Karlsruhe University of Applied Sciences, Karlsruhe, Germany Ermin Husak Technical Faculty Biha´c, Univesity of Biha´c,, Biha´c, Bosnia and Herzegovina Anel Husakovi´c Faculty of Mechanical Engineering, University of Zenica, Zenica, Bosnia and Herzegovina Lejla Husi´c Faculty of Electrical Engineering, University of Tuzla, Tuzla, Bosnia and Herzegovina Nicolae Ionescu Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest, Bucharest, Romania Behadarevi´c Ismir Faculty of Mechanical Engineering, University of Zenica, Zenica, Bosnia and Herzegovina Giuseppe Isola MEID4 Academic Spin-Off of the University of Salerno, Fisciano, Italy Svitlana Ivanova South Ukrainian National Pedagogical University Named After K.D. Ushynsky, Odesa, Ukraine Viktor Ivanov Odesa National Maritime University, Odesa, Ukraine Vladeta Jevremovi´c Academy of Professional Studies Šumadija – Department in Trstenik, Trstenik, Serbia Dušan Ješi´c International Technology and Management Academy – MTMA, Novi Sad, Serbia Kaˇcmarˇcik Josip Faculty of Mechanical Engineering, University of Zenica, Zenica, Bosnia and Herzegovina Mihailo Jovanovic Faculty of Management Herceg Novi, Adriatik University, Herceg Novi, Montenegro Zoran Jurkovi´c Faculty of Engineering, University of Rijeka, Rijeka, Croatia Marinko Jurˇcevi´c Faculty of Transport and Traffic Sciences, Zagreb, Croatia

xxiv

List of Contributors

Antonios Kalampakas College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait Tetiana V. Kalinina Dniprovsk State Technical University (DSTU), Kamianske, Ukraine Edina Karabegovi´c Technical Faculty Biha´c, Univesity of Biha´c,, Biha´c, Bosnia and Herzegovina Isak Karabegovi´c Academy of Sciences and Arts of Bosnia and Herzegovina, Sarajevo, Bosnia and Herzegovina Sašo Karakatiˇc Intelligent Systems Laboratory, Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia Timi Karner Faculty of Mechanical Engineering, Production Engineering Institute, Laboratory for Robotisation, University of Maribor, Maribor, Slovenia Stanislav Katerynych Central Ukrainian National Technical University, Kropyvnytskyi, Ukraine Anton V. Khliebnikov Dniprovsk State Technical University (DSTU), Kamianske, Ukraine Simon Klancnik Faculty of Mechanical Engineering, University of Maribor, Maribor, Slovenia Simon Klanˇcnik Faculty of Mechanical Engineering, Production Engineering Institute, University of Maribor, Maribor, Slovenia Sergii Klimov Department of Information Technologies in Design, Odessa National Polytechnic University, Odessa, Ukraine Pawel Kochmanski Mechanical Engineering and Mechatronics Department, West Pomeranian University of Technology, Szczecin, Poland Samim Konjicija Faculty of Electrical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Anatolii Konoplov Odesa National Maritime University, Odesa, Ukraine Bogdan Kopei Ivano-Frankivsk National Technical University of Oil and Gas, IvanoFrankivsk, Ukraine Ihor Kopei Ivano-Frankivsk National Technical University of Oil and Gas, IvanoFrankivsk, Ukraine Volodymyr Kopei Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine Goran Kos Institut for TourismVrhovec 5, Zagreb, Croatia Amel Kosovac Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

List of Contributors

xxv

Olha Kostiuk Department “Computerized Mechanical Engineering”, Institute of Mechanical Engineering, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine Pavel Kovaˇc Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia Andrii Kuk Department “Computerized Mechanical Engineering”, Institute of Mechanical Engineering, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine Yaroslav Kusyi Ivano-Frankivsk National Technical University of Oil and Gas, IvanoFrankivsk, Ukraine Yaroslav Kusyi Department “Robotics and Integrated Mechanical Engineering Technologies”, Institute of Mechanical Engineering and Transport, Lviv Polytechnic National University, Lviv, Ukraine Rosario La Regina MEID4 Academic Spin-Off of the University of Salerno, Fisciano, Italy Samir Lemeš Polytechnic Faculty, University of Zenica, Zenica, Bosnia and Herzegovina Tony Luigi Leopoldo Lenza Department of Industrial Engineering, University of Salerno, Fisciano, Italy Dmytro Lesyk Laser Systems and Advanced Technologies Department, “Igor Sikorsky Kyiv Polytechnic Institute”, National Technical University of Ukraine, Kyiv, Ukraine; Principles for Surface Engineering Department, G.V. Kurdyumov Institute for Metal Physics of the NAS of Ukraine, Kyiv, Ukraine; Mechanical Engineering and Mechatronics Department, West Pomeranian University of Technology, Szczecin, Poland Oleksandr Levynskyi Department of Information Technologies in Design, Odessa National Polytechnic University, Odessa, Ukraine Osman Lindov Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Yafei Liu College of Information and Electrical Engineering, China Agricultural University, Beijing, China Angelo Lorusso Department of Industrial Engineering, University of Salerno, Fisciano, SA, Italy Dejan Luki´c Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia Florin-Alexandru Lungu National Research and Development Institute for Cryogenics and IsotopicTechnologies, RamnicuValcea, Romania Oleksandr Lysenko Dniprovsk State Technical University, Kamyanske, Ukraine

xxvi

List of Contributors

Oleksandr B. Lysenko Dniprovsk State Technical University (DSTU), Kamianske, Ukraine ˙ Sefika ¸ Ipek Lök Department of Mechatronics Engineering, The Graduate School of Natural and Applied Sciences, DokuzEylul University, ˙Izmir, Türkiye Mehmed Mahmi´c Technical Faculty Biha´c, Univesity of Biha´c, Biha´c, Bosnia and Herzegovina Levent Malgaca Department of Mechanical Engineering, DokuzEylul University, Izmir, Türkiye Bia Mandžuka Faculty of Transport and Traffic Sciences, Zagreb, Croatia Sadko Mandžuka Faculty of Traffic and Transport Sciences, Zagreb, Croatia Anita Maric Government of Montenegro, Bureau for Education Services, Podgorica, Montenegro Adnan Maši´c Faculty of Mechanical Engineering, Department of Mathematics and Physics, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Andrea Medin Faculty of Mechanical Engineering, University of Montenegro, Podgorica, Montenegro Adisa Medi´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Mustafa Mehanovi´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Haris Mehiˇci´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Midhat Mehulji´c Faculty of Mechanical Engineering, Department of Mathematics and Physics, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Kristian Melin Lut University Lahti Campus, Lahti, Finland Belma Memi´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Sadjit Metovi´c Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Mijodrag Miloševi´c Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia Bohdan Mordyuk Principles for Surface Engineering Department, G.V. Kurdyumov Institute for Metal Physics of the NAS of Ukraine, Kyiv, Ukraine Dejan Movrin Faculty of Technical Sciences, Novi Sad, Serbia Kenan Muhamedagic Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

List of Contributors

xxvii

Ermin Muharemovi´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Adis J. Muminovi´c Department of Mechanical Design, Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Branka Muminovi´c University of Zenica, Institute “Kemal Kapetanovi´c”, Zenica, Bosnia and Herzegovina Supraajha Murali Department of Computer Science and Engineering, Easwari Engineering College, Chennai, India Mehanovi´c Mustafa Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Vasyl Mykhailiuk Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine Giacomo Nalli School of Science and Technology, University of Camerino, Camerino, Italy Kamenjaševi´c Nedim Cantonal Administration for Inspection Issues Canton Sarajevo, Olovo, Sarajevo, Bosnia and Herzegovina Ermin Neimarlija School of Economics and Business, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Borivoj Novakovi´c Technical Faculty “Mihajlo Pupin” Zrenjanin, University of Novi Sad, Zrenjanin, Serbia Mirna Noži´c Faculty of Mechanical Engineering, University “DžemalBijedi´c” of Mostar, Mostar, Bosnia and Herzegovina Olena Olefir South Ukrainian National Pedagogical University Named After K.D. Ushynsky, Odesa, Ukraine Constantin Dorin Olteanu Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest, Bucharest, Romania Adnan Omerhodži´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Oleh Onysko Department “Computerized Mechanical Engineering”, Institute of Mechanical Engineering, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine Snehashis Pal Faculty of Mechanical Engineering, University of Maribor, Maribor, Slovenia Yevhen Palazhchenko Information Technologies Department, Sumy State University, Sumy, Ukraine Carmine Maria Pappalardo Department of Industrial Engineering, University of Salerno, Fisciano, Italy

xxviii

List of Contributors

Armin Paravli´c Faculty of Sport, Institute ofKinesiology, University of Ljubljana, Ljubljana, Slovenia Andrii Pavlyshko Department of Information Technologies in Design, Odessa National Polytechnic University, Odessa, Ukraine Tadej Persak Faculty of Mechanical Engineering, University of Maribor, Maribor, Slovenia Nedim Pervan Faculty of Mechanical Engineering, Department of Mechanical Design, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Tadej Peršak Faculty of Mechanical Engineering, Production Engineering Institute, University of Maribor, Maribor, Slovenia Lolita Pituley Ivano-Frankivsk National Technical University of Oil and Gas, IvanoFrankivsk, Ukraine Vili Podgorelec Intelligent Systems Laboratory, Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia Oleg Popil Dniprovsk State Technical University, Kamyanske, Ukraine David Potoˇcnik Faculty of Mechanical Engineering, Production Engineering Institute, University of Maribor, Maribor, Slovenia Bartosz Powalka Mechanical Engineering and Mechatronics Department, West Pomeranian University of Technology, Szczecin, Poland Amel Ramdedovi´c Electrical and Electronics Engineering, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina Amina Ramljak Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Miloš Ranisavljev Faculty of Technical Sciences, Novi Sad, Serbia Mansoor Saburov College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait Vedad Saletovi´c Department of Mechanical Design, Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Dragana Šarac Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia Mirzet Sarajli´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Mirzet Sarajli´c Ministry of Transport Canton Sarajevo, Sarajevo, Bosnia and Herzegovina Nermin Sarajli´c Faculty of Electrical Engineering, University of Tuzla, Tuzla, Bosnia and Herzegovina

List of Contributors

xxix

Isad Šari´c Department of Mechanical Design, Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Borislav Savkovi´c Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia Reinhold Schodl University of Applied Sciences BFI Vienna, Vienna, Austria Sabina Serdarevi´c-Kadi´c Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Munira Šesti´c School of Economics and Business, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Sergii Shendryk Sumy National Agrarian University, Sumy, Ukraine Vira Shendryk Information Technologies Department, Sumy State University, Sumy, Ukraine Ihor Shepelenko Central Ukrainian National Technical University, Kropyvnytskyi, Ukraine Natalya Shramenko Baden-Württemberg Institute of Sustainable Mobility, Hochschule Karlsruhe University of Applied Sciences, Karlsruhe, Germany Pero Škorput Faculty of Traffic and Transport Sciences, Zagreb, Croatia Almira Softi´c Faculty of Mechanical Engineering, University of Zenica, Zenica, Bosnia and Herzegovina Bohdan Solohub Department “Computerized Mechanical Engineering”, Institute of Mechanical Engineering, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine Andrey Solovuch Central Ukrainian National Technical University, Kropyvnytskyi, Ukraine Evhen Solovykh Central Ukrainian National Technical University, Kropyvnytskyi, Ukraine Iraida Stanovska Department of Higher Mathematics and Systems Modeling, Odessa National Polytechnic University, Odessa, Ukraine Oleksandr Stanovskyi Department of Information Technologies in Design, Odessa National Polytechnic University, Odessa, Ukraine Nadica Stojanovic Faculty of Engineering, University of Kragujevac, Kragujevac, Serbia Branko Štrbac Faculty of Technical Sciences, Novi Sad, Serbia Savo Stupar School of Economics and Business, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Suad Su´ceska Sarajevo, Bosnia and Herzegovina

xxx

List of Contributors

Muharem Šuli´c Faculty of Traffic and Communications, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Darko Šunji´c Faculty of Mechanical Engineering, Computing and Electrical Engineering, University of Mostar, Mostar, Bosnia and Herzegovina Iryna Taras Ivano-Frankivsk National Technical University of Oil and Gas, IvanoFrankivsk, Ukraine Mirfad Tari´c Srednja škola metalskih zanimanja, Sarajevo, Bosnia and Herzegovina Adnan Tatarevi´c Institute of Traffic and Communications, Sarajevo, Bosnia and Herzegovina Petric˘a Tertereanu Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest, Bucharest, Romania Kalinina Tetiana Dniprovsk State Technical University, Kamyanske, Ukraine Vito Tiˇc Faculty of Mechanical Engineering, University of Maribor, Maribor, Slovenia Dragi Tiro University “DžemalBijedi´c” of Mostar, Mostar, Bosnia and Herzegovina Aurel Mihail T, ît, u Lucian Blaga University of Sibiu, Sibiu, Romania; The Academy of Romanian Scientists, Bucharest, Romania Stefan T, ît, u Iuliu Hat, ieganu University of Medicine and Pharmacy, Cluj Napoca, Romania Volodymyr Tonkonogyi Department of Information Technologies in Design, Odessa National Polytechnic University, Odessa, Ukraine Andreea Maria Ungureanu Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest, Bucharest, Romania Galyna Urum South Ukrainian National Pedagogical University Named After K.D. Ushynsky, Odesa, Ukraine Sonia Val School of Engineering and Architecture, University of Zaragoza, Zaragoza, Spain Kenan Varda Faculty of Mechanical Engineering, Automation and Metrology Department, University of Zenica, Zenica, Bosnia and Herzegovina Venkatakrishnan Veeraraghavan Department of Computer Science and Engineering, Easwari Engineering College, Chennai, India Salvio Veneziano MEID4 Academic Spin-Off of the University of Salerno, Fisciano, Italy Krešimir Vidovi´c Ericsson Nikola Tesla, Zagreb, Croatia Krešimir Vidovi´c Faculty of Transport and Traffic Sciences, Zagreb, Croatia

List of Contributors

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Francesco Villecco Department of Industrial Engineering, University of Salerno, Fisciano, Italy Varsha Viswanathan Department of Computer Science and Engineering, Easwari Engineering College, Chennai, India - Viteški´c Electrical and Electronics Engineering, International University of Nada Sarajevo, Sarajevo, Bosnia and Herzegovina Tonghao Wang College of Information and Electrical Engineering, China Agricultural University, Beijing, China Iryna Zagorulko G.V. Kurdyumov Institute for Metal Physics of the N.A.S. of Ukraine, Kyiv, Ukraine Nermina Zaimovi´c-Uzunovi´c Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Gordana Zeba Mechanical Engineering Faculty, University of Slavonski Brod, Slavonski Brod, Croatia Alma Žiga Faculty of Mechanical Engineering, University of Zenica, Zenica, Bosnia and Herzegovina

New Technologies in Mechanical Engineering, Metallurgy, Mechatronics, Robotics and Embedded Systems

Robotic Technology as the Basis of Implementation of Industry 4.0 in Production Processes in China Isak Karabegovi´c1(B) , Ermin Husak2 , Edina Karabegovi´c2 , and Mehmed Mahmi´c2 1 Academy of Sciences and Arts of Bosnia and Herzegovina, Bistrik 7, 71000 Sarajevo, Bosnia

and Herzegovina 2 Technical Faculty Biha´c, Univesity of Biha´c, , Ul.Irfana Ljubijanki´ca Bb, 77000 Biha´c, Bosnia

and Herzegovina

Abstract. The implementation of Industry 4.0 has been intensively present in the surrounding countries in the last five to six years. However, its concept is not widespread enough in production processes in the world. Its implementation will improve many aspects of human life in all segments of society. The business paradigm and production models will change at all levels of production processes, including the supply chain. Major changes have taken place in the recent years, such as the transformation of production systems, consumption, delivery, logistics, etc., all due to the implementation of the latest technological discoveries such as: robotics, automation, 3D printing, Internet of Things (IoT), smart sensors, Big Data, Cloud Computing, Radio Frequency Identification (RFID), Virtual and Augmented Reality (AR), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), etc. The implementation strategy of Industry 4.0 consists of adapting industrial production to complete smart automation, which means introducing methods of self-automation, self-configuration, self-diagnosis and elimination of problems, knowledge, and intelligent decision-making. By implementing the ‘’Made in China 2025” strategy, China has become the first country in the world in terms of robot implementation and vehicle production. The paper provides an analysis of Industry 4.0 patent applications and the trend of robot implementation in the last ten years with the aim of presenting the implementation of Industry 4.0. Keywords: Robot · Industry 4.0 · Production process · Automation · China

1 Introduction We are witnesses of the changes taking place on the world industrial and digital scene, which the WEF - World Economic Forum (held in Davos in 2016) named the fourth industrial revolution. The Germans were the first to call these changes “Industry 4.0” at the Hanover fair in 2011. Professor Klaus Schwab has issued a book titled “The Fourth Industrial Revolution” published by the World Economic Forum in Geneva in 2016 [1– 3]. It is well-known that the term Industry 4.0 is already widely used, and it is related to different production concepts. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 3–18, 2023. https://doi.org/10.1007/978-3-031-31066-9_1

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Fig. 1. Graphic representation of part of the basic Industry 4.0 technologies

From a technological perspective, Industry 4.0 should be understood as the increasing digitization and automation of production processes, that is, the production environment and the design of the digital value chain from the product to the customer. Some authors call Industry 4.0 a new disruptive technology, as it is inevitable and changes the production processes that are currently implemented in most companies [4, 5, 15]. The concept of Industry 4.0 is defined by many technologies, of which the fundamental are: robotics, automation, Internet of Things (IoT), Big Data, Cloud Computing, 3D printing, smart sensors, Radio Frequency Identification (RFID), Virtual and Augmented Reality (AR), Artificial Intelligence (AI), advanced security systems, Cyber-Physical Systems (CPS), etc., as shown in Fig. 1 [3]. Cyber-Physical Systems (CPS), Internet of Things (IoT), Artificial Intelligence (AI), Additive Manufacturing, Cloud Computing, and other aforementioned technologies are then combined to construct dynamic, real-time optimized and self-organizing value networks between production processes and companies. All listed components are necessary for the implementation of Industry 4.0 [6–9].

2 The Concept of New Disruptive Technology – Industry 4.0 To date, the world has recorded the following revolutions: the first industrial revolution (steam engines in 1784), the second industrial revolution (electric power in 1870), and the third industrial revolution (IT systems and the Internet in 1969). All three revolutions arose as a result of groundbreaking innovations of their time. In 2016, the fourth industrial revolution was announced at the WEF - World Economic Forum. Unlike the previous revolutions in the production processes of the industry, the fourth industrial revolution, or as the Germans call it Industry 4.0, introduces intellectual work and automatic design. There has been an increase in applied innovations in computer hardware, software, operating technologies, and information technologies that are becoming more and more sophisticated and integrated, which leads to the transformation of society into the global economy. The implementation of Industry 4.0 introduces the Internet of Things and Internet of Service into production processes and the production environment, and like any industrial revolution, it is created by increasing through innovations in advanced

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technologies that can be evolutionary and revolutionary, as shown in Fig. 2. [1, 2, 10–12, 14].

Fig. 2. Implementation of innovations from advanced technologies lead us in the direction of evolution and revolution

The analysis of Fig. 2 has provided us with the conclusion that evolutionary innovations cause many gradual advances in technologies and processes, and they can be continuous or dynamic, while the revolutionary innovations are called discontinuous innovations. In other words, the difference between evolutionary and revolutionary innovations is quite noticeable. Evolutionary innovations dominate between industrial revolutions, while revolutionary innovations dominate during industrial revolutions. Revolutionary innovations are present today, some of which are: robotics, the Internet of Things (Internet of Things), the Internet of Service (Internet of Service), a large amount of data (Big Data) and Autonomous Intelligent Systems. They are present in all segments of society: education, ecology, connection, individuality, new health paradigm, urbanization, mobility and globalization. Both evolutionary and revolutionary innovations are present in the fourth industrial revolution. In order to confirm that the aforementioned basic technologies, such as: robotics, cloud computing, automation, intelligent sensors, 3D printers and Radio Frequency Identification – RFID, represent the foundations of Industry 4.0, we will present the trend of reported and implemented innovations (patents) from Industry 4.0 in the following countries: China, USA, Japan, Korea and Germany, as shown in Fig. 3 [1, 13, 15]. By analyzing the trend of reported innovations of the basic technologies of Industry 4.0 (Fig. 3), we conclude that the Chinese data on innovations for Industry 4.0 are very impressive, because China was in the first place in terms of patent applications in 2016, with the growth trend that has the has exponential function since 2010 [16– 20]. In the USA, Japan, Korea and Germany, the trend of reporting innovations was slightly increasing in the same period. The reported trend of Industry 4.0 innovations

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Fig. 3. Diagram of reported innovations in the listed basic technologies of Industry 4.0 in China, USA, Japan, Korea and Germany

allows only limited conclusions about innovation, as there are a huge number of lowquality Industry 4.0 innovations in China. Another reason why this innovation trend in China should be taken with a grain of salt is the dysfunctional government policy that rewards the registration of innovations regardless of their quality. The third reason is that many innovation registrations from Industry in China appear to be of lower quality compared to Germany or the USA, while their acceptance rate is significantly lower. It is very interesting to observe which industrial branches in the world implement the basic technologies of Industry 4.0, as shown in Fig. 4.

Fig. 4. Analysis of the application of innovations from basic technologies of Industry 4.0 in different industrial branches [1]

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Figure 4 shows the trend of the application of innovations from the basic technologies of Industry 4.0 in the following industrial branches: automotive industry, companies, production processes and logistics for the period 2000–2016. We come to the conclusion that the automotive industry is in first place in terms of implementation and reporting of innovations from the mentioned technologies. This growing trend is expected due to the global competition in the automotive industry in the world, as all companies invest a lot in research, development and implementation of the basic technologies of Industry 4.0 in order to remain competitive in the market. Their aim is to develop an autonomous vehicle without drivers, but also to ensure greater safety of traffic participants. The second place in terms of implementation and application of innovations from Industry 4.0 is held by companies, due to the global competition, and a wide spectrum of application of Industry 4.0 in companies from production processes, suppliers, purchases and the environment of the company. The third place is occupied by production processes, because the goal is to achieve flexible automation, which leads companies to smart production processes, thus making them more competitive on the global market in the world. The fourth place is held by logistics, where the trend of applying innovative solutions will be greater in the future. All four mentioned examples indicate that the trend of implementation of innovative solutions from Industry 4.0 was growing on annual basis from 2000 to 2016, and it is expected to increase in the future. We can conclude that the implementation of Industry 4.0 will occur due to global competition, so that production systems will experience a transformation and increase their limits as follows [34]: • Globalization - interconnected supply chains; global market on all continents, thus increasing the complexity of management; • Customization – the customer is increasingly demanding and wants the product to be adapted to his specific requirements; • Flexible automation – installation of industrial and service robots, transition from rigid to flexible automation, and the older workforce (e.g., in Japan, Western Europe, Russia and China), since the average age of workers in production processes is increasing, which causes difficult performance of tasks and therefore lower efficiency; • We have become an information society in a connected world – new ideas spread quickly, accelerating the development of new products, processes and business models, and creating a high demand for products that are difficult to provide; • The population and the middle class are growing in the world - the demographic trends encourage a growing demand for certain products (such as cars in China); • Sustainable development –energy efficiency, reduction of waste and responsible use of natural resources become priority. In order to satisfy and ensure the previously listed facts, it is important to: • every physical process that can be automated must be flexibly automated; • the production process must be digitized, so that the information is available at all times, including the customers; • implement memory sensors and digital applications and devices that can be useful for deep information, monitoring, control and distributive decision-making.

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Fig. 5. Graphic representation of the Physical-Digital-Physical (PDP) loop

We can say that the concept of Industry 4.0 includes and expands digital connectivity in the context of the physical world of digital enterprises, and initiates the physical process of production, performance and distribution in a continuous cycle. This continuous cycle is known as the Physical-Digital-physical loop, as shown in Fig. 5. As indicated in Fig. 5, it is necessary to record information using sensors (more recently smart sensors are used) about the physical world to create a digital record of the physical world. Within the production process, machines communicate with machines (M2M) and share information with each other, which enables the analysis and visualization of the production process itself, i.e., the physical world. By having all the information about the physical world, we are able to generate directions of movement. Using developed algorithms, we can make automated decisions. In other words, by taking actions from the digital world we are making movements in the physical world. If we observe from the technological aspect, Industry 4.0 should be understood as the increasing digitalization and automation of production processes, as well as the design of a digital value chain between products, the work environment, and the customers [19]. The key prerequisites for the implementation of Industry 4.0 are [20, 21]: • Vertical integration and networking of production systems, with the aim of ensuring an intelligent and integrated production environment, all thanks to the integration of ICT information and communication technology and its consistency within the company, from the area of development through the production process, logistics to sales; • Horizontal integration by ensuring the networking of information technologies, processes and data flows among companies, suppliers, business partners in such a way as to promote intensive cooperation based on partnership within the value chain; • Continuous and digital integration of engineering is necessary within the process of the complete value chain, so as to enable a high level of design of end products that are oriented towards the customer. The goal is to enable cost-saving in the company.

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The implementation of Industry 4.0 replaces the traditional structure, based on centralized mechanisms in terms of decision-making and limitations of individual steps where added value is created, with a new structure, i.e. flexible production systems that have the possibility of reconfiguration, which are interactive, collaborative and intelligent, while the decision-making is transferred to lower levels.

3 The Role of Robotic Technology in the Implementation of Industry 4.0 in China 3.1 The Trend of Implementation of Industrial Robots in the World The automation of production processes began in the era of the third industrial revolution in the 1960s, with the introduction of the first industrial robots in production processes. In order to get a complete picture of the role of robotic technology in the implementation of Industry 4.0, an analysis was conducted of the implementation of industrial and service robots in production processes in the world in the last ten years. The annual use of industrial robots in industries is shown in Fig. 3. The data were taken from the International Federation of Robotics (IFR), the United Nations Economic Commission for Europe (UNECE) and the Organization for Economic Cooperation and Development (OECD) [22–31].

Fig. 6. Diagram of robot application in industry in the world on an annual basis in the period 2010–2020 and predictions until 2023 [22–31]

The trend of application of industrial robots in the world in the period 2010–2020 is shown in Fig. 6. By analyzing the trend, we come to the conclusion that the application of industrial robots is continuously increasing on annual basis. About 118.000 industrial robot units were implemented in 2010. In eight years, the implementation increased to about 422.000 robot units in 2018, which represents 3.5 times increase. It is known that the COVID-19 virus pandemic began in 2019 throughout the world, which also affected the use of industrial robots. The application in 2019 was 373.000 robot units, while the application in 2020 was 384.000 robot units. The International Federation of Robotics (IFR) predicts that the application of robots will increase on annual basis in the coming

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years, and in 2023 the application of around 720.000 industrial robot units is expected. The trend of the application of industrial robots in the world in recent years is shown in Fig. 7.

Fig. 7. Diagram of the total application of robots in industry in the world in the period 20102020and predictions until 2023 [22–31]

Based on Fig. 7, we can conclude that the application of robots in industry in the world is continuously increasing every year. In 2010, a total of about 3.015.000 industrial robot units were implemented in the production processes of industry in the world. In just eight years there was an enormous increase so that in 2018, the implementation of robots amounted to 3.240.000 robot units. Predictions of the International Federation of Robotics (IFR) are that the total representation of robots will increase every year and in 2023 will reach about 5.180.000 industrial robot units. It is interesting to note which branches of industry apply the most industrial robots in the world, which is depicted in the diagram for 2020 and shown in Fig. 8. The diagram presented in Fig. 8 shows us the two industries in which the presence of industrial robots prevailed in 2020, namely the electrical/electronics industry, in which there are about 109.000 robot units, i.e., 29% of the total amount of robots implemented in 2020. The second place is held by the automotive industry, in which there are about 80.000 robot units, or 20.8% of robots implemented in 2020. As can be seen, these two industries implement about 50% of the total number of industrial robots in the world. In the third place is the metal industry with about 11%. When we combine the automotive and metal industries, we have a representation of industrial robots of about 31.2%, which is the largest representation of industrial robots in the world. This trend in the representation of industrial robots by industry in the world is expected for two reasons. The first reason is that these two industries, namely automotive/metal and electrical/electronic industries, are located in developed countries, where most production processes are automated. However, they have large competitors and are fighting for their position on the market. The second reason is that these industries are investing in research and development, and tend to implement innovations and patents in production processes. In recent years they have been working rapidly on the implementation of Industry 4.0 in their production processes, with the

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Fig. 8. Diagram of representation of industrial robots in the world in industrial branches in 2020 [22]

ultimate goal to be competitive on the global market. The trend of the representation of industrial robots in fifteen top countries in the world in 2020 is shown in Fig. 9.

Fig. 9. Diagram of the representation of industrial robots in the top five countries in the world in 2020 [22]

Analysis of the diagram shown in Fig. 9 indicates that China is in the first place, and the application in 2020 amounted to about 168.400 industrial robot units. The second place is held by Japan with the application of about 38.700 industrial robot units. The group of countries including the USA, Republic of Korea and Germany implemented around 30.000–22.000 robot units in 2020, depending on the country, as shown in Fig. 6. In the next group of ten countries, the robot implementation is around 7.400- 2.200 industrial robot units in 2020, where Italy is in the lead with about 7.400 robot units, while the UK is in the fifteenth place with about 2.200 units of applied robots. 3.2 The Trend of Implementation of Industrial Robots in Production Processes in China The reports of the International Federation of Robotics (IFR) [22–31] indicate that in the last eight years China has been the first country in the world to implement industrial

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robots in its production processes. The state of implementation of industrial robots in China is obtained by analyzing the implementation of industrial robots in the last ten years. The trend of the implementation of industrial robots in China in the last ten years is shown in Fig. 10.

Fig. 10. Implementation of industrial robots in production processes in China for the period 2010–2020 [22–31]

The analysis of Fig. 10 indicates that from 2010 to 2013, the trend of robot implementation in China was increasing linearly. The sudden increase in the implementation of industrial robots began in 2014, when around 57.000 robot units were implemented. China has become the world’s leading country in the implementation of industrial robots and remained so to this day. 168.000 robot units were implemented in China in 2020. There are several reasons why China is the leader in the implementation of industrial robots in the world: • China is the first in the world in terms of vehicle production, and industrial robots are mostly implemented in the automotive industry. • China has adopted a national strategy (in May 2015) titled ‘’Made in China 2025”, which implements specific goals, and long-term general goals until 2035 and 2049. The goal of the national strategy is to transform China into a leading world production power. • China, like other developed countries, is implementing Industry 4.0, where robotic technology is the basic technology, and the automation of production processes cannot be conducted without the use of industrial robots. • In China, the price of a working hour is continuously increasing, and companies are automating production processes where they implement industrial robots, as shown in Fig. 11. Based on Fig. 11, we are able to compare the price of a robot’s working hour with the price of a worker’s hour in China and the European Union. The price of a working

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Fig. 11. Comparative values of human labor prices in the European Union and China with the price of robot labor [1]

hour of a robot is continuously decreasing, while the price of a working hour of a worker in the European Union is slightly increasing every year. At the same time, the price of a working hour of a worker in China has been skyrocketing since 2015, which justifies the introduction of industrial robots in the production processes in China. China is the first in the world in terms of vehicle production in 2021, as shown in Fig. 12.

Fig. 12. Vehicle production in top fifteen countries in the world in 2021 [32, 33]

As of 2009, China has been the first in the world in terms of vehicle production (10.3 million vehicles in 2009), as shown in Fig. 12, which indicates that China produced about 26 million vehicles in 2021, which is about 16.8 million more than the USA. This trend of vehicle production justifies the trend of increased implementation of industrial robots in China. The number of installed industrial robots can be a misleading measure in the analysis, because it does not reflect the size of a country’s economy. In order to provide a real illustration, the robot density is introduced, which represents the number of operating industrial robots in relation to the number of employees. The robot density coefficient is

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the number of multipurpose industrial robots per 10.000 employees. The robot density coefficient is a measure of the penetration of industrial robots in the industry. There are two countries in the world that stand out: the Republic of Korea with robot density of 932, and Singapore with robot density of 921 per 10.000 robot units, while the world average robot density is 126. China has been increasing the ratio of the robot density per 10.000 employees in the industry on annual basis, as shown in Fig. 13.

Fig. 13. Coefficient of robot density in production processes in China per 10.000 employees in production processes in the period 2010–2020 [22–31]

Until 2017, China’s ratio of robot density per 10.000 employees was below the world average, so in 2010, the robot density in China was 18, while the world average was 50 robots. With the continuous implementation of industrial robots, the coefficient of robot density per 10.000 employees in China has been continuously increasing annually, so that in 2017 it reached the valued of 97, thus exceeding the world average, which was 85. In 2020, the robot density in China was far above the world average, as shown in Fig. 13. The coefficient of the robot density per 10.000 employees in China follows an exponential function, which confirms the fact that industrial robots are implemented in production processes in China. 3.3 Robotic Technology as the Base Technology of Industry 4.0 The implementation of Industry 4.0 and its basic technologies (shown in Fig. 1) enables companies to increase the flexibility of production processes, the quality of products and productivity of the company. In addition, the aforementioned technologies enable product life monitoring until recycling. The basic technologies of Industry 4.0 have achieved around 350 billion dollars on the market in 2018, as shown in Fig. 14. The first place is held by the Internet of Things (IoT) technology, which achieved around 130 billion dollars on the market, while robotics as a technology is in fourth place with about 32 billion dollars’ worth. The market of the mentioned technologies is increasing every year, and according to predictions for 2025 will achieve values shown in Fig. 15. The estimated value that will be achieved by the basic technologies of Industry 4.0 on the world market in 2025 is about 3.2 trillion dollars, as shown in Fig. 15. As can be

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Fig. 14. Values achieved by the basic technologies of Industry 4.0 on the world market in 2018 [35, 36]

Fig. 15. Estimated values that will be achieved by the basic technologies of Industry 4.0 on the world market in 2025 [35, 36]

seen, the Internet of Things (IoT) technology is again in the first place and will achieve about 1.500 billion dollars on the market, while robotics as a technology is in the second place and will achieve a value of around 499 billion dollars. Based on its value on the market, we can see thatrobotic technology is becoming one of the leading technologies of Industry 4.0 and the implementation of Industry 4.0 would not be possible without it.

4 Conclusion The implementation of Industry 4.0 must enable modern production systems to be flexible/agile, integrated, reactive, and profitable at the same time, in order to allow industrial companies to remain globally competitive. Out of a large number of base technologies (over 40 according to some authors) of Industry 4.0, robotics is among the first fundamental technologies. The trend of growth in the application and implementation of innovations and patents from new technologies that are the basis of Industry 4.0 is

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increasing every year, and we have seen that China in the first place in patent applications. However, they are not the first in terms of innovations, because there are a huge number of low-quality innovations from Industry 4.0 in China. The automotive industry ranks first in the number of innovations and patents implemented. The trend of the implementation of industrial robots in the world in the last ten years has been on the rise, and will continue to increase in the coming years due to the implementation of Industry 4.0. Two industries in the world are leaders in the application of industrial robots, namely the electrical/electronic industry and the automotive industry, which in 2020 applied 50% of industrial robots. The first place in terms of application of robots is held by China with about 168.400 robot units. In recent years, China has always been the first in the world in the implementation of robots. There are many reasons for this, some of which are: the price of workers in China has been increasing in recent years, many companies are choosing to automate their production processes, government in China has been implementing a strategy called ‘’Made in China 2025” which aims to make China the most technologically developed country in the world by 2025, and the final reason is that China is the first in the world in the vehicle production where industrial robots are most implemented. The greatest progress in increasing the robot density coefficient per 10.000 employees in industry was made in China, whose robot density coefficient in 2010 was 18, which was below the world average. However, in 2020 the robot density has grown to 246, which is above the world average. Robotic technology is the base technology of Industry 4.0, as indicated by the research that shows that the value realized by robotic technology on the world market in 2025 will amount to 499 billion dollars. Robotic technology has a bright future in the coming years. Acknowledgements. The authors acknowledge the financial support from the Federal Ministry of Education and Science, Federation of Bosnia and Herzegovina, which financed the project under the heading (Number:05-35-2157-1/22, Mostar: 27.10.2022).

References 1. Karabegovi´c, I., Kovaˇcevi´c, A., Banjanovi´c-Mehmedovi´c, L., Daši´c, P.: Integrating Industry 4.0 in Business and Manufacturing. IGI Global, Hershey (2020). https://www.igi-global.com/ book/handbook-research-integrating-industry-business/237834 2. Schwab, K.: The Fourth Industrial Revolution. World Economic Forum, Geneva, Switzerland (2016) 3. Karabegovi´c, I., Karabegovi´c, E., Mahmi´c, M., Husak, E.: The implementation of Industry 4.0 in the function of application of industrial and service robots in production processes. In: International Scientific Conference, Application of Industry 4.0 on Opportunity for a New Step Forward in All Industrial Branches, 14 April 2022, Special Editions, Volume CCII, Department of Technical Sciences, vol. 20, ANU B&H, pp.103–117 (2022). https://doi.org/10.5644/ PI2022.202.24, https://www.anubih.ba/images/news/PDF/20220526_Aplikacija_industrije_ 4.pdf 4. Karabegovi´c, I., Karabegovi´c, E., Mahmi´c, M., Husak, E.: The implementation of Industry 4.0 by using industrial and service robots in the production processes. In: Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing, pp.1–30. IGI Global (2020). https://doi.org/10.4018/978-1-7998-2725-2.ch001

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5. Chryssolouris, G., Mavrikios, D., Papakostas, N., Mourtzis, D., Michalos, G., Georgoulias, K.: Digital manufacturing: history, perspectives, and outlook. J. Eng. Manuf. Proc. Inst. Mech. Eng. Part B 451–462 (2009). https://doi.org/10.1243/09544054JEM1241 6. Karabegovi´c, I., Karabegovi´c, E.: The role of collaborative service robots in the implementation of Industry 4.0. Int. J. Robot. Autom. Technol. 6, 40–46 (2019). https://www.zealpress. com 7. Wang, K.: Intelligent predictive maintenance (IPdM) system—Industry 4.0 scenario. WIT Trans. Eng. Sci. 113, 259–268 (2016). www.witpress.com, https://doi.org/10.2495/IWAMA1 50301 8. Muller, J.M., Buliga, O., Voigt, K.I.: Fortune favors the prepared: how SMEs approach business model innovations in Industry 4.0. Technol. Forecast. Soc. Change 132(C), 2–7 (2018). https://doi.org/10.1016/j.techfore.2017.12.019 9. Karabegovi´c, I.: The role of industrial and service robots in fourth industrial revolution with focus on China. J. Eng. Archit. 5(2), 110–117 (2017). https://doi.org/10.15640/jea.v5n2a9, https://doi.org/10.15640/jea.v5n2a9 10. Karabegovic, E., Karabegovic, I., Hadzalic, E.: Industrial robot application trend in world’s metal industry. Eng. Econ. 23(4), 368–378 (2012). https://doi.org/10.5755/j01.ee.23.4.2567 11. Hermann, M., Pentek, T., Otto, B.: Design principles for Industrie 4.0 scenarios. In: Proceedings of the IEEE 2016, 49th Hawaii International Conference on System Sciences (HICSS), Koloa, HI, USA, pp. 3928–3937 (2016). https://doi.org/10.1109/HICSS.2016.488 12. Thoben, K.D., Wiesner, S., Wuest, T.: Industrie 4.0 and smart manufacturing-a review of research issues and application examples. Int. J. Autom. Technol. 11, 4–16 (2017). https:// doi.org/10.20965/ijat.2017.p0004 13. Karabegovi´c, I.: The role of industrial and service robots in the fourth industrial revolution. ACTE Technica Corviniensis-Bull. Eng. XI(2), 11–16 (2018). http://acta.fih.upt.ro/pdf/20182/ACTA-2018-2-01.pdf 14. Karabegovi´c. I., Karabegovi´c, E., Mahmi´c, M., Husak, E.: The application of service robots for logistics in manufacturing processes. Adv. Prod. Eng. Manag. 10(4), 185–194 (2015). https://www.apem-journal.org/Archives/2015/APEM10-4_185-194.pdf 15. Karabegovi´c, I., Karabegovi´c , E., Mahmi´c, M., Husak, E.: Implementation of Industry 4.0 and industrial robots in production processes. In: Karabegovi´c, I. (ed.) New Technologies, Development and Application, vol. 76, pp. 96–102. Springer, Cham (2020). https://doi.org/ 10.1007/978-3-030-18072-0_1 16. Karabegovi´c, I., Husak, E.: Industry 4.0 based on industrial and service robots with application in China. J. Mobility Veh. 44(4), 59–71 (2018) 17. Karabegovi´c, I.: The role of industrial and service robots in fourth industrial revolution with focus on China. J. Eng. Archit. 5(2), 110–117 (2017) 18. Mi´ciˇc, V.: Industry 4.0 development conditions in the Republic of Serbia. J. facta Universitatis, Econ. Organ. 17(2), 97–112 (2020). https://doi.org/10.22190/FUEO191112008M 19. Oesterreich, T.D., Teuteberg, F.: Understanding the implications of digitisation and automation in the context of Industry 4.0: a triangulation approach and elements of a research agenda for the construction industry. Comput. Ind. 83, 121–139 (2016). https://doi.org/10.1016/j.com pind.2016.09.006 20. Sinay, J., Kotianová, Z.: Automotive industry in the context of Industry 4.0 strategy. Trans. VSB - Tech. Univ. Ostrava, Saf. Eng. Ser. XIII(2), 61–65 (2018). https://doi.org/10.2478/tvs bses-2018-0014 21. Karabegovi´c, I., Husak, E., Predrag, D.: The role of service robots in Industry 4.0 - smart automation of transport. Int. Sci. J. Industry 4.0 4(6), 290–292 (2019). https://stumejournals. com/journals/i4/2019/6/290 22. World Robotics 2020, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2020). https://ifr.org/

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23. World Robotics 2019, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2019). https://ifr.org/ 24. World Robotics 2018, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2018). https://ifr.org/ 25. World Robotics 2017, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2017). https://ifr.org/ 26. World Robotics 2016, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2016). https://ifr.org/ 27. World Robotics 2015, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2015). https://ifr.org/ 28. World Robotics 2014, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2014). https://ifr.org/ 29. World Robotics 2012, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2012). https://ifr.org/ 30. World Robotics 2011, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2011). https://ifr.org/ 31. World Robotics 2010, Industrial Robots, Service Robots, The International Federation of Robotics, Statistical Department, Frankfurt am Main, Germany (2010). https://ifr.org/ 32. Verband Deutscher Verkehrsunternehmen VDA: AutoJahresbericht 2021, Koln, Deutschland (2021) 33. Verband Deutscher Verkehrsunternehmen VDV: Jahresbericht 2020/2021, Koln, Deutschland, (2021) 34. https://www2.deloitte.com/content/dam/insights/us/articles/4340__DSN-Logistics-and-dis tribution/figures/4340_fig1.png. Accessed 7 July 2022 35. UNCTAD: Technology and innovation report 2021, United Nations conference on Trade and Development; based on data from Maddison Project Database, version 2018, Bolt et al. (2018), Perez (2002), Schwab (2013), (2018). https://unctad.org/system/files/official-document/tir 2020overview_en.pdf ´ M., Šesti´c, M., Stupar, S.: Industry 4.0 of Bosnia and Herzegov36. Karabegovi´c, I., Biˇco Car, ina within Industry 4.0. In: International Scientific Conference, Application of Industry 4.0 an Opportunity for a New Step Forward in all Industrial Branches, 14 April 2022, Bosnia and Herzegovina, Sarajevo, pp. 49–68 (2022). https://www.anubih.ba/images/news/PDF/202 20526_Aplikacija_industrije_4.pdf, https://doi.org/10.5644/PI2022.202.20

Kinesthetic Trajectory Learning of a Collaborative Robot UR 10e with APLC S7-1500 Rok Belšak, Janez Gotlih(B) , Lucijano Berus, and Timi Karner Faculty of Mechanical Engineering, Laboratory for Robotisation, University of Maribor, 2000 Maribor, Slovenia {rok.belsak,janez.gotlih}@um.si

Abstract. Collaborative robots are gaining in popularity in various applications. Their practicality to be able to work without additional safety requirements in specific tasks and cooperate with humans has a great potential. Programming a collaborative robot is intended to be easier from programming a classical industrial robot. However, some basic knowledge of programming is required. In order to simplify the teaching process for a collaborative robot a kinesthetic learning is introduced and implemented into the Universal Robot UR10e with the external PLC S7-1500 controller. It has been shown that with the help of kinesthetic learning the trajectory can be easily modified where programming knowledge for robots is not required. Keywords: collaborative robot · UR · PLC · Siemens · Kinesthetic learning

1 Introduction The programming of industrial robots can be divided into several phases. The first stage is choosing the right robot for the intended application. When a suitable robot has been selected, then a suitable grip must be chosen or constructed. This can be changed during the execution of the program or even modified. After placing the robot in the industrial application, it is necessary to program the robot and give it points with the help of which the appropriate trajectory is created. In most cases, these points are fixed points in space. But they can also be variables. After the programming is finished, the entire program must be tested carefully and all possible scenarios that may occur during operation should be predicted, and collisions should be prevented. Possible damage to the equipment might occur if all steps are not performed accordingly. Most industrial robot applications operate in high-volume production, where the learned trajectory does not need to be changed unless product replacement occurs. In this case, it is necessary to change the existing trajectory of the robot, which can only be done by an experienced robot programmer. Recently, collaborative robots are gaining on popularity on the market, robots that under certain conditions do not need a safety curtain and can cooperate with humans. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 19–26, 2023. https://doi.org/10.1007/978-3-031-31066-9_2

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Collaborative robots are still industrial robots and should be treated as such. Collaborative robots appeal primarily to the ISO 15066:2016 standard [1]. The latest collaborative robots already have built-in torque sensors on individual axes. With their help, collaborative robots detect collisions with their surroundings or with humans. These sensors are also used by programmers to manually guide collaborative robots in the sense that they can be grabbed and freely guided to a certain point. Such control of the robots is, of course, rather imprecise but extremely fast. After placing the robot in the desired point, it can be saved with the help of the teaching console. This way of programming is not fundamentally different from programming ordinary industrial robots. Even ordinary robots are first driven to the desired point and only later this point is saved via the teaching console. A lot of tools for end-user programming have become widely available and are integrated into a diversity of platforms. The main goal of end-user programming is that most programs are now written by end-users and not professional software programmers [2].End-user robot programming is promising to democratize robotic assistance and boost economic growth by making the way for collaborative robots entering a variety of industries, including smaller companies with small production capacity and variety of products. The most important advantage of robotic system is its ability in their adaptation for different applications without significant redesign to their hardware or control. This can only be fully utilized if the robots are programmed by experienced programmer or if it is easy for end-user to program. Collaborative robots are nowadays used in different applications. They are used in the research areas for example for model-based reinforcement trajectory learning with the help of the artificial intelligence algorithms [3].Research has been made on how to include collaborative robots in dental assistance with the collaborative robot Franka Emika Panda [4]. Collaborative robot was used in the study for automated COVID-19 oropharyngeal swabbing (testing) where Universal Robots UR5 was used [5]. In industry collaborative robots have proven to be of a great value and help improving the quality of monotonic allow series products with or without of collaboration with a human worker. They can be implemented for different tasks [6]. Main advantage of collaborative robot is that it can under certain circumstances work with human worker. Programming collaborative robots requires background knowledge in robotics. However, latest teach-pendants are becoming more and more user friendly. Still some basic knowledge is needed. Kinesthetic programming of the desired trajectory is presented in the work in order to simplify the teaching process of the collaborative robot.

2 Principle of Kinesthetic Programming of Collaborative Robots The term kinesthetic means being aware of the position of your limbs and how they move. Primarily, the term represents man and his ability to be aware of the position of his limbs and their movement. With the advent of collaborative robots, kinesthetics have also been transferred to the field of robotics. Kinesthetic programming of collaborative robots is primarily based on the integration of torque sensors on the individual axis of the collaborative robot [7–9]. Thus, the robot

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senses an external force (a human pushing the robot axis with his hand) acting on the axis and reduces the torque on the axis so that it can move in the direction of the external force. This is also called the compliance of the robot. Such a principle of a robot manipulation is very primitive and suitable even for people without knowledge of robot programming. However, the collaborative robot itself with its own controller does not enable kinesthetic learning, but only enables kinesthetic guidance and manipulation to the desired point, only after that can this point be saved via the teaching console. For kinesthetic programming of industrial collaborative robots, the robot also needs an external master controller, which in the specific case is a PLC. 2.1 Hardware and Software Used to Demonstrate Kinesthetic Learning A Universal Robots UR10e [10] robot with an OnRobot RG6 [11] collaborative gripper was chosen to demonstrate the effectiveness of kinesthetic learning. The UR10e is the latest robot from Universal Robots with integrated torque sensors on each axis. The robot is connected to the external controller via the PROFINET protocol. Siemens S7-1500 (1516-3PN) [12] was chosen as the external master controller, which is programmed via the TIA Portal program [13]. The robot controller and the Siemens controller communicate via PROFINET serial communication which can be seen in Fig. 1. The components described above have been selected with the intention that the entire demonstration cell is based on components that meet industry standards and which are also most frequently encountered in the industry. 2.2 Kinesthetic Learning The kinesthetic learning application is divided into two parts. First part is intended to learning process and the second part to implementing the learned trajectory into the movement of the collaborative robot. In the learning phase, the robot receives a command via the control system to switch the robot to the compliance mode. With this command, it is possible to move the robot by pushing and pulling the tool or individual axis of the robot to the desired point. By pressing the “Start Rec” button, which is located on the HMI display, the master controller PLC starts reading the current rotations of the individual axes of the industrial robot via PROFINET communication and writing them to a set of variables. Figure 2 shows the HMI display. The number of possible positions that the control system can remember is currently limited to 1000. This can of course be increased, but for a demonstration application this is sufficient. Frequency of saving the robot’s current positions to a set of variables was limited to 0.5 s, which can be seen in Fig. 3. This can also be increased or decreased. When the process of kinesthetic learning is finished, the “Stop Rec” button needs to be pressed. This stop saving the current rotation positions of individual motors to a set of variables. With the command “Start playing” the robot starts executing the learned trajectory. The master controller PLC simultaneously sends data about the rotation of individual motors for three consecutive positions, as shown in Fig. 3.

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Fig. 1. PROFINET connection between devices used in the project.

Fig. 2. HMI screen for kinesthetic learning of a collaborative robot.

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Fig. 3. Flowchart of the program in the PLC for saving a current robot position on the S7-1500 controller and sending it back to the robot.

When the robot starts executing the first position, it sends a request for the new three positions of the motors. The program that is executed on the robot can be seen in Fig. 4. When performing the learned movement, it is necessary to select the transition mode for each point, which means that the robot does not stop at the specified point, but only approaches the point and with a radius of 20 mm already continues to a new point. Also, to perform the trajectory, it is necessary to reduce the acceleration of the movement to 20°/s2 and the speed of the movement to 30°/s. With such settings consistent execution of the learned trajectory is ensured. Otherwise, there may be stops at individual points and jerky acceleration or braking of the robot, which affects the quality of the performed movements, as well as the lifetime of the industrial robot.

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Fig. 4. Program on the UR10e collaborative robot for performing the learned movement.

2.3 Demonstration of Kinesthetic Learning Figure 5 show the kinesthetic learning of an arbitrary trajectory where the robot is grasped and moved synchronously or along individual axes in the compliance mode. It can be seen that the robot is easily handled. After trajectory has been completed the execution of the learned trajectory can be performed as seen in the Fig. 6. Successful tracking of the learned trajectory was shown, where there were no jerky stops and accelerations, but the robot consistently performed the learned movements.

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Fig. 5. Moving UR10e in compliance mode for the trajectory recording.

Fig. 6. Robot UR10e repeating learned trajectory where positions are sent from S7–1500 controller.

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3 Conclusion An implementation of kinesthetic learning of an industrial robot with an industrial controller acting as a master was demonstrated. This type of programming is appropriate especially for reconfigurable robot cells with low productivity where it is necessary to ensure fast re-programmability of the robot trajectory. With kinesthetic learning a collaborative industrial robot can be taught new trajectories quickly and easily. Also, kinesthetic programming does not require any prior knowledge of industrial robot programming so worker-operator can easily re-teach robot trajectory. In the future work the main program on the PLC would be modified in such a way that more programs will be available for kinesthetic learning and that grasping of the object would be included into teaching mode.

References 1. ISO/TS 15066:2016 Robots and robotic devices—Collaborative robots. https://www.iso.org/ standard/62996.html. Accessed 17 Mar 2020 2. Paramasivam, V., Huang, J., Elliott, S., Cakmak, M.: Computer Science Outreach with EndUser Robot-Programming Tools, pp. 447–452 (2017) 3. Polydoros, A.S., Nalpantidis, L.: Survey of model-based reinforcement learning: applications on robotics. J. Intell. Rob. Syst. 86(2), 153–173 (2017). https://doi.org/10.1007/s10846-0170468-y 4. Grischke, J., Johannsmeier, L., Eich, L., Haddadin, S.: Dentronics: review, first concepts and pilot study of a new application domain for collaborative robots in dental assistance. In: 2019 International Conference on Robotics and Automation (ICRA), 20–24 May 2019, pp. 6525–6532 (2019). https://doi.org/10.1109/ICRA.2019.8794139 5. Chen, Y., et al.: A collaborative robot for COVID-19 oropharyngeal swabbing. Robot. Auton. Syst. 148, 103917 (2022). https://doi.org/10.1016/j.robot.2021.103917 6. Djuric, A.M., Urbanic, R.J., Rickli, J.L.: A framework for collaborative robot (CoBot) integration in advanced manufacturing systems. SAE Int. J. Mater. Manuf. 9(2), 457–464 (2016). http://www.jstor.org/stable/26267460 7. Gosar, Ž., Bem, M., Gašpar, T., Kovaˇc, I., Ude, A.: Rekonfigurabilna robotska celica za malo in srednjeserijsko proizvodnjo. In: Posvet Avtomatizacija Strege in Montaže 2017 – ASM 2017 (2017). https://www.academia.edu/35398775/Rekonfigurabilna_robotska_celica_za_ malo_in_srednjeserijsko_proizvodnjo 8. Akgun, B., Cakmak, M., Yoo, J., Thomaz, A.: Trajectories and key frames for kinesthetic teaching: a human-robot interaction perspective. In: HRI 2012 - Proceedings of the 7th Annual ACM/IEEE International Conference on Human-Robot Interaction (2012). https://doi.org/10. 1145/2157689.2157815 9. Cho, S., Jo, S.: Kinesthetic learning of behaviors in a humanoid robot. Accessed 01 Jan 2011 10. U. Robots “UR10e”. https://www.universal-robots.com/products/ur10-robot/. Accessed 6 Dec 2022 11. OnRobot “RG6 gripper”. https://onrobot.com/en/products/rg6-gripper. Accessed 6 Dec 2022 12. Siemens “S7-1516 3PN”. https://mall.industry.siemens.com/mall/en/WW/Catalog/Products/ 10204211. Accessed 6 Dec 2022 13. Siemens “TIA v16”. https://support.industry.siemens.com/cs/document/109772803/simaticstep-7-incl-safety-and-wincc-v16-trial-download?dti=0&lc=en-SI. Accessed 6 Dec 2022

Application of the PFMEA Methodology in a Production Flow with Collaborative Robots Aurel Mihail T, ît, u1,2(B) , Cristian Vasile Doicin3 , Nicolae Ionescu3 , and Vasile Gusan3 1 Lucian Blaga University of Sibiu, 10 Victoriei Street, Sibiu, Romania

[email protected]

2 The Academy of Romanian Scientists, 54 Splaiul Independentei, Bucharest, Romania , 3 Faculty of Industrial Engineering and Robotics, University POLITEHNICA of Bucharest,

Splaiul Independen¸tei Nr. 313, 6th District, Bucharest, Romania

Abstract. The implementation of collaborative robots can often be a challenging aspect. Depending on how collaborative robots have been integrated, various negative effects can occur that can affect the final quality of the product. The authors believe that this aspect could be prevented by identifying potential defects, their effects and causes using the PFMEA methodology. In this scientific work, the PFMEA Methodology will be applied in a serial manufacturing flow with collaborative robots, focusing on the potential defects arising due to the functions operated by the collaborative robots. The individual identification of potential causes will make it possible to treat and prevent them. By punctually treating the causes that generate the appearance of negative effects in a process, their appearance in the long term can be significantly reduced, and thus the quality, efficiency and effectiveness of the manufacturing flow with collaborative robots will be increased. Keywords: Collaborative robot · PFMEA · Cause-effect · Quality assurance · Manufacturing

1 Introduction The automotive industry is constantly changing. In recent years, it has had to face various challenges at the global level represented by the pandemic, and then the chip and semiconductor crisis. To resist these crises, the flexibility of organizations represented one of the keys to success together with the use of certain methodologies that prevent erroneous investments by discovering the potential causes of failures. Also, collaborative robots have become an important integrated part of the automotive serial production processes. They ensure the quality of the final product through the repeatability and safety through which they handle the products on the manufacturing flow. Collaborative robots bring a significant impact on productivity, they keep a constant speed and a constant pace of production. FMEA represents an methodology used in risk management with the aim to improve quality [1]. Being an integrated part of the production processes, collaborative robots must be also subjected to analysis through the PFMEA methodology. This methodology needs © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 27–36, 2023. https://doi.org/10.1007/978-3-031-31066-9_3

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to be applied before the installation of the production flow with collaborative robots or, if collaborative robots will be implemented on an existing production flow, before their integration. The PFMEA methodology has the role of identifying potential deficiencies and their effects that may appear after the integration of collaborative robots on a manufacturing flow. Taking into account the mentioned aspects, the authors proposed through the scientific work apply the methodology in a practical way to a production flow with collaborative robots.

2 Application of the PFMEA Methodology in a Flow with Collaborative Robots in the Automotive Field FMEA was used for the first time in 1940, having military use [2]. FMEA is an acronym that can be translated into Failure Mode and Effect Analysis [3]. Collaborative robots have become an integrated part of production processes. They can be identified most of the time by carrying out picking and placing operations on the production flow or by manipulating various devices to process or process the products. Due to the mentioned aspects, in this chapter the authors propose: o to identify the place of a collaborative robot in the manufacturing flow of a product through a flow diagram; o to identify the potential deficiencies and effects that may appear due to the existence of collaborative robots on a series manufacturing flow applying the PFMEA methodology; To identify the place of the collaborative robots on a production line, we created the flow diagram in Fig. 1. In the series manufacturing flow shown, collaborative robots take over the role of the operator to transfer products between certain stations. If in the past these transfer operations were passed to the responsibility of the operator, now the responsibility of product transfer is passed to the collaborative robots. The production flow represented by the diagram is the same as the manufacturing flow on which the collaborative robot operates. The flowchart contains four shapes that were used depending on the role. The legend of the flowchart can be found at the bottom of Fig. 1. FMEA is concluding into corrective actions with the aim of eliminating or reducing the failure rate [4]. RPN is an acronym for Risk Priority Number. Itcanbecalculatedusingthe formula, [5]: RPN = S ∗ O ∗ D

(1)

The manufacturing flow of the presented diagram can be described as follows: o The manufacturing flow starts with the Depanelling process. This is the process of separating electronic boards. They can be arranged, depending on the project, on a

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panel with several electronic boards. Into this process will come the panels with PCBs that they process, making separate PCBs. Depending on the result of the process, if the product is declared suspect, it can be transferred by the operator to the analysis station, from where it will be reintroduced into the manufacturing flow or declared rejected, and if the product has been processed correctly, it will be transferred by to the operator through the operator to the connector pressing station;

Fig. 1. Flow chart of collaborative robot manufacturing

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o The connector pressing process makes the connection of the PCB with the connector through a cold pressing. After completing the process, the product can be transferred to the testing station in the circuit or, if it is declared a suspect product, it will be transferred to the analysis station where it will be declared rejected or reintroduced into the flow. The transfer operations are carried out by the operator; o In-circuit testing is a testing process whose role is to detect the electrical functionality of each electronic component on the product. At the time of testing, the product is in the form of a populated electronic board or, according to the input, PCB with inserted connector. After the test, the product is to be transferred to the software installation station or, if it is suspect, to be transferred to the analysis station. Following the analysis, the technician will decide if the product can be put back into the flow or if it must be declared rejected. These transfer operations between stations are performed by the production operator; o Software installation, also known as Flash download, is a process in which the product software is loaded into it. This is a testing process. At the time it is processed, the product is in the form of a populated electronic board or PCB with an inserted connector according to the input mentioned in the graphic modelling. Following the completion of the test, the product can be transferred to the assembly station or, if it is declared suspect, it will be transferred to the analysis station where it will be declared rejected or reintroduced into the production flow. The operator is responsible for the transfer of the products; o The assembly process is a process in which the housing is assembled with the populated electronic board. The populated electronic board will enter the process together with the inserted connector accompanied by a casing, and at the exit, the two will turn into an assembled product. In this area, it can be seen that both the PCB with the connector and the housing is transferred and loaded into the station by the operator. Depending on the result of the assembly process, the product is to be transferred to the final testing station by collaborative robot number 1, or if the product is suspect, it is transferred by the operator to the analysis station. Depending on the result of the analysis, the technician will reintroduce the product into the production flow or declare the PCB together with the rejected case; o Final testing is a verification test, in which the functionality of the product is tested. Certain commands are simulated and certain of their functionalities are verified. Transfer operations to and from this station are performed by the collaborative robot. If the product is declared suspect, it will be transferred to the suspect parts conveyor or relocated to the intermediate transfer table; o The intermediate transfer table has only the role of storing the products with a conforming result from the final testing stations. The nests of this table will be loaded by the transfer of products by collaborative robot number 1 and will be unloaded by collaborative robot number 2; o The connector verification test is performed by contacting the product. If the existing pins in the mask are enabled, the result will be a compliant one. Depending on the result, collaborative robot number 2 will transfer the products to the line. If the result is a compliant product, it will transfer the tested products to the product conveyor to be packed. If the result is a suspect product, it will transfer the tested products to the suspect parts conveyor;

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o The packaging process, where the final product is checked to have no visible defects, the label to be legible, to be assembled according to many other characteristics. The product is still packed. The number of packed products depends on the packaging used and the customer’s request. The packaging can only be temporary so that when it arrives at the warehouse it will be repackaged, or it can be permanent. The products arrive at this station via the conveyor belt for products to be packed; o The analysis station is the space where the process of analyzing suspicious products from the process takes place. The analysis is done only if the client expresses his agreement in this direction. Any part coming from the process or test as suspicious is thoroughly analyzed by the technician. If the product is compliant in terms of functionality and customer requirements, it can be fed back into the flow at the required station. If the parts or products do not meet the customer’s requirements, they are declared as scrap. Analysis stations can be processed or tested, the analysis is done by a process or test technician. The FMEA moderator is the one who leads the FMEA meetings and invites the relevant people. – [6] It can be seen that in this flow chart, the collaborative robots are identified as having the same function and responsibility as the operator. They, like the operator, transfer the products from one station to another depending on the result. Through this analysis, additional possibilities for improving the manufacturing flow are identified. In this case, the authors recommend that the responsibility of the transfer of products on the manufacturing flow be carried out entirely by collaborative robots. However, as in any other manufacturing flow, certain deficiencies in the process may occur. The authors considered it necessary to focus strictly on the deficiencies appearing in the manufacturing areas containing collaborative robots, which may appear due to their implementation or due to the collaboration between humans and collaborative robots. By detecting in time the deficiencies that may appear, clear measures can be taken to prevent problems and reduce any potential risk through which these deficiencies could affect the product and, after delivery, the customer. The PFMEA methodology was applied as can be seen in Table 1. Using the flowchart in Fig. 1, the authors identified the functions that the collaborative robots perform on the analyzed manufacturing flow. These are: • Transfer of the product to the final testing station by collaborative robot number 1; • Product transfer by collaborative robot number 1 to the station with intermediate transfer nests from the final testing station; • Transfer of the suspect product by collaborative robot number 1 to the suspect product conveyor for analysis; • Product transfer by collaborative robot number 2 to the connector check station from the station with intermediate transfer nests; • Transfer of the product by collaborative robot number 2 to the conveyor with products for packaging from the connector check station; • Transfer of suspect product by collaborative robot #2 to suspect product conveyor for analysis.

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Because the functions are to transfer the product, differing only by the place from which the product departs or arrives and respectively the collaborative robot that carries

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out the product transport, the same deficiencies were identified for each function. Also, for each deficiency a potential effect was identified, as follows: o Deficiency: Contamination of the product with oil. This deficiency can lead to a potential product contamination effect; o Deficiency: Electrical components damage. Due to this deficiency, the potential effect on the product could be one of electrical or functional failure; o Deficiency: Mechanical stress of the product. This deficiency could also lead to the potential effect of electrical or functional failure of the product; o Deficiency: Scratched product. Two potential effects were identified for this deficiency. The first potential effect could be the unsightly appearance, and the second potential effect could be the electrical or functional failure of the product. The grades were distributed according to the severity or severity of the potential effects. For each potential effect, the authors assigned a score according to the severity of the effect. Thus, the following can be distinguished: • Note 7 for the potential effect of contamination of the product. The authors gave this grade because the contamination of the product can lead to malfunctions during its operation, but does not put the customer’s life at risk; • Note 8 for the potential effect of electrical or functional failure. The authors noted this because, even if the product is non-functional, it will not put the customer’s life in danger; • Note 2 for the potential effect of unsightly appearance. The authors gave this grade because the functionality of the product is not affected, the defect may go unnoticed by the customer. Next, the authors investigated what could be the potential cause of each effect. The following aspects were concluded: o In the case of the potential effect regarding the contamination of the product, the authors established the fact that the collaborative robot was mechanically damaged, the lubricating oil of the gears coming from the joints of the collaborative robot; o For the potential effect of electrical or functional failures of the product, the authors determined several potential causes: damage to the gripper of the product handled by the collaborative robot, the product was dropped on foot by the collaborative robot during transport, or the product from the gripper of the collaborative robot was hit by the product in the machine device; o In the case of the potential effect of unsightly appearance, the authors determined that this aspect could be because the product in the collaborative robot’s gripper was hit by the product in the machine device. It continued by noting the potential causes according to the occurrence and the possibility of their detection in case of occurrence. The authors performed calculations to establish the risk priority number for each potential cause.

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It is recommended that in case of a result of RPN above 100 value corrective measures must be taken [7]. However, after calculating the risk priority number, the authors focused on the top three potential causes with the highest RPN. These are: 1. Potential cause: product dropped on the ground by the collaborative robot during transport, with an RPN value of 96; 2. Potential cause: device of the collaborative robot hit by a product in the device, with an RPN value of 120; 3. Potential cause: The robot gripper is damaged, with an RPN value of 64. PFMEA recommends ways of improvement regarding the design of the equipment and of the production line [8]. It was necessary to establish clear and punctual measures for the two actions so that the occurrence is reduced or the detectability is improved. The authors established the following actions to be implemented: • For the potential cause of the product dropped on foot by the collaborative robot during transport, it is necessary to implement a vacuum generator that will return a signal to the robot when a certain vacuum value is reached. Adding this signal to the collaborative robot program will cause the collaborative robot to stop when the product is not correctly clamped in the device. The technician will have to intervene and check the state of the clamping device and the clamping coordinate of the collaborative robot. Thus, the occurrence will be particularly low, because the collaborative robot will always appropriately grip the product; • For the potential cause of the gripper of the collaborative robot being hit by a product located in the device of the equipment, it is necessary to implement the solution for querying signals in parallel in the “Thread” category. This consists of the use of variables correlated with the signals of the existing presence sensors, whose values will be modified by the collaborative robot in real-time. This action will lead to a low occurrence because, in case the human changes; the position of a product on the manufacturing flow, the collaborative robot will detect this aspect in real-time and will not place one product on top of the other; • For the potential cause, the robot gripper is damaged, the authors found that it is necessary to check the gripper at the beginning of each shift, batch change or product change. This operation will be included in the operator and technician verification operations. Thus, the detectability of the damage to the gripper will be improved. There are many organizations which are focusing there financial and human resources, including experts to complete the PFMEA analysis. [9] PFMEA analysis presents all the risks existing in a process from the automotive industry. [10] Following the application of these measures on a point-by-point basis for each potential cause mentioned, new grades were provided for occurrence and detectability. The scores given to the original severity of the potential effects remained unchanged because the severity of the effects cannot be changed. Based on the new grades, the RPN index was recalculated, according to Table 2.

Application of the PFMEA Methodology in a Production Flow Table 2. PFMEA study on collaborative robots. Part 2

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3 Conclusion Using the PFMEA, the potential causes that facilitate the emergence of the potential effects were treated. By punctually treating the causes that generate the appearance of negative effects in a process, we will significantly reduce their appearance in the long term, and thus we will increase the efficiency and effectiveness of a manufacturing flow with collaborative robots. Finally, to identify the functions of collaborative robots on a manufacturing flow, the authors designed a flow diagram. They used the identified functions to apply the PFMEA methodology. The authors applied the PFMEA methodology to identify potential deficiencies and their effects that may appear due to the existence of collaborative robots on a series manufacturing flow. Following the application of the PFMEA methodology, a specific action plan was established for each potential cause. The authors believe that it is important that actions focus on remedying the cause and not the effect. By punctually treating the causes that generate the appearance of negative effects in a process, their occurrences will be significantly reduced in the long term, and thus the quality, efficiency and effectiveness of a manufacturing flow with collaborative robots will increase.

References 1. Belu, N., Khassawneh, N., Al Ali, A.R.: Implementation of failure mode, effects and criticality analysis in the production of automotive parts. Calitatea 14(135), 67 (2013) 2. Giannetti, C., Ransing, M.R., Ransing, R.S., Bould, D.C., Gethin, D.T., Sienz, J.: Product specific process knowledge discovery using co-linearity index and penalty functions to support process FMEA in the steel industry. In: Proceedings of the 44th International Conference Computer Industrial Engineering, Istanbul, Turkey, pp. 14–16 (2014) 3. Komatina, N., Tadi´c, D., Aleksi´c, A., Banduka, N.: The integrated PFMEA approach with interval type-2 fuzzy sets and FBWM: a case study in the automotive industry. Proc. Inst. Mech. Eng. Part D: J. Autom. Eng. 236, 1201–1212 (2022) 4. Matos, C.P.D., Matias, J.C.O., Azevedo, S.G.: Manufacturing proceses control in automotive industry (2014). AIAG: Advanced Product Quality Planning (APQP) and Control Plan, 2nd edn., Chrysler, Ford, General Motors, USA (2008a). AIAG: FMEA: Reference Manual, 4th edn., USA (2008b). Aldridge, J.R., Taylor, J., Dale, B.G.: The application of failure mode and effects analysis of an auto. Case Stud. J. ISSN (2305-509X), vol. 3 (1990) 5. Stamatis, D.H.: Failure Mode and Effect Analysis: FMEA from Theory to Execution. Quality Press, Seattle (2003) 6. Ekmekçio˘glu, M., Can Kutlu, A.: A fuzzy hybrid approach for fuzzy process FMEA: An application to a spindle manufacturing process. Int. J. Comput. Intell. Syst. 5, 611–626 (2012) 7. Banduka, N., Veza, I., Bili´c, B.: An integrated lean approach to process failure mode and effect analysis (PFMEA): a case study from automotive industry. Adv. Prod. Eng. Manag. 11, 355–365 (2016) 8. Braglia, M., Castellano, D., Gabbrielli, R., Marrazzini, L.: A revised PFMEA approach for reliable design of assembly activities. Designs 5(1), 12 (2021) 9. Rehman, Z., Kifor, C.V.: An ontology to support semantic management of FMEA knowledge. Int. J. Comput. Commun. Control 11(4), 507–521 (2016) 10. Banduka, N., Aleksi´c, A., Komatina, N., Aljinovi´c, A., Tadi´c, D.: The prioritization of failures within the automotive industry: the two-step failure mode and effect analysis integrated approach. Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. 234(12), 1559–1570 (2020)

Analysis and Development of a Robotic Arm for Space Applications Carmela Franco1 , Rosario La Regina1 , and Carmine Maria Pappalardo2(B) 1 MEID4 Academic Spin-Off of the University of Salerno, Via Giovanni Paolo II 132,

84084 Fisciano, Italy [email protected] 2 Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy [email protected]

Abstract. The present paper focuses on the design of a robotic arm for space applications, virtually prototyped using software such as SOLIDWORKS, MATLAB, and SIMSCAPE. More than sixty years have passed since the first space launch in orbit around the Earth. Since then, numerous missions have been conducted in the meantime, making space launches way more accessible. Nonetheless, if launching satellites into space is now something so approachable, not much has been done to deliver it back. As a result, space pollution has become a problem. Therefore, it is essential to try to reduce the risk of collision and loss of satellites. Moreover, it is fundamental to equip the new satellite with a self-destruct system to prevent the occurrence of the so-called “Kessler Syndrome” scenario. This paper illustrates and analyses the design phases, the choice of the kinematics, the static verification, and the modal analysis in different setups of a robotic arm attached to a minisatellite. For this purpose, the propulsion system was carefully chosen, whereas control systems for the arm movement were developed and a feedback controller was chosen. The arm under study was designed to fit a minisatellite, be resistant during orbit, and be able to stabilize the attitude of the robot in orbit. The paper presents the analysis of the results of the virtual prototyping process developed in this work by using a multibody approach. Keywords: virtual prototyping · computer simulations · robotic arm · serial kinematics · multibody dynamics · satellite attitude control

1 Introduction In the last decades, there has been an exponential increase in space missions thanks to a sharp decrease in costs, which made space an accessible place for everyone. It follows that there have been massive breakthroughs in terms of scientific research, but everything has a price. Within an average of 60 years more than 30.000 pieces of space debris can be found in orbit around the earth, identified, and regularly monitored to avoid collisions [1]. Moreover, the exponential increment of this debris has a strong impact on future and present space missions. Costs vary depending on the type of mission and orbital patterns, a classic example is fuel consumption to make a maneuver to avoid direct © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 37–44, 2023. https://doi.org/10.1007/978-3-031-31066-9_4

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collision with debris [2]. In view of this, the first evasive maneuver was made in 1991 during the STS-48 mission. The International Space Station (ISS) too had no escape, being attacked several times by space debris and having to change its course [3]. This suggests that if this debris were to increase, the scenario described as Kessler syndrome could be met, a chain collision that would compromise space exploration and the use of artificial satellites in the next generations [4]. Hence, this problem has had such a strong impact that an organization to deal with space debris, the IADC, Inter-Agency Space Debris Committee, was set up by the UNU. Over time, several solutions were analyzed for the problem presented. ESA, in the specific, funded several missions, scheduled in the coming years. ClearSpace-1 is the first mission for the active removal of debris, consisting of a satellite equipped with 4 robotic arms [5]. In addition to active removal, several studies have been carried out. For instance, another solution could be to reuse the debris itself as a propellant, using a special engine [6]. The purpose of this article is to find a low-cost solution to this type of problem, an affordable, zero-impact space robot. In particular, a configuration has been designed that can control the attitude of the satellite, avoiding its loss, and ensuring self-destruction at the end of work. A robot was designed that consists of two units: a satellite, that can be adapted to different needs, and a robotic arm equipped with a probe. Starting from Cubesat, a mini satellite developed by Twiggs (Stanford University’s Space Systems Development Laboratory) and Puig-Suri (California Polytechnic State University) in 1999 [7]. The Cubesat has the characteristic of being able to be assembled using COTS (Commercial Off-the-Shelf components), thus keeping costs low. Two units, 2U, will be used: one for satellite components and the other for the arm. The size of a unit is very small, just 10 × 10 × 10 (cm) with a maximum weight of 1 (kg), so among the main challenges for the design there have been the spatial and mass limits [8–10]. The arm describes a large working area. It allows the adjustment in the space of the engine so that the attitude in case of loss can be adjusted. The arm, including the material, motors, sensors, probes, and work area, were specially chosen to enter its dedicated CubeSat area, to keep costs low and affordable.

2 Structural and Mechanical Design One of the main challenges faced during the design of the robotic arm was to guarantee a system that must be resistant, simple to assemble, and easy to use. During the design process, the robotic arm was planned to occupy a single unit of the CubeSat, placed at the top in order to reduce the effects of vibration during launch and use. The choice of kinematics was made based on the working area that needed to be covered. Over the years, several robotic arms have been sent into space. One of the most interesting is the robotic arm assembled on the ISS, the anthropomorphic arm ERA, equipped with 7° of freedom, whose wrists have two revolute kinematic pairs [11]. By working area it is intended the sum of the spaces reachable from the robot end-effector. For instance, it was necessary that the probe could be oriented freely in the different space whereabouts. In this specific case, a serial robot arm was designed, which can be described as a series of connections between the joints, which are driven by an engine. The degrees of freedom of the mechanism are given by Grubler’s formula, which takes into account the number of connected elements and the joints present in the mechanism. In the present case, a

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structure with three components was considered: a waist with translational movement, a shoulder with rotoidal movement, and an elbow with rotoidal motion was conceived. The elbow was assembled with a probe which is allowed to rotate around two axes, through the structure of the wrist. The choice of five degrees of freedom allows one to reach a point in space with multiple configurations of the robotic arm. It should be considered that each movement of the arm results in a variation in the initial kinetic energy of the system [12]. To control the movement of the arm, a small and low-power pulsed plasma thruster was used, to allow controlled movements. A robotic system is the result of the interconnection of four sub-assemblies: mechanical system, actuation system, measurement system, and control system. Concerning the mechanical system, the engine system was carefully chosen to meet the required power and dimensional characteristics. Hence, linear and rotary micromotors were used. The characteristic of a linear actuator is that it can work along a straight line, meanwhile, the rotary one puts an angular movement of a certain number of degrees [13–15]. The aim of this paper is to design a low-cost robotic arm, readily accessible, and for this reason, parts that are easily available on the market, despite the small size have been chosen. A microlinear servo actuator with a force control lineup, with an integrated drive circuit, position sensor, reducer, and a stroke of 40 (mm) was inserted in the design phase so that it can be within the dimensions of the CubeSat and the power limits [16–18]. For the rotoidal micromotor, given the limited power, a DC motor with a speed sensor, with an integrated drive circuit, was chosen.

3 Robot Arm Dynamic Modeling In the field of robotics, robot dynamics is the study of the motion of robots and the forces that affect their motion. It involves understanding how the robot structure and components, such as its joints and actuators, influence its movements, as well as how external forces, such as gravity and friction, affect the robot motion [19–21]. Robot dynamics is a key area of study in robotics, as it is essential for designing and controlling robots that are stable, efficient, and capable of performing a wide range of tasks. It requires a combination of knowledge from engineering, physics, and mathematics, including topics such as kinematics, kinetics, and control theory. In order to understand and analyze the dynamics of a robot, it is often necessary to develop mathematical models that describe the robot motion and the forces acting on it. These models can be based on physical principles, such as Newton’s laws of motion, or on empirical data obtained through experiments or simulations. Once these models are developed, they can be used to design and test control algorithms that enable the robot to move and interact with its environment in the desired manner [22–24]. The equation of motion for a robotic mechanism is a mathematical expression that describes the relationship between the forces acting on the robot and its motion. For a robotic mechanism with Nl links and Nj joints, the equation of motion can be written as: ˙ q˙ + τg (q) + J(q)T fe = τc H(q)q¨ + C(q, q)

(1)

where H is the joint-space inertia matrix, also known as the manipulator inertia matrix or the manipulator mass matrix. This is a matrix that describes the mass and inertia

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properties of a robot mechanism in joint space. It is used to model the dynamic behavior of the robot, including the forces and torques required to accelerate and decelerate its joints and links. The joint-space inertia matrix is defined as H = JT MJ, where J is the Jacobian matrix of the robotic system, which describes the relationship between the joint velocities and end-effector velocities, and M is the system mass matrix, which describes the mass and inertia properties of the robot in Cartesian space [25]. The generalized force term Cq˙ includes the Coriolis and centrifugal forces. The term τg is the vector of gravitational forces. The effect of the external force is given by the term JT fe , while the generalized control forces are embedded in the term denoted with τc .

4 Results and Discussion After choosing the different components, the virtual prototype of the robot was modeled using SOLIDWORKS, leading to the model shown in Fig. 1. This is a solid modeling computer-aided design (CAD) and computer-aided engineering (CAE) software.

Fig.1. Robotic arm and CubeSat CAD model.

Fig. 2. Finite element static analysis.

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The structure was optimized by a series of tests. In particular, a static analysis and a modal analysis were carried out to verify the resistance of the main body. For instance, to ensure good resistance, the system was tested both in the launch configuration (when the arm is folded on itself inside the Cubesat) and in the working configuration (maximum extension of the arm) [26–28], as shown in Fig. 2. Once the arm and all its components were statically tested, dynamic modeling was possible. One of the features of SOLIDWORKS is that it can export a CAD model in different formats, including one compatible with SIMSCAPE. This is software for the modeling, simulation, and analysis of dynamic systems, integrated into MATLAB.

Fig. 3. MATLAB/SIMSCAPE model: robotic arm.

Fig. 4. MATLAB/SIMSCAPE model: robotic wrist.

By importing the robotic arm into MATLAB, as shown in Figs. 3 and 4, all the features previously chosen, such as mass, inertia, geometric characteristics, joints, and more remain unchanged, but it allows to greatly simplifies the control [29–31]. The most commonly used control technique is the Proportional-integral-derivative controller, also known as PID. A PID controller continuously calculates error value, as the difference between the desired set point and the measured value of the process variable, and therefore applies a correction on the motion [32–35]. In a PID controller, the output variable is generated based on the contribution of three terms. The first is proportional to the reference error, the second is proportional to the integral of the error, and the third will be proportional to the integral of the error [28, 36, 37]. To determine the law of motion, the method of direct kinematics was used through the MATLAB function that allows

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for the assigning of each joint to the desired position, thus obtaining the trajectory of the end-effector [38, 39].

5 Conclusions and Future Work This paper aims to present an innovative and low-cost design for a space robot. Robot dynamics is a vast and rapidly-evolving field, with applications in areas such as manufacturing, healthcare, construction, and search and rescue. As robots continue to become more advanced and capable, a deeper understanding of robot dynamics will be essential for realizing their full potential in a wide range of tasks and environments. As future improvements of the present work, one might consider implementing a second robotic arm, to make the structure more stable and symmetrical. The dynamic and control performances can be analyzed thoroughly using MATLAB and SIMSCAPE. There are several ways in which robotic arms for space debris removal could be developed in the future. One possibility is the development of more advanced and versatile robotic arms that can perform a wider range of tasks and operate in a greater range of environments. This could include the development of robotic arms with improved dexterity, strength, and endurance, as well as the ability to operate in extreme temperatures and other challenging conditions. Overall, the use of space robotic arms for garbage removal is an exciting development that has the potential to greatly improve space operations. As technology continues to advance, it is likely that we will see even more innovative and advanced space robotic arms being developed and deployed in the future.

References 1. ESA’S Annual Space Environment Report, ESA Space Debris Office, 22 April 2022, GENDB-LOG-00288-OPS-SD (2022) 2. Trisolini, M., Lewis, H.G., Colombo, C.: Predicting the vulnerability of spacecraft components: modelling debris impact effects through vulnerable-zones. Adv. Space Res. 65(11), 1 2692–2710 (2020) 3. Schaub, H., Jasper, L.E.Z., Anderson, P.V., McKnight, D.S.: Cost and risk assessment for spacecraft operation decisions caused by the space debris environment. Acta Astronaut. 113, 66–79 (2015) 4. NASA’s Efforts to Mitigate the Risks Posed by Orbital Debris, Office of Inspector General, 27 January 2021, IG-21-011 (A-20-002-00) (2021) 5. Kessler, D.J., Cour-Palais, B.G.: Collision frequency of artificial satellites - the creation of a debris belt. J. Geophys. Res. 83, 2637–2646 (1978) 6. New home for Earth’s protectors, ESA, 12/04/2022 (2022) 7. Palmer, C.: Russian anti-satellite test spotlights space debris danger. Engineering 12, 3–5 (2022) 8. Lan, L., Li, J., Baoyin, H.: Debris engine: a potential thruster for space debris removal (2015) 9. Daši´c, P., Daši´c, J., Antanaskovi´c, D., Pavi´cevi´c, N.: Statistical analysis and modeling of global innovation index (GII) of Serbia. In: Karabegovi´c, I. (ed.) New Technologies, Development and Application III. LNNS, vol. 128, pp. 515–521. Springer, Cham (2020). https://doi.org/ 10.1007/978-3-030-46817-0_59 10. Daši´c, P.: Scientific and Technological Trends: Selected Scientific-Professional Papers. SaTCIP Publesher Ltd., Vrnjaˇcka Banja (2020). (in Serbian)

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11. Boumans, R., Heemskerk, C.: The European robotic arm for the international space station. Robot. Auton. Syst. 23(1–2), 17–27 (1998) 12. Guida, R., De Simone, M.C., Daši´c, P., Guida, D.: Modeling techniques for kinematic analysis of a six-axis robotic arm. IOP Conf. Ser.: Mater. Sci. Eng. 568(1), 012115 (2019) 13. Oleksiuk, W., Nitu, C.: Miniature linear electromagnetic drives. In: Proceedings of International Conference on Mechatronics and Robotics, Brno, Czech Republic, pp. 29–34 (1999) 14. De Simone, M.C., Veneziano, S., Guida, D.: Design of a non-back-drivable screw jack mechanism for the hitch lifting arms of electric-powered tractors. Actuators 11(12), 358 (2022) 15. De Simone, M.C., Ventura, G., Lorusso, A., Guida, D.: Attitude controller design for microsatellites. In: Karabegovi´c, I. (eds.) New Technologies, Development and Application IV, vol. 233, pp. 21–31. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_2 16. Doua, R.: Inverse kinematics for a 7-DOF humanoid robotic arm with joint limit and end pose coupling. Mech. Mach. Theory 169, 104637 (2022) 17. De Simone, M.C., Rivera, Z.B., Guida, D.: Obstacle avoidance system for unmanned ground vehicles by using ultrasonic sensors. Machines 6(2), 18 (2018) 18. Rivera, Z.B., De Simone, M.C., Guida, D.: Unmanned ground vehicle modelling in Gazebo/ROS-based environments. Machines 7(2), 42 (2019) 19. De Simone, M.C., Celenta, G., Rivera, Z.B., Guida, D.: Mechanism design for a low-cost automatic breathing applications for developing countries. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V, vol. 472, pp. 345– 352. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_40 20. De Simone, M.C., Guida, D.: Experimental investigation on structural vibrations by a new shaking table. In: Carcaterra, A., Paolone, A., Graziani, G. (eds.) Proceedings of XXIV AIMETA Conference 2019, pp. 819–831. Springer, Cham (2020). https://doi.org/10.1007/ 978-3-030-41057-5_66 21. Colucci, F., De Simone, M.C., Guida, D.: TLD design and development for vibration mitigation in structures. In: Karabegovi´c, I. (eds.) New Technologies, Development and Application II, vol. 76, pp. 59–72. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-18072-0_7 22. Pappalardo, C.M., Regina, R.L., Guida, D.: Multibody modeling and nonlinear control of a pantograph scissor lift mechanism. J. Appl. Comput. Mech. 9(1), 129–167 (2023) 23. Pappalardo, C.M., Vece, A., Galdi, D., Guida, D.: Developing a reciprocating mechanism for the emergency implementation of a mechanical pulmonary ventilator using an integrated CAD-MBD procedure. FME Trans. 50(2), 238–247 (2022) 24. Ardila-Parra, S.A., Pappalardo, C.M., Estrada, O.A.G., Guida, D.: Finite element based redesign and optimization of aircraft structural components using composite materials. IAENG Int. J. Appl. Math. 50(4), 1–18 (2020) 25. De Simone, M.C., Guida, D.: Modal coupling in presence of dry friction. Machines 6(1), 8 (2018) 26. Chourasia, K., Joladarashi, S.: Modelling, static and dynamic analysis of offset bearing using ANSYS. Mater. Today: Proc. 66(4), 2124–2132 (2022) 27. De Simone, M.C., Laiola, V., Rivera, Z.B., Guida, D.: Dynamic analysis of a hybrid heavyvehicle. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application, vol. 472, pp. 236–243. Springer, Cham (2022). https://doi.org/10. 1007/978-3-031-05230-9_27 28. Formato, A., Ianniello, D., Romano, R., Pellegrino, A., Villecco, F.: Design and development of a new press for grape marc. Machines 7(3), 51 (2019) 29. Li, T., Kou, Z., Wu, J., Yahya, W., Villecco, F.: Multipoint optimal minimum entropy deconvolution adjusted for automatic fault diagnosis of hoist bearing. Shock Vibr. 6614633 (2021)

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Robot-Assisted 3D Laser Surface Hardening of Medium-Carbon Steel: Surface Roughness Parameters and Hardness Dmytro Lesyk1,3,4(B) , Matej Hruska2 , Bohdan Mordyuk3 , Pawel Kochmanski4 , and Bartosz Powalka4 1 Laser Systems and Advanced Technologies Department, “Igor Sikorsky Kyiv Polytechnic

Institute”, National Technical University of Ukraine, Kyiv 03056, Ukraine [email protected] 2 New Technologies Research Centre, University of West Bohemia, 30100 Pilsen, Czech Republic 3 Principles for Surface Engineering Department, G.V. Kurdyumov Institute for Metal Physics of the NAS of Ukraine, Kyiv 03680, Ukraine 4 Mechanical Engineering and Mechatronics Department, West Pomeranian University of Technology, 70310 Szczecin, Poland

Abstract. To improve the surface properties of the steel products, the robotbased 3D laser surface hardening system was applied. AISI 1045 steel flat parts were selectively hardened by a laser heat treatment (LHT) method using a highpower disc laser. The laser hardening tests were performed using a constant power strategy. The single-pass laser-based phase transformation hardening processes were performed. The main influential laser processing parameters, such as laser power (1.35–2.55 kW) and scanning speed (9.0–15.0 mm/s), were selected and studied using a design of experiments. The statistical models were developed using a response surface method (RSM). The LHT parameters were also examined using the analysis of variance (ANOVA). The results showed that the optimized singlepass LHT treatment provided more than 200% increase in surface hardness due to transformation hardening. Keywords: AISI 1045 carbon steel · laser surface hardening · robot-assisted 3D scanning system · hardening intensity · hardness · roughness parameters

1 Introduction To provide surface integrity and improve the functional performance of steel products, the development and improvement of surface modification technologies is an urgent task in manufacturing processes. The laser transformation hardening method by changing the structure in the subsurface layers does not involve the roughness/waviness parameters of the surface profile and chemical composition change of the treated surface is an effective surface heat treatment for finishing processes [1]. It is well-known that the laser-based phase transformation hardening of metal products involves the formation of © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 45–53, 2023. https://doi.org/10.1007/978-3-031-31066-9_5

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an austenitic microstructure during rapid heating and its subsequent transformation to fine martensitic microstructure during cooling by absorbing and transferring the energy of high-concentration to the surface thin layer [2, 3]. Other laser heat treatment techniques include surface melting/alloying [4]. Laser heat treatment (LHT) has some specific advantages [5] as compared to flame hardening and induction hardening. In particular, the LHT process can be implemented selectively and remotely using computer numerical control (CNC) robotic equipment. Moreover, the LHT using advanced programmable scanning optics [6] and a heating temperature control system [7] can be fully controlled as compared to plasma hardening and electron-beam hardening. The effects of the CO2 laser heat processing on the microstructural features in carbon/alloyed steels were widely studied [8–10]. Compared to the conventional CO2 lasers, the appearance on the market of high-power lasers with a higher overall level of economic and technical performance can be expanded using the LHT technology for surface hardening in manufacturing processes. The diode and fiber lasers in continuous wave mode are often used in the laser surface hardening process [5, 11, 12]. In particular, Arai [13] confirmed that the hardening depth formed by a diode laser is 10–20% larger than that using a CO2 laser. Moreover, the compressive residual stress values in the alloyed steel were increased to about −300 MPa after LHT by a diode laser [14]. The friction coefficient values of the LHT-treated area (2 kW fiber laser [15] and 4 kW diode laser [16]) are lower than the untreated sample due to the increased surface hardness. Ponticelli et al. [17] developed an algorithm-optimized model for the control of the fatigue life of carbon steel components processed using the diode laser surface hardening process. The corrosion observation confirms that the LHT-processed samples of AISI 1045 steel (1 kW fiber laser) corrode far more slowly than the unprocessed sample [18]. It should be noted that the disk/fiber lasers combined with the robotic-based 3D scanning systems provide a higher laser processing performance. Moreover, disc lasers combined with scanning optics can be used for the surface hardening of complexly shaped metallic parts [19, 20]. As a consequence, the optimization of the LHT parameters using high-power disc lasers is becoming extremely relevant. In this study, the AISI 1045 steel plane parts were selectively processed by a robotbased 3D laser selective surface hardening system to enhance the surface properties. This work aims to study the effects of LHT using a disc laser and scanning optics on the surface roughness, hardening intensity, and hardness of medium-carbon steel.

2 Experimental Procedures The medium-carbon steel with an average carbon content of 0.45% was used in this work. The chemical composition of the studied steel is presented in Table 1.

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Table 1. Chemical composition and hardness of AISI 1045 steel parts Chemical composition (wt.%) Material

C

Mn

Si

Ni

Cu

P

S

Fe

AISI 1045 steel

~0.45

~0.65

~0,25

≤0,25

≤0,2

≤0,04

≤0,035

Bal

Surface hardness (HV5 / HRC5 ) Material

1

2

3

4

5

6

Average HV5

Average HRC5

AISI 1045 steel

219.3

221.1

214.5

221.2

225.1

229.0

221.7

15.8

The average surface hardness of the initial samples was about 222 HV5 (Table 1). The steel specimens were subjected to polishing before the laser surface hardening tests (Ra = 0.3–0.4 µm). The plane polished samples with the dimension of 100 mm × 400 mm × 12 mm were exposed to laser heat treatment (LHT) using a robot-based 3D scanning laser hardening system, containing a Fanuc M-710iC robot, a Trudisk 8002 solid state disk laser, and SCANLAB scanning optics (Fig. 1).

Fig. 1. Robot-based 3D laser selective surface hardening system

The used solid-state disk laser emits a beam of a wavelength of 1.03 µm. The power of the laser can be reached by 8 kW on the workpiece. The laser was coupled to a 200 µm fiber connected to the scanner (image volume size is 220 × 220 × 140 mm3 at the pre-objective scanning), providing a maximum deflection speed of the laser beam of 21.5 m/s. The Z-axis focus range is ±70 mm. The laser scanning process was monitored and controlled by a RobotSync Unit and SAMLight software [19]. In this study, the LHT treatment of AISI 1045 carbon steel parts was carried out at laser power from 1.35 to 2.55 kW at increments of 600 W and scanning speed from 9 to 15 mm/s at intervals of 3 mm/s (Table 2). The calculated magnitudes of the laser energy

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density fall into the range between 3.4–11.3 J/mm2 . The laser tracks with a width of 10 mm on the surface were formed at a laser spot in a diameter of 0.8 mm and a scanning velocity of the laser beam of 20000 mm/s. The most influential parameters (laser power A(x1 ) and scanning speed B(x2 )) were selected to optimize the LHT regimes using an experimental design (Table 2). The planmatrix of experiments with code-independent factors is given in Table 3 [21]. Table 2. Levels of LHT factors Factor

Factors’ levels xmin (–1)

A(x1 ) is the laser power, P (kW)

1.35

B(x2 ) is the scanning speed, S (mm/s)

9.0

xmax (+1) 2.55 15.0

x0 (0)

x

1.95

600

12.0

3.0

Table 3. Run number and the corresponding LHT parameters Run order

No. test

Coded variable

Actual variable

x1 (Factor 1)

x2 (Factor 2)

x1 [P, kW]

x2 [S, mm/s]

1

LHT1

Pmin

Smin

1.35

9.0

2

LHT2

Pmin

S0

1.35

12.0

3

LHT3

Pmin

Smax

1.35

15.0

4

LHT4

P0

Smin

1.95

9.0

5

LHT5

P0

S0

1.95

12.0

6

LHT6

P0

Smax

1.95

15.0

7

LHT7

Pmax

Smin

2.55

9.0

8

LHT8

Pmax

S0

2.55

12.0

9

LHT9

Pmax

Smax

2.55

15.0

The LHT-hardened surface specimens were evaluated using a Hommelwerke T2000 contact profilometer. The surface profile parameters (average surface roughness (Ra) and maximum height of the roughness profile (Rt)) were studied on a sampling length of 0.8 mm according to the standard ISO 4287–97. Each laser track was subjected to at least three measurements. The surface hardness was estimated using a LV700AT macro-Vickers hardness tester at a load on the indenter of 5 kg for a dwelling time of 15 s. A total of 5–6 measurements were carried out at different zones in the center of the laser track and the averaged magnitudes were given. The hardening intensity of the LHT-treated surface samples was estimated by the HRC values of surface hardness of the untreated and LHT-treated samples by the following formula I hard = (HRChard – HRCin )/HRCin · 100%.

Robot-Assisted 3D Laser Surface Hardening of Medium-Carbon Steel

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3 Results The influence of LHT parameters on the laser energy density is demonstrated in Fig. 2.

Fig. 2. Model graph for interaction effect of the laser power [P, kW] and scanning speed [S, mm/s] on laser energy density of LHT-hardened AISI 1045 carbon steel

It can be seen that the values of the power density of the laser beam are 8.5– 11.0 J/mm2 with increasing laser power (2.0–2.5 kW). The laser power value (F-value = 7.87) is more influential than the scanning speed value (F-value = 0.14), according to the variance analysis for the linear experimental model. The experimental prediction equation in terms of actual factors for the laser energy density (E lb ) response variable of the LHT-hardened carbon steel is as follows: Elb = −1.06 + 3.41P + 0.09S where P is the laser power (kW); S is the scanning speed (mm/s). The developed experimental model is significant (the p-values are less than 0.05 value; Adeq Precision value is greater than 4 value) and can be used to predict the laser energy density. Average surface roughness Ra parameters after the disk laser surface hardening process are given in Fig. 3. Compared to the untreated surface of the sample (Ra = 0.3–0.4 µm; Rt = 3.2–3.5 µm), the Ra parameters were significantly increased after the LHT4 and LHT7–LHT9 treatments (Ra = 0.76–0.88 µm; Rt = 7.53–9.40 µm) because of the partial melting of peaks of the surface profile. The LHT5 and LHT6 treatments almost unchanged the roughness parameters (Ra = 0.34–0.38 µm; Rt = 3.24–3.84 µm) in comparison with the initial sample (Fig. 3). This may be due to the formation of an oxide film on the surface [18]. Based on the results of the surface hardness and hardening intensity of the studied steel (Fig. 4 and 5), it can be confirmed that the defined values of the hardening intensity

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Fig. 3. Average surface roughness of the AISI 1045 carbon steel hardened by LHT

at a laser power of 1.95–2.55 kW (LHT4, LHT5, and LHT7–LHT9 regimes) increased by 275–300% (60–65 HRC5 ) in comparison with the untreated specimen (~16 HRC5 ). It should also be noted that the laser heat treatment at a laser power of 1.35 kW and scanning speed of 9.0 –15.0 mm/s does not lead to the required hardening of the surface layer of the studied steel (Fig. 4). Further increase in laser power (P = ~ 2.0 kW) results in an increase in the surface hardness by approximately 3 times after the laser heat treatment at a scanning speed of 9.0 mm/s (LHT4 regime) and 11 mm/s (LHT5 regime), respectively. This is due to the formation of a fine-grained martensitic microstructure and an increase in the density of dislocations in the near-surface layer [4, 18].

Fig. 4. Average surface hardness of the AISI 1045 carbon steel hardened by LHT

Robot-Assisted 3D Laser Surface Hardening of Medium-Carbon Steel

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The LHT parameters were narrowed for the hardening intensity response variable, setting maximum limits. The selected optimal region was added to the contour plot (Fig. 5). It was observed that increasing the scanning speed led to a decrease in the hardening intensity magnitudes. The hardening intensity is significantly increased with increasing the laser power. At the same time, it is clear that laser power is a more influential parameter than scanning speed.

Fig. 5. Model graphs for interaction effect of the laser power [P, kW] and scanning speed [S, mm/s] on hardening intensity of LHT-hardened AISI 1045 carbon steel

Thus, given the above-mentioned results (Figs. 3, 4 and 5), the robot-assisted 3D scanning laser heat treatment of the AISI 1045 steel can be performed at the laser power of 1.9–2.2 kW, the scanning speed of 11.0–13.0 mm/s, and the laser spot scanning velocity (10 mm × 0.8 mm) of 20000 mm/s. The optimized LHT processing leads to an increased in surface hardness to ~60 HRC5 .

4 Conclusion This paper is devoted to the effects of single-pass laser heat treatment (LHT) using scanning optics and high-power disc laser on the surface hardness and roughness parameters of AISI 1045 carbon steel parts. The study reaches the following conclusions: 1. The surface roughness parameters were significantly increased after the LHT4 and LHT7–LHT9 treatments (Ra = 0.76–0.88 µm; Rt = 7.53–9.40 µm), while the LHT5 and LHT6 treatments almost unchanged the surface roughness parameters (Ra = 0.34–0.38 µm; Rt = 3.24–3.84 µm) as compared to the unhardened sample (Ra = 0.3–0.4 µm; Rt = 3.2–3.5 µm); 2. Analysis of the surface roughness and hardness magnitudes allowed to choose the optimum region (laser power in a range of 1.9–2.2 kW and the scanning speed in a range of 11–13 mm/s) for single-pass disk LHT of medium-carbon steel, which provides ~200% hardening intensity increase due to transformation hardening;

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3. The study of the heat-affected zone and microstructural features in the near-surface layers, as well as the surface texture by optical profilometer and corrosion behavior of the LHT-processed AISI 1045 steel parts is planned in further studies.

Acknowledgements. The authors would like to thank the Ministry of Education, Youth and Sports of the Czech Republic and the Ministry of Education and Science of Ukraine for financial support of the Ukrainian-Czech project (Project No. 0122U002389). Partial support by the Ulam NAWA program (Grant No. BPN/ULM/2021/1/00153) and the National Academy of Sciences of Ukraine (Project No. 0119U001167).

References 1. Frerichs, F., et al.: Process signature for laser hardening. Metals 11, 465 (2021). https://doi. org/10.3390/met11030465 2. Kennedy, E., et al.: A review of the use of high power diode lasers in surface hardening. J. Mater. Process. Tech. 155–156, 1855–1860 (2004). https://doi.org/10.1016/j.jmatprotec. 2004.04.276 3. Santhanakrishnan, S.: An experimentally based thermo-kinetic phase transformation model for multi-pass laser heat treatment by using high power direct diode laser. Int. J. Adv. Manuf. Technol. 64, 219–238 (2013). https://doi.org/10.1007/s00170-012-4029-z 4. Yao, J., et al.: Laser surface hardening. In: Laser Applications in Surface Modification, Advanced Topics in Science and Technology in China, vol. 65, pp. 83–102 (2022). https:// doi.org/10.1007/978-981-16-8922-2_4 5. Li, R., et al.: A comparative study of high-power diode laser and CO2 laser surface hardening of AISI 1045 steel. J. Mater. Eng. Perform. 23, 3085–3091 (2014). https://doi.org/10.1007/ s11665-014-1146-x 6. Chen, C., et al.: Statistical modelling and optimization of microhardness transition through depth of laser surface hardened AISI 1045 carbon steel. Opt. Laser Technol. 124, 105976 (2020). https://doi.org/10.1016/j.optlastec.2019.105976 7. Lesyk, D., Alnusirat, W., Martinez, S., Mordyuk, B., Dzhemelinskyi, V.: Comparison of effects of laser, ultrasonic, and combined laser-ultrasonic hardening treatments on surface properties of AISI 1045 steel parts. In: Tonkonogyi, V., Ivanov, V., Trojanowska, J., Oborskyi, G., Pavlenko, I. (eds.) Advanced Manufacturing Processes III. InterPartner 2021, pp. 313–322. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-91327-4_31 8. Orazi, L., Rota, A., Reggiani, B.: Experimental investigation on a novel approach for laser surface hardening modelling. Int. J. Mech. Mater. Eng. 16, 2 (2021). https://doi.org/10.1186/ s40712-020-00124-0 9. Hung, T.-P., et al.: Temperature modeling of AISI 1045 steel during surface hardening processes. Materials 11, 1815 (2018). https://doi.org/10.3390/ma11101815 10. Jerniti, A.G., et al.: Single track laser surface hardening model for AISI 4340 steel using the finite element method. Model. Numer. Simul. Mater. Sci. 6, 17–27 (2016) 11. Li, Z.-X., et al.: Microstructure distribution and bending fracture mechanism of 65Mn steel in the laser surface treatment. Mater. Sci. Eng. A 850, 143568 (2022). https://doi.org/10.1016/ j.msea.2022.143568 12. Tarchoun, B., et al.: Experimental investigation of laser surface hardening of AISI 4340 steel using different laser scanning patterns. J. Mineral Mater. Charact. Eng. 8, 9–26 (2020). https:// doi.org/10.4236/jmmce.2020.82002

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13. Arai, T.: Processing with application of high-power semiconductor laser – theoretical analysis of heat source and application to surface processing. Int. J. Autom. Technol. 14, 534–545 (2020). https://doi.org/10.20965/ijat.2020.p0534 14. Muthukumaran, G., Babu, P.D.: Analysis of residual stress distribution and corrosion in laser surface hardened low alloy steel with a flat top-hat laser beam, using a high-power diode laser. Arab. J. Sci. Eng. 47, 8785–8803 (2022). https://doi.org/10.1007/s13369-021-06350-8 15. Raza, M.S., et al.: Surface modification of high-carbon steel using fiber laser and its thermal, microstructural and tribological analysis. J. Mater. Eng. Perform. 28, 1873–1883 (2019). https://doi.org/10.1007/s11665-019-03943-1 16. Park, C., et al.: Influence of diode laser heat treatment and wear conditions on the fretting wear behavior of a mold steel. Wear 434–435, 202961 (2019). https://doi.org/10.1016/j.wear. 2019.202961 17. Ponticelli, G.S., et al.: An optimal genetic algorithm for fatigue life control of medium carbon steel in laser hardening process. Appl. Sci. 10, 1401 (2020). https://doi.org/10.3390/app100 41401 18. Lesyk, D.A., et al.: Influence of combined laser heat treatment and ultrasonic impact treatment on microstructure and corrosion behavior of AISI 1045 steel. Surf. Coat. Technol. 401, 126275 (2020). https://doi.org/10.1016/j.surfcoat.2020.126275 19. Lesyk, D., Hruska, M., Dzhemelinkyi, V., Danyleiko, O., Honner, M.: Selective surface modification of complexly shaped steel parts by robot-assisted 3D scanning laser hardening system. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V, vol. 472, pp. 30–36. Springer, Cham (2022). https://doi.org/10.1007/978-3031-05230-9_3 20. Lee, K.H., et al.: Microstructure and hardness of surface melting hardened zone of mold steel, SM45C using Yb:YAG disk laser. J. Weld. Join. 34, 75–81 (2016). https://doi.org/10.5781/ JWJ.2016.34.1.75 21. Barka, N., et al.: Effects of laser hardening process parameters on hardness profile of 4340 steel spline – an experimental approach. Coatings 10, 342 (2020). https://doi.org/10.3390/coa tings10040342

Nonlinear Control of a Robotic Arm in the Electromechanical Domain Rosario La Regina1 , Maria Curcio1 , and Carmine Maria Pappalardo2(B) 1 MEID4 Academic Spin-Off of the University of Salerno,

Via Giovanni Paolo II, 132, 84084 Fisciano, Italy 2 Department of Industrial Engineering, University of Salerno,

Via Giovanni Paolo II, 132, 84084 Fisciano, Italy [email protected]

Abstract. A growing number of industries are paying attention to research in robotics. Precision and speed of execution are necessary features that must not be underestimated during the design phase. In this context, the choice of actuators to be used and the control policy play a key role. In this paper, a prototype of a robotic arm is proposed together with its dynamic analysis. In particular, the problem at hand was studied in a multi-domain environment using two MATLAB toolboxes, namely SIMSCAPE MULTIBODY and SIMSCAPE ELECTRICAL. By combining multibody dynamics and electrical dynamics, the developed model of the robotic system is as close to reality as possible. The control architecture chosen is a proportional-derivative controller, which is widely used in industry for mechanical systems of this type. Consequently, from a software-in-the-loop perspective, the design and calibration of the controller yield more accurate results for subsequent hardware-in-the-loop and control prototyping phases. Keywords: robotic arm · nonlinear control · direct current motor · SIMSCAPE MULTIBODY · SIMSCAPE ELECTRICAL · Robotics System Toolbox

1 Background Information In this section, a brief analysis of the state of the art regarding robotic arms is provided for the benefit of the reader. A robotic arm is a system whose structure consists of a series of rigid elements connected by appropriate constraints [1–3]. Based on their configuration, different types of manipulators can be distinguished. In particular, two macro-categories are mainly used in mechanics: robots with different elements connected in series, called serial robots, and robots with parallel connections, called parallel robots [4, 5]. Serial structures, also known in applied mechanics as open kinematic chains, are currently the most widely used in the industry by far. The serial approach, which is the one used in the present investigation, offers higher flexibility in movement, on the other hand, the parallel approach allows for greater stiffness [6]. The purpose of robotic system development is to create systems that are capable of performing work autonomously. The development of these kinds of systems requires the solving of problems in mechanics © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 54–61, 2023. https://doi.org/10.1007/978-3-031-31066-9_6

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[7], control [8], and actuation [9]. The first step is to define the various component parts and to define their relative position within space. The relative motion between each part is made possible through the use of actuators, which provide the torque or driving force to the robots. Generally, the three commonly used are: electromagnetic, hydraulic, and pneumatic [10]. To ensure greater accuracy in terms of position, speed, and driving torque, servo motors are adopted in robotic applications; the most popular ones are permanent magnet direct current motors and brushless direct current motors [11, 12]. Obviously, if actuator systems are present, it is necessary to mount appropriate sensors on the system to identify the position of the manipulator during its operations. The implementation of sensors is essential as they allow, instant-by-instant, the knowledge of the state of the system so that the control board can implement appropriate corrections in order to achieve the required target [13, 14]. The control process takes place through appropriate systems implemented within the board. In particular, the proper movement of a robot frequently requires the coordinated control of multiple motors. Such control is imparted by designing a controller for each motor [15, 16]. There are several types of control, the most commonly used consists of using a proportional derivative controller, which is also considered for the development of the robotic arm presented in the following paper [17, 18]. Other control techniques have been proposed in the literature [19, 20]. The one that most closely resembles the one previously mentioned is the design of a PID (Proportional Integrated Derivative) controller with fuzzy logic [21, 22]. The use of fuzzy logic has led to advantages over the use of PID alone since the system so designed has faster implementation times and less noticeable overshoots [23]. In general, the principal research areas of interest for the authors are multibody system dynamics of articulated mechanisms and machines, nonlinear control of robotic mechanical systems, and applied system identification of structural systems [24–26]. More specifically, this paper deals with the development of a nonlinear control system of a tridimensional revolute robotic arm modeled in an electromechanical domain.

2 Description of the Robotic System The robotic arm studied in this paper is aimed at noninvasive fatigue testing of seats, chairs, and etcetera. It is composed of a frame, two links, and an end-effector. Each part is connected to the other according to a serial structure through a revolute joint. Thus, the system is composed of four rigid bodies and three revolute joints. According to the Kutzbach formula, which serves to determine the degrees of freedom of an articulated mechanical system, the presented system has three degrees of freedom in space. By adopting the classical approach used in robotics, it is necessary to introduce three local reference frames to properly develop the model of the robotic arm, as shown in Fig. 1. The main objective is to study the multi-environment dynamics of the virtual prototype of the system at hand. Table 1 shows the Denavit-Hartenberg parameters used to schematize the robotic arm. Since the system has three degrees of freedom, it is necessary to include three actuators in order to have a completely actuated system. The actuators chosen to drive the system are direct current motors and were implemented through the use of two MATLAB toolboxes: SIMSCAPE MECHANICAL and SIMSCAPE ELECTRICAL. The schematization of the motor is presented in Fig. 2.

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Fig. 1. Robotic system geometry schematization.

Table 1. Denavit-Hartenberg parameters n-link

Joint

ϑ

d

a

α

1

R

ϑ1 (t)

0

0

0

2

R

ϑ2 (t)

0

−l1

0

3

R

ϑ3 (t)

−s1

l2

0

Fig. 2. Motor schematization.

The subscript i denotes the i-th motor. The symbol Jm,i is the moment of inertia of the i-th motor measured in (kgm2 ). The symbol Li represents the inductance of the i-th motor measured in (mH), Ri is the resistance of the i-th motor measured in (), and Eb,i represents the back electromotive force measured in (V), and it is given by: Eb,i = Kb,i nm,i

(1)

Nonlinear Control of a Robotic Arm in the Electromechanical Domain

57

where Kb,i is the back electromotive force constant measured in (V/rpm) and nm,i is the engine speed of the motor measured in (rpm). The symbol Vi indicates the input voltage of the i-th motor, which depends on the control logic. In this investigation, it is considered a derivative proportional controller acting on the position of the i-th link. Thus, one can write the input voltage as follows:     ref ref (2) Vi = Kp,i θi − θi + Kd ,i θ˙i − θ˙i where, Kp,i plays the role of a constant of proportionality measured in (V/deg), and it is multiplied by the error of tracking the trajectory committed by the system, that is, the deviation between the effective time law and the nominal time law, Kd,i plays the role of a derivative constant measured in (V/deg/s), and it is multiplied by the error between the actual and the nominal value of the speed. By applying the second law of Kirchhoff, one can write: Vi = Li I˙i + Ri Ii + Eb,i

(3)

where ˙I i is the time derivative of the current. By combining the Eqs. (2) and (3), the following relationship is obtained:     ref ref Kp,i θi − θi + Kd ,i θ˙i − θ˙i = Li I˙i + Ri Ii + Eb,i (4) Once schematized the electrical part of the system, it is also necessary to develop mechanical schematization. For the sake of simplicity, the system is simplified by imagining that a perfectly statically and dynamically balanced disk is connected to the motor. By considering the simplified assumptions adopted, it is possible to write the equation of the electromechanical system as follows:  Ji θ¨i − Kb,i Ii =0   (5) ref ref Kp,i θi − θi + Kd ,i θ˙i − θ˙i = Li I˙i + Ri Ii + Eb,i where Ji is the total moment of inertia given by the sum of the moment of inertia of the disk and the moment of inertia of the motor.

3 Numerical Results and Discussion The maneuver to be simulated in this paper is a passive phase of processing in which the manipulator reaches the final configuration, starting from an initial position defined by the parent company, in which it will begin its active phase of processing, which is not discussed in this paper. In this analysis, the movement from the initial to the final configuration is defined by a series of points occupied by the individual link, imposing a trapezoidal velocity profile. Once schematized the system, the motors are chosen, and the speed and position profile are defined. Finally, the dynamic behavior of the system is studied, and the tuning of the parameters of the controllers is carried out. The parameters of the motors and controllers used in the simulation are reported in Table 2.

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Motor

L (mH)

R ()

Kb (V/rpm)

J (kg * m2 )

Controller Parameters [KP ; KD ]

1

0.35

0.45

18.2e−3

0.0029

[40; 35]

2

4.15

1.8

17e−3

0.00018

[80; 75]

3

2

1.33

6.4e−3

0.0015

[90.5; 60.5]

Fig. 3. Control system schematization.

The dynamic behavior of the robotic arm is simulated using SIMSCAPE MULTIBODY. The implementation of the system in the software is shown in Fig. 3. Using three separate motors and controllers, the corresponding numerical results for the position and velocity are shown in Fig. 4 and in Fig. 5, in which the solid line represents the actual value, and the dashed line represents the reference value. Figure 4(a) shows the comparison between the actual value of the position and the nominal value of the position for the first link. Figure 4(b) represents the comparison between the actual value of the position and the nominal value of the position for the second link. Figure 4(c) shows the comparison between the actual value of the position and the nominal value of the position for the third link. Figure 5(a) shows the comparison between the actual value of the velocity and the nominal value of the velocity for the first link. Figure 5(b) represents the comparison between the actual value of the velocity and the nominal value of the velocity for the second link. Figure 5(c) shows the comparison between the actual value of the velocity and the nominal value of the velocity for the third link. The numerical results of voltage are shown in Fig. 6.

Nonlinear Control of a Robotic Arm in the Electromechanical Domain

(a)

(b)

59

(c)

Fig. 4. Numerical results: position.

(a)

(b)

(c)

Fig. 5. Numerical results: velocity.

(a)

(b)

(c)

Fig. 6. Numerical results: voltage.

Figure 6(a) shows the control voltage for the first link. Figure 6(b) represents the control voltage for the second link. Figure 6(c) shows the control voltage for the third link. A voltage overshoot is present in the initial surround due to the fact that, during the simulation phase, the delay caused by the sensor system was not taken into account. However, the voltage values obtained downstream of the numerical simulation respect the values of the voltage actually applicable to the motors and the system reaches the desired target without presenting any oscillations in the surroundings of the final configuration [27, 28].

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4 Conclusions and Future Work This investigation focuses on the development of a virtual prototype of a robotic arm in an electromechanical domain. The starting point of this paper defines the main steps in the realization of a robotic arm. Different types of actuators that can be used are described, with an emphasis on direct current actuators. The final purpose of the present investigation is to analyze a nonlinear control system in a multidomain simulation environment, in order to have a numerical simulation as close to reality as possible. This work can be seen as the first approach of the authors to the design of real robotic systems in the electromechanical domain. Future research work will be devoted to further refining the simulation by modifying the motors used, simulating also the active phase of processing, taking into account the contact between the end effector and a flexible body, and testing other control strategies. In this vein, both the problems of position control and orientation guidance of the end effector will be addressed in future investigations.

References 1. Muscat, M., Cammarata, A., Maddio, P.D., Sinatra, R.: Design and development of a towfish to monitor marine pollution. Euro-Mediterr. J. Environ. Integr. 3(1), Article no. 11 (2018) 2. Cammarata, A., Lacagnina, M., Sinatra, R.: Closed-form solutions for the inverse kinematics of the Agile Eye with constraint errors on the revolute joint axes. In: IEEE International Conference on Intelligent Robots and Systems, November 2016, Article no. 7759073, pp. 317– 322 (2016) 3. Huang, Z., Xi, F., Huang, T., Dai, J.S., Sinatra, R.: Lower-mobility parallel robots: theory and applications. Adv. Mech. Eng. 2, Article no. 927930 (2010) 4. De Simone, M.C., Veneziano, S., Guida, D.: Design of a non-back-drivable screw jack mechanism for the hitch lifting arms of electric-powered tractors. Actuators 11(12), 358 (2022) 5. De Simone, M.C., Celenta, G., Rivera, Z.B., Guida, D.: Mechanism design for a low-cost automatic breathing applications for developing countries. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) NT 2022. LNNS, vol. 472, pp. 345–352. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_40 6. De Simone, M.C., Laiola, V., Rivera, Z.B., Guida, D.: Dynamic analysis of a hybrid heavyvehicle. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) NT 2022. LNNS, vol. 472, pp. 236–243. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_27 7. De Simone, M.C., Ventura, G., Lorusso, A., Guida, D.: Attitude controller design for microsatellites. In: Karabegovi´c, I. (ed.) NT 2021. LNNS, vol. 233, pp. 21–31. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_2 8. De Simone, M.C., Guida, D.: Experimental investigation on structural vibrations by a new shaking table. In: Carcaterra, A., Paolone, A., Graziani, G. (eds.) AIMETA 2019. LNME, pp. 819–831. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-41057-5_66 9. Colucci, F., De Simone, M.C., Guida, D.: TLD design and development for vibration mitigation in structures. In: Karabegovi´c, I. (ed.) NT 2019. LNNS, vol. 76, pp. 59–72. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-18072-0_7 10. Guida, R., De Simone, M.C., Daši´c, P., Guida, D.: Modeling techniques for kinematic analysis of a six-axis robotic arm. In: IOP Conference Series: Materials Science and Engineering, vol. 568, no. 1, Article no. 012115 (2019)

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11. Rivera, Z.B., De Simone, M.C., Guida, D.: Unmanned ground vehicle modelling in Gazebo/ROS-based environments. Machines 7(2), Article no. 42 (2019) 12. De Simone, M.C., Rivera, Z.B., Guida, D.: Obstacle avoidance system for unmanned ground vehicles by using ultrasonic sensors. Machines 6(2), Article no. 18 (2018) 13. De Simone, M.C., Guida, D.: Modal coupling in presence of dry friction. Machines 6(1), Article no. 8 (2018) 14. Salvati, L., d’Amore, M., Fiorentino, A., Pellegrino, A., Sena, P., Villecco, F.: Development and testing of a methodology for the assessment of acceptability systems. Machines 8, 47 (2020) 15. Formato, A., Ianniello, D., Romano, R., Pellegrino, A., Villecco, F.: Design and development of a New Press for Grape Marc. Machines 7(3), 51 (2019) 16. Formato, A., Ianniello, D., Pellegrino, A., Villecco, F.: Vibration-based experimental identification of the elastic moduli using plate specimens of the olive tree. Machines 7(2), Article no. 46 (2019) 17. Sun, X., Liu, H., Song, W., Villecco, F.: Modeling of Eddy current welding of rail: threedimensional simulation. Entropy 22, Article no. 947 (2020) 18. Liguori, A., Armentani, E., Bertocco, A., Formato, A., Pellegrino, A., Villecco, F.: Noise reduction in spur gear systems. Entropy 22, 1306 (2020) 19. Villecco, F., Aquino, R.P., Calabrò, V., Corrente, M.I., Grasso, A., Naddeo, V.: Fuzzy-assisted ultrafiltration of wastewater from milk industries. In: Naddeo, V., Balakrishnan, M., Choo, K.-H. (eds.) Frontiers in Water-Energy-Nexus—Nature-Based Solutions, Advanced Technologies and Best Practices for Environmental Sustainability. ASTI, pp. 239–242. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-13068-8_59 20. Liguori, A., Formato, A., Pellegrino, A., Villecco, F.: Study of tank containers for foodstuffs. Machines 9, Article no. 44 (2021) 21. Li, T., Kou, Z., Wu, J., Yahya, W., Villecco, F.: Multipoint optimal minimum entropy deconvolution adjusted for automatic fault diagnosis of hoist bearing. Shock Vibr. 2021, Article no. 6614633 (2021) 22. Formato, A., Romano, R., Villecco, F.: A novel device for the soil sterilizing in sustainable agriculture. In: Karabegovi´c, I. (ed.) NT 2021. LNNS, vol. 233, pp. 858–865. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_94 23. Naviglio, D., et al.: Study of the grape cryo-maceration process at different temperatures. Foods 7, 107 (2018) 24. Pappalardo, C.M., Guida, D.: A comparative study of the principal methods for the analytical formulation and the numerical solution of the equations of motion of rigid multibody systems. Arch. Appl. Mech. 88, 2153–2177 (2018) 25. Pappalardo, C.M., La Regina, R., Guida, D.: Multibody modeling and nonlinear control of a pantograph scissor lift mechanism. J. Appl. Comput. Mech. 9, 129–167 (2023) 26. Pappalardo, C.M., Vece, A., Galdi, D., Guida, D.: Developing a reciprocating mechanism for the emergency implementation of a mechanical pulmonary ventilator using an integrated CAD-MBD procedure. FME Trans. 50(2), 238–247 (2022) 27. Neziri´c, E., Isi´c, S., Karabegovi´c, I.: Vibration quantity share of multiple faults with similar frequency spectrum characteristics in rotational machinery. Periodica Polytechnica Mech. Eng. 66(3), 213–218 (2022) 28. Tomovi´c, R., Dizdar, S., Isi´c, S., Tuka, S., Karabegovi´c, I.: FEM analysis of inspection manhole on large steel tanks. Proc. Inst. Mech. Eng. Part E: J. Process Mech. Eng. 235(4), 1235–1247 (2021)

A New Hybrid PSO-JAYA Algorithm for Function Optimization Lucijano Berus, Jernej Hernavs, Tadej Peršak, David Potoˇcnik, Simon Klanˇcnik, Janez Gotlih, Timi Karner, and Mirko Ficko(B) Faculty of Mechanical Engineering, Production Engineering Institute, University of Maribor, 2000 Maribor, Slovenia [email protected]

Abstract. A simple yet powerful population based algorithm (PSO-JAYA) is proposed with the combination of Particle Swarm Optimization (PSO) and JAYA optimization algorithms. The idea is to synthesize the exploration abilities of PSO and JAYA into hybrid PSO-JAYA, which incorporates both algorithms’ strengths. Benchmark test functions are used to compare PSO-JAYA with other well-known optimization algorithms. Keywords: Particle swarm optimization · Function optimization · Jaya optimization · Constrained benchmark problems

1 Introduction Mathematically, a single-objective design optimization problem can be formulated as: minf (x), x ∈ S

(1)

where f is a scalar objective function and S is the set of constraints also called feasible set or feasible region and can be defined as:   S = x ∈ Rn |gj (x) ≥ 0, j = 1 . . . p; hi (x) = 0, i = 1 . . . m; xkl ≤ xk ≤ xku , k = 1 . . . n . (2) To solve single-objective optimization problems new algorithms are steadily being developed. To find the best algorithm for a specific problem, algorithm performance testing is required. As a first estimation to evaluate the performance of algorithms on very general cases algorithm benchmarking is used. Hellwig and Beyer [1] presented common principles that need to be taken into account when considering benchmarking problems for constrained optimization and reviewed current benchmark environments for testing Evolutionary Algorithms. Aci et al. [2] have developed a modified Dragonfly Algorithm (DA) that uses the Brownian motion instead of the Levy flight mechanism, used by the original DA, to improve the randomization stage. To evaluate the performance of the modified DA, authors tested the algorithm on 15 single-objective and 6 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 62–68, 2023. https://doi.org/10.1007/978-3-031-31066-9_7

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multi-objective benchmark problems and compared its performance to the original DA. Zhang et al. [3] developed a hybrid metaheuristic algorithm for solving the Job Shop Scheduling Problem. They integrated the Shuffled Frog Leaping Algorithm (SFLA), Intelligent Water Drops (IWD) algorithm and the Path Relinking (PR) algorithm. For algorithm performance testing the used the Travailing Salesman Problem (TSP) on four benchmark instances. Waibel et al. [4] investigated the performance of a wide selection of single-objective randomized, deterministic and model-based algorithms, when applied to a large set of well-known building energy simulation problems. In addition, the authors studied the impact of parameter tuning on the performance of the algorithms. To evaluate the algorithms, they developed a new metric based on ranks and performed extensive experiments to draw generalized conclusions on convergence times, stability and robustness of the algorithms. They found that no single algorithm dominates the benchmark for all considered performance metrics and/or optimization problems. The optimization is recognized as a challenging task with significant impact and application potential upon multiple fields of problems, in this sense current study presents a novel hybrid PSO-JAYA optimization technique. Discussed technique is a combination of basic PSO and JAYA optimization methods. Paper is organized as follows; second part offers descriptions of PSO, JAYA and PSO-JAYA formulations. In the third part, the experimental results and discussion on optimization algorithms used for finding the benchmark functions optimum (minimum), are provided. In the last section, the overall conclusion is conducted.

2 Materials and Methods 2.1 Standard Particle Swarm Optimization Algorithm PSO algorithm is a population based optimization method, first introduced by Kennedy and Eberhart [5]. PSO is a heuristic iteration based method [6] and has proven it’s applicability at tackling diverse sets of problems [7, 8]. PSO was inspired, and is set to mimic, a flock of birds searching for food which is represented as an optimal solution. Each bird (particle) is set to find a solution based on its current direction of flying, its best solution reached till now (autobiographical memory) and the collectively best reached solution until now (collective knowledge). Population based search for the specified function’s optimal solution is initialized and every particle is set to search the space, on the basis of it’s personal pbestid and collective best experience gbest. The PSO workings t+1 (Eq. 3) and particle’s position are summarized by equations for the particle’s velocity vid t+1 xid (Eq. 4):     t+1 t t t + C2 rand2 ∗ gbest − xid = wvid + C1 rand1 ∗ pbestid − xid vid

(3)

t+1 t+1 t xid = xid + vid

(4)

where t is the current iteration, id current particle’s subscript, w the inertia weight coefficient and rand () the generated random number in [0, 1]. The acceleration coefficients C1 and C2 represent the weights for personal and collective particle’s preferences, if

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C1 is larger than C2 each particle will search for a new solution mostly based on its personal best solution pbestid . At the first iteration the velocities are set to zero and the particles positions are randomly generated across the search space. For the workings of presented PSO algorithm the user is set to specify the number of particles (swarm size), the number of iterations, constraints and provide the problem described as a function. 2.2 Standard JAYA Optimization Algorithm A new approach for solving constrained and unconstrained optimization problems was proposed in 2016 by Rao [9]. Jaya is a population-based heuristic algorithm. Its main asset is an absence of the tunable parameters, which are usually present in other evolutionary or swarm intelligence algorithms (e.g. Particle Swarm Optimization – PSO, Genetic Algorithm – GA, Evolution Programming – EP, Ant Colony Optimization – ACO, Artificial Bee Colony - ABC, etc.). The improperly set parameters lead to either an increase in computation or yield towards the local optimal solution. Also, a tuning of algorithm-specific parameters makes the optimization computation time consuming and as such, JAYA is time efficient. These attributes make it compelling to researchers who found a way to implement JAYA in use cases like optimizing PID controller for DC motor speed control [10] or combining it with the fuzzy C-means based model simplification [11]. Most recently, Jaya was used for solving a multi-objective ORPD (Optimal Reactive Power Dispatch) problem in power systems [12] and optimizing the walking pattern generator for a biped robot [13]. The algorithm starts with the definition of initial population size, a number of design variables and termination criterion. This is followed by the identification of best and worst solutions in the population. Solutions are further modified, based on best and worst solutions according to optimization function Eq. 5:  t      t+1 t  − rand2 iterworst − xt  , (5) = xid + rand1 iterbest − xid xid id t+1 where xid denotes a modified value (vector with the dimensionality of the tested funct represents the current tion) for the id-th candidate during the t-th iteration. Similarly, xid candidate’s position. After each iteration the best candidate has variable value iterbest and the worst iterworst. The two random numbers for the respective variable during  t the    ” t-th iteration rand1 and rand2 are in the range [0, 1]. The term “rand1 iterbest − xid indicatesthe inclination  tofthe solution to move towards the best solution and the term  ” represents proneness of the solution to avoid the worst “−rand2 iterworst − xid t and x t+1 . x t+1 is accepted only if it solution. The comparison is made between xid id id gives better function value. All the accepted function values at the end of the iteration are maintained and these values become the input to the next iteration. These steps are repeated until the termination criterion is met. Once satisfied, the algorithm reports an optimum solution.

2.3 Hybrid PSO-JAYA Optimization Algorithm The combined PSO-JAYA algorithm is comprised of basic PSO and JAYA methods in discussed manner. The inspiration for synthesis of discussed methods has been their

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65

resemblance. PSO for example is comprised of inertia, personal and global best parts, JAYA on the other hand of iteration best and iteration worst parts. The idea of new hybrid PSO-JAYA based algorithm is to combine all the parts into single procedure. t+1 , based on hybrid PSO-JAYA Whole procedure of searching new particle position xid is represented by Eq. 6.    t   t+1 t t t + C2 rand2 ∗ gbest − xid = xid + wvid + C1 rand1 ∗ pbestid − xid xid (6)   t −C3 rand3 ∗ iterworst − xid t the particle’s velocity, where t is the current iteration, id current particle’s subscript, vid w the inertia weight coefficient and rand () the generated random number in range [0, 1]. The acceleration coefficients C1 , C2 and C3 represent the personal best, collective best and iteration worst preferences weights. The pbestid and gbest stand for personal and global best positions (such as in standard PSO algorithm), and iterworst for worst particle selected among all particles after one iteration. Part of Eq. 6 in squared brackets represents t+1 in subsequent iteration. In the first the velocity part (similar to PSO) and is used as a vid iteration the generated positions are randomly spread across the search space, defined by function constrains. The velocities in the first iteration are set to zero.

3 Experimental Results and Discussion To evaluate performance of PSO-JAYA, it is applied on 5 benchmark functions f 1 , f 2 , f 16 , f 17 and f 18 [14]. Table 1 depicts these benchmark functions, their dimensions, the ranges (constraints) of their search space and the minimum function value. Table 1. Benchmark functions. Function f1 (x) = ni=1 xi2

f2 (x) = ni=1 |xi | + ni=1 |xi | f16 (x) = −2.1x14 + 13 x16 + x1 x2 − 4x22 +4x24 2  5.1 2 5 x f17 (x) = x2 − x + − 6 1 4π 2 1 π +10(1 1 cosx1 + 10 − 8π

Dimensions

Range

minf (x)

30

[−100, 100]

0

30

[−100, 100]

0

2

[−5, 5]

−1.0316

2

[−5, 5]

0.3979

(continued)

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Function

Dimensions

Range

minf (x)

2

[−2, 2]

3

f18 (x) = 1 + (x1 + x2 + 1)2 (19 −14x1 + 3x12 −14x2 + 6x1 x2  +3x22 ∗[30 +(2x1 − 3x2 )2  ∗ 18 − 32x1 + 12x12 +48x2 − 36x1 x2  +27x22

As discussed before, our objective is minimization of benchmark functions in Table 1. PSO, JAYA and PSO-JAYA have several parameters to be specified before the start of optimization procedure. For PSO stated parameters were used; swarm size = 30, C1 = 2, C2 = 2, w is decreased linearly from 0.9 to 0.2, maximum iteration = 1000 and stopping criteria = maximum iteration. For JAYA we used population size = 30, maximum iteration = 1000 and stopping criteria = maximum iteration. For hybrid PSOJAYA the hyper-parameters were equal to; population size = 30, C1 = 0.8, C2 = 0.8, C3 = 0.5 and w are linearly decreased from 1 to 0.8, maximum iteration = 1000 and stopping criteria = maximum iteration. For better comparison and broader assessment of PSO-JAYA workings, also GSA and hybrid PSOGSA are depicted in Table 2, wherein Ave indicates average result among 30 runs and Best the best result among 30 runs. Figure 1 depicts the iteration process of PSO, JAYA and PSO-JAYA. For GSA and PSOGSA the authors in [15] used these settings: population size = 30, C1 = 0.5, C2 = 1.5, w = random number in [0, 1], G0 = 1, α = 20, maximum iteration = 1000 and stopping criteria = maximum iteration. The experimental results presented in Table 2 are bolded if they represent function value, which is the closest value to global minimum of tested benchmark function.

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Table 2. Benchmark function minimalization results of tested optimization algorithms over 30 runs. f

GSA [15] Ave

Best

PSOGSA [15]

PSO

Ave

Ave

Best

JAYA Best

Ave

PSO-JAYA Best

Ave

Best

f1

1.19e − 7.92e − 6.66e − 4.91e − 2.19e − 2.16e − 1.02e − 2.18e − 7.63e − 1.31e − 16 17 19 19 06 08 06 07 91 91

f2

4.77e − 4.17e − 3.79e − 3.18e − 461.11 08 08 09 09

2.7e − 03

2.23e + 0.4216 21

4.24e − 1.74e − 45 45

f16 −1.0316 −1.0316 −1.0316 −1.0316 −1.0316 −1.0316 −1.0316 −1.0316 −1.0316 −1.0316 f17 0.3979

0.3979

0.3979

0.3979

0.3979

0.3979

0.3979

0.3979

0.3979

0.3979

f18 3

3

3

3

3

3

3

3

3

3

Fig. 1. All 30 runs comparison between PSO, JAYA and PSO-JAYA on benchmark function f 1 .

4 Conclusion Every problem can be to some extent approximated with representative mathematical description in the form of function. Optimization algorithms are used in order to find optimal problem state, whether that is maximum or minimum. In this research, a new hybrid algorithm PSO-JAYA is introduced utilizing strengths of PSO and JAYA optimization algorithms. The main difference between JAYA and PSO-JAYA, is that JAYA excepts the new solution (new particle) only if the new solution is better than previous solution (from previous iteration), wherein PSO-JAYA excepts the new solution (disregard to the particle’s previous solution) and remembers the best particle solution as

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pbestid solution. The main difference between PSO and PSO-JAYA, is that PSO algorithm takes into account only personal and global best solutions, wherein PSO-JAYA adds the iteration worst iterworst into account. The performance of PSO, JAYA and PSO-JAYA is evaluated on 5 bentchmark functions and the results show PSO-JAYA outperforms them both, including some other tested optimization algorithms. Future work should be directed into additional study of a hyperparameters used in PSO-JAYA, with the end goal of making the presented algorithm parameter-less. Additional study on varying the constants is needed and comparison with broader set of optimization algorithms, tested on broader set of benchmark functions. The authors also encourage researchers to use PSO-JAYA on real problems to further assess its performance.

References 1. Hellwig, M., Beyer, H.G.: Benchmarking evolutionary algorithms for single objective realvalued constrained optimization - a critical review. Swarm Evol. Comput. 44, 927–944 (2019) 2. Aci, C.I., Gulcan, H.: A modified dragonfly optimization algorithm for single- and multiobjective problems using Brownian motion. Comput. Intel. Neurosc. 2019, 1–17 (2019) 3. Zhang, H., Liu, S., Moraca, S., Ojstersek, R.: An effective use of hybrid metaheuristics algorithm for job shop scheduling problem. Int. J. Simul. Model. 16(4), 644–657 (2017) 4. Waibel, C., Wortmann, T., Evins, R., Carmeliet, J.: Building energy optimization: an extensive benchmark of global search algorithms. Energ. Buildings 187, 218–240 (2019) 5. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of the 1995 IEEE International Conference on Neural Networks, pp. 1942–1948 (1995) 6. Kennedy, J., Shi, Y., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann Publishers, San Francisco, USA (2001) 7. Qiang, C., Chengpeng, Z., Zhifeng, L., Yongsheng, Z., Peihua, G.: Sensitivity-based multidisciplinary optimal design of a hydrostatic rotary table with Particle swarm optimization. J. Mech. Eng. 61(7–8), 432–447 (2015) 8. Marko, H., Simon, K., Tomaz, I., Matej, P., Joze, B., Miran, B.: Turning parameters optimization using Particle swarm optimization. Ann. DAAAM Proc. 24(1), 670–677 (2013) 9. Venkata Rao, R.: JAYA: a simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int. J. Ind. Eng. Comput. 7(1), 19–34 (2016) 10. Kiran, A.R., Kumar, P.V.: DC motor speed control using PID controller tuned by a JAYA optimization algorithm. In: 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), pp. 983–987 (2017) 11. Nath, S.C., Kumar, G.A., Deepak, K., Paulson, S.: Fuzzy C-means based model simplification using JAYA optimization algorithm. In: 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), pp. 881–885 (2018) 12. Barakat, A.F., El-Sehiemy, R.A., Elsayd, M.I., Osman, E.: An enhanced JAYA optimization algorithm (EJOA) for solving multi-objective ORPD problem. In: 2019 International Conference on Innovative Trends in Computer Engineering (ITCE), pp. 479–484 (2019) 13. Huan, T.T., Anh, H.P.H.: Optimal biped walking pattern generator with preset hip-shift using JAYA optimization algorithm. In: 2019 International Symposium on Electrical and Electronics Engineering (ISEE), pp. 275–280 (2019) 14. Yao, X., Liu, Y., Lin, G.: Evolutionary programming made faster. IEEE Trans. Evol. Comput. 3, 82–102 (1999) 15. Mirjalili, S., Zaiton, S.: A new hybrid PSOGSA algorithm for function optimization. In: ICCIA 2010 International Conference on Computer and Information Application, pp. 374–377 (2010)

Characterisation of 17-7PH Steel of Modified State RH 950 with Modified Chemical Composition 2 ´ Belma Faki´c1(B) and Diana Cubela 1 Institute “Kemal Kapetanovi´c” of Zenica, University of Zenica,

72000 Zenica, Bosnia and Herzegovina [email protected] 2 Metallurgical and Technological Faculty, University of Zenica, 72000 Zenica, Bosnia and Herzegovina

Abstract. Precipitation hardening at low temperature is a heat treatment in which the material is hardened by the precipitation of secondary phases from a solid solution. The first degree of hardening of steel 17-7PH is the transformation of austenite into martensite. Cryogenic heat treatment of this material offers the possibility of obtaining a suitable combination of martensite and austenite. The microstructural constituents of martensite, austenite and delta ferrite were determined using an optical light microscope and the Feritoscope. The mechanical properties were determined at room and high temperature. Fire resistance testing of 17-7PH steel with high chromium and nickel content to show that it retains its high strength at high temperatures. Keywords: PH steel · microstructure · hardness · mechanical properties · fire resistance · heat treatment

1 Introduction Precipitation-hardened (PH) stainless steels are iron-chromium-nickel alloys with the addition of one or more precipitation-hardening elements such as aluminum, titanium, copper, niobium, and molybdenum. PH Steels were developed as a material for the aerospace industry, but are now gaining commercial importance because they are inexpensive and available in a wide range of products (bars, wires, forgings, plates, strips). These steels are characterized by a unique combination of high strength, toughness, good corrosion resistance and easy plastic processing [1].

2 A Brief Review of the History of Stainless Steel In the period from 1900 to 1915 appeared the first steels, whose corrosion resistance was significantly improved. The appearance of the first stainless steel was the result of the effort of several people, which actually began in 1821 [1, 2]. In that year, the Frenchman © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 69–77, 2023. https://doi.org/10.1007/978-3-031-31066-9_8

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Berthier discovered that iron alloyed with chromium was resistant to the action of some acids. Subsequently, researchers worked to discover the influence of chromium in the iron matrix, but they used alloys with lower chromium content. In 1872, Woods and Clark produced an alloy with 30–35% Cr and 1.5–2% W. Frenchman Brustlein showed the importance of carbon content in chromium alloys. The carbon content of stainless steel should be less than 0.15%. In the following years, many researchers had problems finding the optimum chromium-iron ratio due to the low carbon content, which was overcome by the discovery of low-carbon ferrochromium. In 1904, Leon Guillet published research on alloys now known as 410, 420, 442, 446, and 440-C. Two years later, he published a detailed study of the iron-nickel-chromium alloy underlying 300 series stainless steel. In England, Giesen published a study of 300 series chromium-nickel stainless steels in 1909, and Portevin published a study of the 430 series. In Germany, Monnartz and Borchers discovered a relationship between the minimum chromium content (10.5%) and the corrosion resistance of steel, as well as the importance of a low carbon content and the role of molybdenum in increasing the corrosion resistance of chlorides [2]. Independently, many researchers subsequently worked to develop materials with better properties than those previously known. In England, it was H. Brearley. In Germany, B. Strauss produced the first austenitic stainless steel, while in the USA, F.M. Becket developed the first refractory stainless steel [3]. According to the literature, the inventor of stainless steel is an Englishman, Harry Brearley. In Sheffield, England, H. Brearley was the first to recognize the exceptional corrosion resistance of chromium-containing iron alloys and used this property to produce cutlery from an alloy containing 0.24% C and 12.8% Cr [1]. Brearly’s discovery, which included heat treatment to strengthen the alloy, was an accident. H. Brearley was trying to prevent corrosion and fouling in gun barrels and alloyed iron with chromium. While etching metallographic specimens, he found that some of them could not be etched in the nitric acid solution he used. He called these ferritic Fe-Cr alloys “stainless” steel. Later, this name was transferred to austenitic iron-chromium-nickel alloys, which were developed in Germany at the same time [1]. The first precipitation hardened stainless steel was martensitic steel developed by US Steel in 1945 under the name Stainless W (AISI 635) [1, 4]. This type of stainless steel was installed in submarines used in World War II, while in the 1960s precipitation hardened stainless steel was used in landing gears of aircraft. It contained a large amount of nickel, which made it too expensive, so it was not widely used, although it had excellent mechanical properties.

3 Classification of PH Steel Precipitation-hardened stainless steels are classified into three groups [1, 5]: – martensitic – 17-4 PH (AISI 630), 15-5 PH, PH 13-8Mo, – austenitic - A-286 (AISI 600), 17-10 PHNM, – semi-austenitic - 17-7PH (AISI 631), PH 15-7Mo, PH 14-8.

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Martensitic PH steels - after solution annealing the microstructure is predominantly martensitic with the possible presence of some retained austenite. During precipitation annealing at temperatures from 450 to 650 °C, precipitation of intermetallic phases occurs. The corrosion resistance of martensitic PH steels is comparable to that of austenitic steels in most media. Martensitic PH steels have greater flexibility in shaping the final products and exhibit high strength, ductility, corrosion resistance, and toughness [1, 5, 6]. Austenitic PH steels - precipitation occurs from stable austenite in both the annealed and aged states as they retain austenite as the matrix phase at room temperature. The temperature of onset of martensitic transformation is so low in these steels that it is never reached and the contribution of martensitic transformation to the overall hardening of this group of steels is non-existent. A higher nickel content (≥25%) and the addition of the elements Ti, Al, Cu and P, which are involved in the formation of precipitates, contribute to increased hardening [1, 5, 6]. Semi-austenitic steels PH - precipitation occurs from indirectly formed martensite. These steels are austenitic in the solution-annealed condition. They can contain between 5 and 20% delta ferrite [1, 5, 7]. Semi-austenitic steels are ductile in the solution-annealed condition and are easily deformed. The content of alphagenic and gammagenic elements must be carefully balanced to obtain the desired properties of these steels. Cooling from the solution annealing temperature must be fast enough to avoid grain coarsening [1, 5, 6]. 3.1 Mechanism of Precipitation Hardening The possibilities of hardening alloys by solid solution hardening, deformation hardening and grain reduction are limited. A higher degree of hardening is additionally achieved by precipitation hardening, which is based on the decomposition of the supersaturated solid solution into a mechanical mixture of two phases, one of which, the secondary phase, is finely dispersed in the other, the so-called matrix phase. Numerous researchers, including Mott, Nabarro, Orowan, Kelly, and Nicholson, worked in the middle of the last century to understand the mechanism of precipitation hardening by studying the microstructure of aged alloys using a transmission electron microscope [1, 8] Precipitation hardening affects ductility, notched impact strength, and susceptibility to corrosion-induced cracking. For precipitation hardening to be possible, there must first be a partial solubility of the dissolved components in the solid state that decreases with temperature. If the solubility of the components decreases with decreasing temperature, it is possible to cool the alloy rapidly from the single-phase region to suppress phase transformation and obtain a supersaturated solid solution that is reheated to temperatures at which both phases are present, allowing precipitation of other phases. The degree of hardening depends on the type of precipitation, which can be controlled by choosing the appropriate decomposition temperature of the supersaturated solid solution. The principle of all hardening mechanisms is to block the movement of dislocations, so this principle is the basis of precipitation hardening. The secondary phase, precipitates, act as dislocation blockers. The more efficient they are at this, the higher the degree of hardening. The degree of precipitation hardening depends on the following factors: type of particles, degree of dispersion, shape and strength of the particles [9, 10].

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3.2 Precipitation Hardening (Aging) Aging is a relatively low temperature heat treatment that strengthens the material by precipitation of secondary phases from a saturated solid solution [1]. The first degree of hardening of steel 17-7PH is the transformation of austenite to martensite. At solution annealing temperatures, the steel is in the austenitic range. The solubility of carbon iniron is much higher than in-iron. During rapid cooling, the phase is transformed into the phase. Due to the high cooling rate, the carbon is unable to leave the bcc lattice phase, causing the fcc lattice to deform into the volume centered tetragonal lattice. This tetragonal phase is martensite, a saturated solid solution of carbon in-Fe, which has higher hardness and strength than austenite. The steel 17-7PH has a low carbon content, so the martensite formed by hardening is soft. Hardening of martensite is the result of the following effects: very pronounced solution hardening, high dislocation density, fewer slip systems in the volume-centered tetragonal lattice compared to the bcc lattice, the disintegration of martensitic plates and formation of suitable precipitates. 3.3 Cryogenic Heat Treatment - Condition RH950 Austenite conditioning is carried out at a temperature of 955 °C for 10 min. The result of this treatment is an increase in Ms temperature close to room temperature. Thus, the material conditioned at 955 °C retains the austenitic microstructure when cooled to room temperature, so it must be transformed by cooling to −75 °C. If the conditioning temperature is higher than 955 °C, the martensitic transformation is suppressed, so cooling to −75 °C does not result in the complete transformation to martensite. Transformation - after conditioning to 955 °C, cooling to −75 °C and holding at this temperature for eight hours, austenite is transformed to martensite. This state is marked R-100. Most of the transformation takes place during cooling to −75 °C and during the first hour at this temperature. The aging temperature for the R-100 state is 510 °C for one hour. At higher or lower aging temperatures, the result is lower strength, but at higher aging temperatures, better ductility is obtained [1].

4 Experimental Part The standardized chemical composition of stainless steel 17-7PH and the modified chemical composition of an experimental batch are given in Table 1. 4.1 Heat Treatment Heat treatment of 16 mm bars was carried out in semi-industrial furnace and automatic laboratory furnace in Heat Treatment Department of “Kemal Kapetanovi´c” Institute in Zenica [1, 6, 11].

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Table 1. Chemical composition Batch

Standard Chemical composition, mas % C, max

Mn, max

Si, max

P, max

S, max

Cr

Ni

Al

BAS EN 10088-5

0,09

1,0

0,7

0,040

0,015

16,0-18,0

6,5-7,8

0,7-1,5

V1774

0,04

0,52

0,53

0,009

0,023

14,5

7,8

1,53

4.1.1 Solution Annealing Rolled bars of 16 mm were solution annealed in a furnace without a protective atmosphere: - heating to a temperature of 1050 °C for 115 min, held at a temperature of 1050 °C for 30 min and cooling in the air. The diagram of solution annealing is shown in Fig. 1.

Fig. 1. Schematic of solution annealing of steel 17-7PH [1, 6]

4.1.2 Modified Condition RH950 - Precipitation Hardening Heating to 955 C for 90 min, holding at this temperature for 10 min (austenite conditioning), cooling in air to room temperature, within one hour start of cooling to − 50 °C in dry ice and holding for 8 h (transformation of austenite to martensite), followed by heating to room temperature and heating to 510 °C for 45 min and holding at this temperature for 60 min (precipitation hardening) and cooling in air. The diagrams of the heat treatment performed can be found in Fig. 2 [1, 6].

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Fig. 2. Diagram of precipitation hardening steel 17-7PH [1, 6]

4.2 Metallographic Analysis Metallographic analysis of the samples in the modified RH950 condition showed the microstructure of martensite and austenite and the presence of a smaller amount of delta ferrite. The appearance of the microstructure of samples in the RH950 condition for melt V1774 are shown in Fig. 3.

Kalling

x 150 Kalling

x750 Kalling

a)

b)

x 1500 c)

Fig. 3. Melt V1774, a) and b) longitudinal to the rolling direction; c) transverse to the rolling direction

The results of the measurement of the amount of phases present are shown in Table 2. Table 2. Amount of phases present [1] Sample

Solution annealing Light microscope

V1774

RH950 Ferritescope

Light microscope

Ferritescope

M

δ

A

M+δ

A

M

δ

A

M+δ

A

69

5

26

76,6

23,4

87

5

8

85,5

14,5

Characterisation of 17-7PH Steel of Modified State RH 950

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4.3 Mechanical Tests The literature values of the mechanical properties for the solution annealed condition and RH950 condition and the results of tests of the mechanical properties at room and elevated temperature for these conditions can be found in Table 3. Table 3. Results of mechanical testing. Batch

ARMCO 17-7 PH solution annealing [13]

Literature Rm [N/mm2 ]

Rp0,2 [N/mm2 ]

A [%]

Room temp.

425 °C

Room temp.

425 °C

Room temp.

425 °C

—

—

—

—

—

≤1034

V1774 – solution 988 annealing [1] Metals handbook [4] AK Steel bulletin [12] for condition RH950

Hardness HV 10 ≤258*

848 —

14,5 —

336 —

1378 -

1103

1206 -

945

10 -

12

438 -

V1774 1636 modified condition RH950 [1]

1126

1555

1039

8,0

15,5

535

* converted Brinell hardness value to Vickers value according to standard tables [1]

4.4 Testing of Fire Resistance Fire resistance testing was performed in accordance with ASTM G54-84 (R 1996) [14]. The specimens were ground and the diameter and height were measured with a sliding scale. After degreasing in acetone, the mass of the specimens was measured with an accuracy of ±0.1 mg. The samples were placed in a Kohler laboratory furnace heated to a temperature of 600 °C. After the samples were held at a temperature of 600 °C for cycle durations of 24 h, 48 h, and 72 h, they were removed from the oven, cooled to room temperature in air, and weighed. The total depth of oxidation attack for melt V1774 after 72 h at 600 °C is 0.15 mm [1, 15]. Metallographic analysis of the surface of the oxide layer after the fire resistance test are shown at Fig. 4.

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a) 24h

b) 48 h

c) 72h

Fig. 4. Metallographic analysis of the surface of the oxide layer after the fire resistance test, melt V1774, modified condition RH950, Kalling + Villela [1, 15]

5 Conclusion Tensile strength for melt V1774, in solution annealed state are in accordance with literature values (less than 1034 N/mm2 ), but hardness is higher then prescribe in literature data (336 is higher than 258HV10), which is related to high content of martensite in this melt after solution annealing (about 70% martensite). Mechanical properties at elevated temperature (450 °C) in modified condition RH950 are in accordance with literature data. Microstructure tests of stainless steel PH17-7 with modified chemical composition in modified condition RH950 shows martensite and austenite and the presence of a smaller amount of delta ferrite. The total depth of oxidation attack is very small, just 0,15 mm after 72 h at 600 °C, and showed very good oxidation stability properties of the tested material.

References 1. Faki´c, B.: A Modification of Chromium, Nickel, and Aluminum Content in Precipitation Hardening Steel 17-7PH Intended for the Production of Automotive Engine Components. Ph.D., University of Zenica, December 2015 (2015) 2. http://www.ssina.com/overview/history.html. Accessed May 2013 3. Handbook of stainless steel - Outokumpu Oyj, Finland 4. Metals Handbook: Properties and Selection: Iron, Steels and High-Performance, 10th edn, vol. 1. ASM American Society for Metals (1990) 5. Lai, J.K.L., et al.: Stainless Steels: An Introduction and Their Recent Developments. http:// books.google.ba. Accessed July 2012 ´ 6. Faki´c, B., Cubela, D.: Metallographic analysis of precipitation-hardened state RH950 steel 17-7PH of modified chemical composition. In: International Conference on Applied Sciences, ICAS 2022, Banja Luka (2022) 7. Novosel, M., Krumes, D.: Posebni cˇ elici, Slavonski Brod (1998) 8. Dislocations and Precipitation Hardening. dissertations.ub.rug.nl/FILES/faculties.pdf. Accessed Mar 2013 9. Drobnjak, Ð.: Fiziˇcka metalurgija, Fizika cˇ vrsto´ce plastiˇcnosti 1, Tehnološko-metalurški fakultet, Beograd (1981) 10. Decker, R.F.: Alloy design, using second phases. Metall. Trans. 4, 2495–2518 (1973) ´ Buri´c, A.: Microstructural and mechanical properties of modified pre11. Faki´c, B., Diana, C, cipitation hardening steel 17-7PH after modification heat treatment. Int. J. Adv. Res. (IJAR) 8, 865–872 (2020)

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12. http://www.aksteel.com/pdf/markets_products/stainless/precipitation/17-7_ph_data_bul letin.pdf. Accessed Jan 2013 13. ARMCO 17-7 PH STAINLESS STEEL. AK Steel International. https://www.aksteel.nl. Accessed Dec 2022 14. Standard ASTM G54-84 (Reapproved): Standard Practice for Simple Static Oxidation Testing ´ Research of oxidation properties of steel 17-7PH. In: 2nd 15. Faki´c, B., Milenko, R., Diana, C.: International Conference “NEW TECHNOLOGIES NT-2015” Development and Application (2015)

Gauss-Based Honey Badger Algorithm for Step-Cone Pulley Optimization Problem - 1(B) , Mijodrag Miloševi´c2(B) , Dejan Luki´c2(B) , Aco Anti´c2(B) , Mi´ca Ðurdev - c1(B) Borivoj Novakovi´c1(B) , and Luka Ðordevi´ 1 Technical Faculty “Mihajlo Pupin” Zrenjanin, University of Novi Sad, Zrenjanin, Serbia

{mica.djurdjev,borivoj.novakovic,luka.djordjevic}@tfzr.rs 2 Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia {mido,lukicd,antica}@uns.ac.rs

Abstract. This study considers the application of the improved Gauss-based Honey badger algorithm (Gauss-based HBA) to deal with the popular constrained optimization problem regarding the minimization of the weight of the step-cone pulley. The concept of the proposed swarm intelligence algorithm is described, and the mathematical formulation is detailed. Afterward, the step-cone pulley optimization is presented graphically with the mathematical model regarding objective function and eleven constraints. The comparative study was performed to validate the performances of the Gauss-based HBA that proved to be efficient for this optimization problem. Keywords: honey badger algorithm · optimization · step-cone pulley problem

1 Introduction A subset of artificial intelligence called swarm intelligence considers the design of intelligent algorithms that draw inspiration from the group behavior of social creatures like ants, bees, and birds. These algorithms are used to address problems involving many interacting agents, such as control, pattern recognition, and optimization. Typically, these algorithms involve a population of search agents that cooperate to accomplish a common goal by sharing information and modifying their behavior in response to the actions of other agents. They are incorporated into many disciplines, such as robotics, computer science, mathematics, economics, and biology [1, 2]. Each swarm intelligence algorithm shares a common goal, which is to achieve a balance between exploring the search space to discover new, potentially fitter solutions and utilizing the current best solution in order to enhance and improve it. This is popular in the scientific community as the trade-off between exploration and exploitation. Exploration in optimization is the act of finding new solutions in new areas of the search space, whereas exploitation is the process of making improvements to the best solution that has already been found. In optimization algorithms, it’s crucial to establish a balance between exploration and exploitation because too much exploitation may result in low convergence, while too much exploration may result in a premature convergence to local © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 78–85, 2023. https://doi.org/10.1007/978-3-031-31066-9_9

Gauss-Based Honey Badger Algorithm for Step-Cone Pulley Optimization Problem

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optima [3]. The characteristics of the search space and the type of optimization problem determine the optimal balance between exploration and exploitation. In this study, an improved novel swarm intelligence algorithm is incorporated to solve the well-known step-cone pulley optimization problem. The concept of the Honey Badger Algorithm (HBA) is described, and then the Gauss chaotic map is introduced as the main technique used to improve the search capabilities of the HBA. The flowchart of the Gauss-based HBA is presented graphically. Afterward, the step-cone pulley optimization problem is presented in detail. The optimization results are then obtained and represented in tables. The proposed algorithm is compared to other swarm intelligence algorithms in order to validate its performance for the step-cone pulley problem. Relevant literature sources are listed in the last chapter.

2 Gauss-Based Honey Badger Algorithm The Honey Badger Algorithm (HBA) is a swarm intelligence algorithm belonging to the class of stochastic algorithms that was developed in response to honey badgers’ foraging habits [4]. Its purpose is to find high-quality solutions by achieving the balance between exploitation and exploration of the search, as mentioned in the previous section. The concept of HBA is based on two different strategies honey badgers use when finding food. One is known as “the digging stage,” in which a honey badger uses its smelling abilities to find its prey before roaming around and selecting a location to dig a hole before finally capturing it. The second is known as “the honey stage”, where a honey badger follows a honeyguide bird that helps the badger find the beehive. The mathematical model of HBA is described in detail in [4]. Here we propose the improved version of the HBA, called the Gauss-based HBA, a variant that was a part of the hybrid approach implemented in [5]. Due to their capacity to produce random number sequences with intricate and unpredictable behavior, chaotic maps, including Gauss chaotic maps, have been utilized as a tool for optimization techniques. These chaotic maps can be used to produce random solutions to optimization problems and offer a way to avoid entrapment in local optima and direct the search toward the global optima. It has been demonstrated that Gauss chaotic maps, based on the combination of Gaussian and mouse functions, are efficient in a variety of optimization problems. In terms of convergence speed and solution quality, the use of chaotic maps in optimization algorithms is an important area of research. Gauss chaotic map is presented in Fig. 1. Here we adopted the Gauss chaotic map to improve the convergence of the classical HBA toward the global optima. The mathematical formulation of the Gauss-based HBA is described below. The population of honey badger positions is formed in the initial stage of the HBA when the input parameters for HBA are established, and the fitness of each of these positions is assessed. The best position in the population of honey badgers is the position of the prey, Xp, and its fitness is Fp.

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Fig. 1. Visualization of the Gauss chaotic map [6]

Honey badgers move in the search space according to the Inverse-square law. They move faster when the smell of the prey is more intense and slower if less. The Inversesquare law equation is used to define the smell intensity: Ii = chaositer ·

S 4π di2

(1)

where chaositer represents a random value obtained from the Gauss map in iteration iter, S is the concentration strength, and d i is the distance from the prey. These two values can be defined using these equations: S = (Xi − Xi+1 )2

(2)

di = Xp − Xi

(3)

where X p is the position of the prey, X i is the current position of the i-th honey badger, and X i+1 is the current position of the next honey badger. In the “digging stage,” honey badgers update their position using Cardioid motion that can be defined using this equation: Xnew = Xp + F · β · Ii · Xp + F · r1 · α · di · |cos(2π r2 ) · [1 − cos(2π r3 )]|

(4)

where X new is the updated position of a honey badger, and r 1 , r 2 , and r 3 are random numbers between 0 and 1. F is the obstacle a honey badger can find on his way toward the prey:  1 if chaositer ≤ 0.5 F= (5) −1 else where chaositer is also a random value obtained from the Gauss map in iteration iter. The density factor α from the Eq. (4) is used to positively affect the transition from global to local search: 

α =C·e

−iter itermax



(6)

Gauss-Based Honey Badger Algorithm for Step-Cone Pulley Optimization Problem

81

According to the above given mathematical expressions, two important parameters that need to be tuned when implementing HBA are constants C and β. The default values for these two constants are 6 and 2, respectively. The second stage, “the honey stage”, assumes that a honey badger updates its position according to the help from the honeyguide bird that leads him to a beehive. Here is the equation for this stage of the HBA: Xnew = Xp + F · r4 · α · di

(7)

where r 4 is a random number from interval [0, 1].

3 Step Cone Pulley Problem The optimization of step-cone pulleys with the objective of minimizing weight is a complex problem that involves finding the optimal combination of five design variables: four diameters of each step (d1 , d2 , d3 , and d4 ) and the width of the pulley (w). The diameters of the steps and the width of the pulley directly affect the weight of the pulley, as well as other performance parameters such as mechanical strength, efficiency, and durability. This problem contains eleven non-linear constraints, three equality constraints, and eight inequality constraints. The step pulley transmitted at least 0.75 hp, with an input speed of 350 rpm and output speeds of 750, 450, 250, and 150 rpm. The graphical representation of the step-cone pulley optimization problem is given in Fig. 2. Mathematical formulation of this problem is given below [7, 8]. Design variables: x = {d1 , d2 , d3 , d4 , w}

(8)

Objective function:    2   2  ⎤ N1 2 1+ N + d2 1 + NN2 ⎢ ⎥ π ⎢   Minimize : f (x) = ρw⎣  2   2  ⎥ ⎦ 4 + d42 1 + NN4 +d32 1 + NN3 ⎡

d12

(9)

Subject to: Design constraints (equalities): h1 (x) = c1 − c2 = 0

(10)

h2 (x) = c1 − c3 = 0

(11)

h3 (x) = c1 − c4 = 0

(12)

Design constraints (inequalities): g1,2,3,4 (x) = Ri − 2 ≥ 0; i = 1, . . . , 4

(13)

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g5,6,7,8 (x) = Pi − (0.75 × 745.6998) ≥ 0; i = 1, . . . , 4

(14)

where: ci is the belt length required to obtain speed Ni and can be calculated using the following equation:  2

d 2 Ni − 1 i N di π Ni ci = +1 + + 2a; i = 1, . . . , 4 (15) 4 N 4a Ri is the tension ratio that can be calculated by: 

   −1 di Ni −1 ; i = 1, . . . , 4 Ri = exp μ π − 2 sin 2a N

(16)

Pi is the power transmitted to each step; the adopted unit for power is W (watt), meaning that hp units (horsepower) in Eq. (14) have to be converted. The following equation calculates the transmitted power Pi :    



di Ni di π Ni Pi = stw 1 − exp −μ π − 2 sin−1 −1 × ; i = 1, . . . , 4 2a N 60 (17) ρ = 7200

kg ; μ = 0.35; a = 3 m; t = 8 mm; s = 1.75 MPa m3

(18)

and bounds: 40 mm ≤ di ≤ 100 mm; i = 1, . . . , 4

Fig. 2. Step-cone pulley optimization problem [8]

(19)

Gauss-Based Honey Badger Algorithm for Step-Cone Pulley Optimization Problem

16 mm ≤ w ≤ 100 mm; i = 1, . . . , 4

83

(20)

4 Results and Discussion The attempt to solve the step-cone pulley optimization problem using the proposed Gauss-based HBA was successful. Validation of the obtained results is made by comparing the performances of several swarm intelligence algorithms. Here, the adopted algorithms are Particle swarm optimization (PSO), Grey Wolf Optimizer (GWO), Bat Algorithm (BA), Artificial Bee Colony (ABC), and Seagull Optimization Algorithm (SOA). Algorithms are coded in the Matlab programming environment on the computer with Windows 10 operating system and modern configurations. After performing a manual sensitivity analysis of HBA parameters β and C, the conclusion is that values 6 and 2, respectively, are the best choice for the considered optimization problem. As far as other algorithms are concerned, default parameter settings are adopted. The number of search agents and the maximal number of iterations are the same for each search algorithm, 30 and 1000, respectively. It is worth mentioning that the information about the tolerance for equality constraints is mostly avoided in the literature sources. Here, the adopted tolerance is 5 regarding these constraints. Without defining the appropriate tolerance, some algorithms are unable to find good solutions. Table 1 shows the comparative results of performance measures regarding the swarm intelligence algorithms considered in this study. According to the results, Gauss-based HBA showed better performances than most of the algorithms. Only GWO showed more consistent results assuming the smallest deviation, mean fitness, and worst fitness values. Gauss-based HBA, like PSO, found the best results in the study. The best solutions that match the best fitness values are presented in Table 2. Future research studies can be directed to further improve the efficiency of HBA by considering different chaotic maps, as well as other ways of improving their capabilities to avoid local optima. Table 1. Comparison of statistical values by the applied swarm intelligence algorithms on the step-cone pulley optimization problem Performance measures

Swarm intelligence algorithms PSO

SOA

GWO

BA

ABC

Gauss-based HBA

Mean fitness

17.0041

16.4242

16.1877

18.73828

19.4427

16.2693

Worst fitness

18.67

18.1024

16.2262

23.6367

24.2730

16.5545

Best Fitness

16.1776

16.2336

16.1849

16.7476

17.0184

16.1776

St. dev.

1.0177

0.26318

0.0060369

1.595426

1.757412

0.12527

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Table 2. Best solutions obtained by the applied SI algorithms on the step-cone pulley optimization problem Design variables

Swarm intelligence algorithms PSO

SOA

GWO

BA

ABC

Gauss-based HBA

d1

40

40

40

40.0007

40

40

d2

53.6504

53.6878

53.6574

55.1803

53.6889

53.6504

d3

71.5283

71.5978

71.5406

73.0928

73.7614

71.5283

d4

90.2071

89.7294

90.1773

87.9183

90.1005

90.2071

W

84.2858

84.7676

84.3278

86.4879

86.7962

84.2858

Best Fitness

16.1776

16.2336

16.1849

16.7476

17.0184

16.1776

5 Conclusion This paper proposed a novel Gauss-based HBA to solve the step-cone pulley optimization problem. The relevant information about swarm intelligence algorithms is first given. Exploration and exploitation are emphasized as the main components of SI algorithms. The main concept of HBA with equations is presented, and Gauss chaotic map is given as an improvement technique. The step-cone pulley problem is described, and the mathematical model is presented. To validate Gauss-based HBA, a comparative study is performed, and the performance measures and obtained solutions are compared among different SI algorithms. Gauss-based HBA performed very well for the step-cone pulley optimization problem. Acknowledgments. This paper is part of a study in the project “Collaborative systems in the digital industrial environment” No. 142-451-2671/2021-01/02, supported by the Provincial Secretariat for Higher Education and Scientific Research of the Autonomous Province of Vojvodina and “Innovative scientific and artistic research from the FTS domain”, No. 451-03-68/2020-14/200156, supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia.

References 1. Blum, C., Li, X.: Swarm intelligence in optimization. In: Blum, C., Merkle, D. (eds.) Swarm Intelligence. NCS, pp. 43–85. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-54074089-6_2 - M., Anti´c, A., Borojevi´c, S.: An overview of genetic 2. Miloševi´c, M., Luki´c, D., Ðurdev, algorithms for job shop scheduling problems. J. Prod. Eng. 18(2), 11–15 (2015). ISSN 1821-4932 3. Malik, H., Iqbal, A., Joshi, P., Agrawal, S., Bakhsh, F.I.: Metaheuristic and Evolutionary Computation: Algorithms and Applications. Studies in Computational Intelligence. Springer, Singapore (2021). https://doi.org/10.1007/978-981-15-7571-6

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4. Hashim, F.A., Houssein, E.H., Hussain, K., Mabrouk, M.S., Al-Atabany, W.: Honey Badger Algorithm: new metaheuristic algorithm for solving optimization problems. Math. Comput. Simul. 192, 84–110 (2022). https://doi.org/10.1016/j.matcom.2021.08.013 5. Düzenl˙i, T., Funda Kutlu, O., Salih Berkan, A.: Improved honey badger algorithms for parameter extraction in photovoltaic models. Optik – Int. J. Light Electron Opt. 268, 1–27 (2022) 6. Saremi, S., Mirjalili, S., Lewis, A.: Biogeography-based optimisation with chaos. Neural Comput. Appl. 25(5), 1077–1097 (2014). https://doi.org/10.1007/s00521-014-1597-x 7. Kumar, A., Wu, G., Ali, M.Z., Mallipeddi, R., Suganthan, P.N., Das, S.: A test-suite of nonconvex constrained optimization problems from the real-world and some baseline results. Swarm Evol. Comput. 56, 1–47 (2020). https://doi.org/10.1016/j.swevo.2020.100693 8. Yildiz, A.R., Abderazek, H., Mirjalili, S.: A comparative study of recent non-traditional methods for mechanical design optimization. Arch. Comput. Methods Eng. 27, 1031–1048 (2020). https://doi.org/10.1007/s11831-019-09343-x

Comparison of the Main Parameters of the Steel and Carbon-Fiber-Reinforced Plastic Band Traction Units for Long-Stroke Oil Well Pumps Bogdan Kopei, Ihor Kopei, Volodymyr Kopei, Oleh Onysko(B) , and Vasyl Mykhailiuk Ivano-Frankivsk National Technical University of Oil and Gas, 15 Karpatska st., Ivano-Frankivsk 76019, Ukraine [email protected]

Abstract. Sucker rod well pump installations are the most common for the mechanized method of oil production. They use a beam-balanced pumping unit as a surface drive, and a sucker rod string is a flexible link connecting the drive with a plunger well pump. The disadvantage of a beam-balanced pumping unit is the cyclic nature of operation with a short cycle period and a large asymmetry of loads. In this regard, the use of long-stroke pumping units with a band traction unit is promising. The problem of increasing the inter-repair period of a long-stroke pumping unit is associated with the creation of a long-sized, high-strength and durable band traction unit. The authors proposed to use carbon-fiber-reinforced plastic instead of steel. Carbon-fiber plastic is characterized by high strength, low density and corrosion resistance. The optimal values of the geometric parameters of the carbon-fiber band traction unit are determined and compared with the steel one: the thickness of the band is 2–3 mm (4–5 mm for steel); the width of the band depends on the diameter of the tubing and is 35–90 mm; band length is 1000–3000 m (1500–4500 m for steel). The carbon-fiber band traction unit of a long-stroke pumping unit has a significant margin of endurance in comparison with steel bands. Keywords: oil production · long-stroke pumping unit · band traction unit · carbon fiber · endurance limit

1 Introduction Equipment for artificial oil production is divided by the type of ground drive into: balanced, unbalanced, screw, chain, linear, hydraulic and long-stroke. The most common mechanized method of oil production is the use of rod deep pumping units (RDPU). About 2/3 of all production wells in the world use rod deep pumps (RDP), and many of them are driven by beam-balanced rocking machines, which are a four-link crank-androd mechanism. One of their main disadvantages is the cyclic nature of operation with a short cycle period and large asymmetry of loads with a high upper limit [1–3]. It is difficult to achieve long-strokes and low-impact cycles [4]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 86–97, 2023. https://doi.org/10.1007/978-3-031-31066-9_10

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At the moment, the main areas of work on increasing the efficiency of oil production processes with the use of RDP in the fields are [5]: improvement of equipment selection methods taking into account the conditions of a specific well, its mode of operation, as well as maintaining optimal operating conditions during the entire inter-repair period; development of new and improvement of existing equipment; development and application of special designs of pumps for the extraction of oil with a high content of sand, resins and paraffin; application of new technological means and methods for the operation of the RDP in difficult geological conditions; development and implementation of measures for the efficient use and saving of electricity during oil production RDP, etc. The world’s leading manufacturers of equipment for the oil industry constantly set themselves the task of creating and implementing new designs that replace the classic balanced pumping units [4, 6–9]. Among them are mechanical [10], chain drives [11] “Rotaflex” [12–14], hydraulic [6, 7], based on permanent magnet synchronous motor [15], “Qing You” long stroke [16] or units with variable diameter wheel [17]. The economic efficiency of the well lies in minimizing downtime and productivity losses. A set of measures to improve the use of the well stock, including the introduction of high-reliability downhole pumps, the use of high-strength sucker rods and new types of rocking machines, and improving the quality of repair work, does not always give the desired result.

2 Main Content 2.1 Analysis of Modern Research and Publications Compared to beam-balanced pumping units, the following advantages of long-stroke pumping units (LSPU) have been proven: higher rod pump efficiency and increased production [2, 6, 13, 18–26], reducing the number of operating cycles while maintaining performance, reducing dynamic loads without reducing the pressure, increases rod pump, sucker rod and pumping unit life [2–4, 6, 13, 18–21], there is no compression of the rod string, the rod, tube and pump wear is reduced [2, 13, 22, 23, 25], lower investment and operating cost, more unlimited adjustment of stroke and stroke frequency, simplified transmission links [3, 25], the possibility of applying effective control systems [24, 27], advantages when operating in difficult conditions such as deep well oil, high water cut oil and heavy oil [6, 18, 28], elimination of gas problems [13, 23]. Greater efficiency can be achieved by using fiberglass rods [29]. One of the promising directions is the use of LSPU with band traction unit (BTU), which includes a band mechanism, a self-sealing plunger and a working cylinder made of tubing column (tubes). Figure 1 shows the scheme of the LSPU with the BTU. The principle of its operation consists in the fact that the ground drive winds up the band on a drum and winds out it into the well with the given interval of the movement of the plunger [3, 19, 30]. The downward movement of the plunger is due to the load attached to it. Switching from upstroke to downstroke is done by reversing the motor [3]. The length of the plunger stroke is regulated by the location of the limit switches on the screw of the reversing mechanism, and the performance is regulated by the creation of appropriate pauses in the cycle at the end of the downstroke [30].

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The advantage of LSPU with the BTU in comparison with others is the easier working conditions of the band traction body and ultra long stroke [19, 21]. The band bends only on the drum, since the point of convergence is stationary. In this case, there are practically no contact stresses in the band. The stroke length of the plunger is commensurate with the depth of its descent and reaches hundreds of meters [3, 30]. When the LSPU is running, there are no oscillations in the BTU [15, 18–20]. The maximum load on a service station with a mechanical drive is reached 2–2.5 s after its start-up [31]. The LSPU with a mechanical drive has one upward movement speed of the plunger, and it also provides for smooth adjustment of the length of the plunger stroke by changing the position of the limit switches.

1 – suction valve; 2 – plunger; 3 – discharge valve; 4 – traction body; 5 – pump cylinder (tubing column); 6 – oil seal; 7 – emergency switch; 8 – guide roller; 9 – reducer; 10 – reversal mechanism; 11 – limit switches; 12 – brake; 13 – V-belt transmission; 14 – electric motor; 15 – drum; 16 – control station Fig. 1. Scheme of a long-stroke pumping unit with a band traction unit

LSPU work in a wide range of pump volumetric flow rate - from 2 to 82 m3 /day. With small pump flow rates (less than 5 m3 /day), the specific energy consumption for lifting 1 ton of liquid increases sharply and the pump delivery ratio decreases [19]. The specific energy consumption increases with a decrease in the liquid level in the well and with the deposition of paraffin and resins in the lifting pipes. LSPU provides a sufficiently high pump delivery ratio - from 0.55 to 0.79 [15]. The average value of specific energy consumption is low (6.4–7 kWh/t), when lifting liquid from dynamic levels from 630 to 850 m. In the same interval of the liquid level in the well, for lifting 1 ton of liquid with the help of a balanced pumping unit, the specific power consumption increases to 7.64 kW · h/t [31].

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2.2 Statement of the Task and the Purpose of the Work For the production of BTU, steel 30XGCA (0.3% C, 1% Cr, 1% Mn, 1% Si according to GOST 4543) is used, supplied in the form of a tape with a thickness of 2–3 mm and a width of 40–90 mm. Mechanical properties of the workpiece: endurance limit σe = 350–850 MPa, yield point σp = 250–600 MPa, relative elongation at break δ5 = 15– 23%. The finished tape, after thermoplastic deformation by alternating sign bending and subsequent quenching with water at room temperature, has the following properties of the workpiece: endurance limit σe = 1200–2000 MPa, yield point σp = 1000–1900 MPa, relative elongation at break δ5 = 4–8% [32]. In the process of operation, the BTU perceives complex loads of cyclic tension and bending. The main requirements for BTU [33] are established: high fatigue strength, the number of loading cycles is at least 2 · 105 , equal strength along the entire length, high surface quality and high ultimate tensile strength of at least 1200–1500 MPa. Currently, a material with the above properties is not manufactured in Ukraine. Thus, the problem of increasing the inter-repair period of LSPU operation with BTU is related to the creation of a long-dimension, high-strength and durable BTU. As an alternative to steel, it is proposed to use carbon-fiber-reinforced plastic (CFRP) for the manufacture of the BTU column. CFRP is characterized by high strength at low density, corrosion resistance and other important physical and mechanical characteristics of the material (Table 1) [28, 34]. Table 1. The main physical properties of BTU materials №

Parameter

Value Steel

CFRP

1

Limit of endurance σ e , MPa

1000

1800

2

2.1

1.5

3

Modulus of elasticity E, × 1011 Pa Density ρ, kg/m3

7850

1350

4

Poisson’s ratio μ

0.3

0.22

The modulus of elasticity of CFRP along the fibers is almost half the modulus of elasticity of structural steels and depends on the manufacturing technology, reinforcement structure and heat treatment. In turn, the strength of CFRP directly depends on the modulus of elasticity due to the redistribution of loads between the carbon fiber and the matrix [35]. It was found that the use of a sucker rod string made of composites with a polymer matrix reduces its rigidity by approximately 4 times, and increases the dissipation of oscillations almost as much [29]. Dynamic models of LSPU were developed [36–38] and allowable loads were calculated [12], including taking into account the elasticity of the traction unit [39]. The purpose of the research is to determine the main geometric and strength characteristics of the LSPU band traction unit made of CFRP and compare them with steel ones.

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2.3 Coverage of the Main Research Material In order to compare the characteristics of steel and carbon-fiber BTU and to confirm the expediency of the BTU manufacturing from a unidirectional composite material, it is first necessary to determine the thickness, width, length and mechanical properties of the tape material depending on the load acting on it. The total stress acting in the BTU is determined by the formula σsum = σliq + σpl + σbtu + σfr + σwh + σbend ≤

σe , n

(1)

where σ liq is the stress due to the weight of the liquid above the plunger; σ pl is the stress due to the weight of the plunger and the load; σ btu is the stress due to the weight of the tape in the liquid; σ fr is the stress due to the friction of the BTU against the inner walls of the tubing pipes; σ wh is the stress arising from back pressure at the wellhead; σ bend is the maximum bending stress that occurs in the tape when it is wound on the LSPU drum. The stress in the tape due to the weight of the liquid depends on the value of the maximum weight of the liquid above the plunger and is determined by the formula  2  π ·dp ρliq · g · − b · δ · hmax 4 Pmax = , (2) σliq = b·δ b·δ where ρ liq is the liquid density, kg/m2 ; g is the acceleration of gravity, m/s2 ; d p is the inner diameter of tubing, m; b, δ is the width and thickness of the tape, respectively, m; hmax is the maximum depth of descent of the plunger, m. Stresses due to the weight of the plunger with the load are determined by the formula σpl =

mpl · g Ppl = , b·δ b·δ

(3)

where mpl is the mass of the plunger, kg. The stress due to the weight of the tape in the liquid is determined by the formula σbtu =

qbtu · l ρbtu − ρliq · , b·δ ρbtu

(4)

where qbtu is the weight of 1 m of tape, N/m; l is the length of the tape in the well, equal to the maximum depth of descent of the plunger hmax , m; ρ btu is the density of the tape material, kg/m3 . Stresses due to the action of the frictional forces of the BTU on the inner walls of the tubing are determined by the formula σfr =

qfr · Hliq , δ

(5)

where qfr is the force of friction at a length of 1 m, N/m; H liq = hmax is the height of the liquid column, m.

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Stresses arising due to the back pressure at the wellhead are determined by the formula σwh =

Pwh · fpl , b·δ

(6)

where Pwh is the pressure at the wellhead, MPa; f pl is the cross-sectional area of the plunger, m2 . The maximum bending stresses that occur in the tape when it is wound on the LSPU drum Ebtu · δ · k  , σbend =  1 − μ2 · r

(7)

where E btu is the modulus of elasticity of the tape material, Pa; k is the correction factor, k = 0.38–0.40; μ is the Poisson’s ratio; r is the radius of the LSPU drum, m. Making the necessary substitutions and neglecting the relatively small amount of stress due to the action of friction forces, we determine from Eq. (1) the maximum permissible loads on the traction body of the LSPU  Pmax =

ρbtu − ρliq σe E ·δ·k −  btu 2  − ρbtu · g · hmax · n ρbtu 1−μ ·r

 · b · δ − mpl · g − Pwh ·

π · dp2 4

.

(8)

Permissible height of liquid rise  hmax =

ρbtu − ρliq σe E ·δ·k −  btu 2  − ρbtu · g · hd · n ρbtu 1−μ ·r 

× ρliq · g ·

1 π ·dp2 4 −b·δ

.

 · b · δ − mpl · g − Pwh ·

 π · dp2 × 4

(9)

where hd is the immersion depth of the plunger below the liquid level, m. Let’s investigate the dependence of the permissible height of the liquid rise on the transverse dimensions of the tape b and δ. The thickness of the tape takes the value 1; 2; 3; 3.5; 4; 4.5; 5 mm. We accept for calculations: n = 2; hd = 500 m; ρ liq = 900 kg/m3 ; k = 0.4; r = 1 m; mpl = 100 kg; Pwh = 1 MPa. The maximum possible width of the tape depends on the inner diameter of the lifting pipes and is determined by the formula  2 − δ2 − Δ, (10) b = dmp where Δ is the sum of the tolerances on the size of the pipes and the concentricity of the threads, which reduce the internal diameter, m. Table 2 shows the value of the maximum tape width rounded to the standard range for different diameters of lifting pipes. The graphic dependence of the maximum pressure of the LSPU on the thickness of the tape for different diameters of the lifting pipes is presented in Fig. 2. When constructing graphical dependencies, the minimum tape width b = 35 mm is accepted.

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Dp , mm

48

60

73

73

89

89

102

114

δ p , mm

4.0

5.0

5.5

7.0

6.5

8.0

6.5

7.0

b, mm

35

45

55

55

70

70

80

90

It can be seen from Fig. 1 that there is an optimal thickness of the tape at which the maximum pressure is achieved. Thus, for steel tapes, the optimal thickness is about 3 mm, and for carbon-plastic tapes is about 5 mm. Changing the thickness of the tape relative to the optimal one reduces the carrying capacity of the tape due to the reduction of the allowable tensile load. Tubes of a smaller diameter have a greater height of liquid rise, which is explained by the rapid increase in the weight of the liquid compared to the carrying capacity of the BTU. In practice, tapes with such cross-sectional dimensions are most often used: 30 × 330 × 4.5; 35 × 3; 35 × 4.5; 45 × 2; 45 × 3; 55 × 2 and 55 × 3 mm. The graphical dependence of the maximum pressure of the LSPU on the tape thickness for different drum radii is presented in Fig. 3. When constructing graphical dependencies, the most common diameter of the tubing is 73 × 5.5 mm and the minimum tape width b = 35 mm.

1 – Steel; 2 – CFRP Fig. 2. Graphical dependence of the maximum pressure of the LSPU on the thickness of the tape for different diameters of the lifting pipes

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1 – Steel; 2 – CFRP Fig. 3. Graphical dependence of the maximum pressure of the LSPU on the thickness of the tape for different radii of the drum for winding BTU

For steel tapes, the optimal drum diameter is 2.0 m with a tape thickness of 3.0 mm, for carbon fiber tape the optimal drum diameter is 1.5 m with a tape thickness of about 5 mm. The diameter of the drum significantly affects the maximum height of the liquid rise, especially with a large thickness of the tape. Increasing the diameter of the drum allows you to increase the depth of the liquid rise from the well (Fig. 4). Let’s determine the strength characteristics of the material from which the BTU is made, depending on the load acting on it. The endurance limit of the tape material is determined by the formula

 Pper Ebtu · δ · k  + · n. (11) σe = b·δ 1 − μ2 · r

1 – Steel; 2 – CFRP Fig. 4. Graphical dependence of the maximum pressure of the LSPU on the radius of the drum for winding BTU

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According to the formula calculations (11) with the diameter of the LSPU drum about 2.0 m, the thickness of the tape 3–4.5 mm, the width of the tape 35–70 mm and the permissible load of 30–80 kN, to ensure reliable work, the tape material σ e at loading Pper = 30 kN should be 1400 MPa for steel (960 MPa for CFRP), at loading Pper = 60 kN—1540 MPa (995 MPa for CFRP), at loading Pper = 80 kN—1735 MPa (1020 MPa for CFRP). The calculated values of σ e for carbon tapes are twice smaller than the values are shown in Table 1. Taking into account the strength characteristics of the tape material and the accepted values of the width of the tape depending on the diameter of the tubing (Table 2) we build graphic dependencies (Fig. 5). When constructing graphic dependencies, the thickness of the tape δ = 3.0 mm for steel and δ = 5.0 mm for carbon plastic BTU is accepted.

1 – Steel; 2 – CFRP Fig. 5. Graphic dependencies of maximum pressure of LSPU on the width of the tape

Figure 5 shows that steel tapes provide a lift of fluid from a depth of 1500–4500 m, and carbon plastic from a depth of 1000–3000 m. Considering that the calculated minimum value of σ e for a carbon fiber tape is half the real value (Table 1), the depth of fluid lifting will be much greater.

3 Conclusion 1. Due to the high limit of endurance, low module of elasticity, low density and high dissipation coefficient carbon-fiber-reinforced plastic can be used to make the band traction units of the long-stroke pumps. The carbon-fiber band traction unit of a long-stroke pumping unit has a significant margin of endurance in comparison with steel bands. 2. The optimal values of the geometric parameters of the carbon-fiber band traction unit are determined and compared with the steel one: the thickness of the band is

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2–3 mm (4–5 mm for steel); the width of the band depends on the diameter of the tubing and is 35–90 mm; band length is 1000–3000 m (1500–4500 m for steel). 3. The diameter of the drum, which is wound, significantly affects the maximum height of the lifting of the liquid, especially at a large tape thickness.

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Tool Wear in the Process of Drill-String Connector Thread Lathe Machining Oleh Onysko(B) , Volodymyr Kopei, Yaroslav Kusyi, Lolita Pituley, and Iryna Taras Ivano-Frankivsk National Technical University of Oil and Gas, 15, Karpatska St., Ivano-Frankivsk 76019, Ukraine [email protected]

Abstract. The oil and gas industry is still the main and largest supplier of energy today. Extraction of hydrocarbons is a complex, science-intensive process that strongly affects the ecological state of the environment. The quality of drill strings, and especially their threaded connectors, determine the efficiency of oil and gas production and, at the same time, the environmental friendliness of the drilling process for years to come. Among the factors that contribute to this are the processes of thread-forming and appropriate tool-cutters. Lathe tools are the most widely used in the process of manufacturing drill-string threads. Well-known global trends offer such threading tools exclusively with a zero value of the rake angle. This, of course, ensures that a thread profile as close as possible to the theoretical one is obtained. However, this approach does not improve the efficiency of the threading process and does not allow these cutters to thread on alloyed, difficult-to-machine parts. The authors of this article developed a tool and methods of determining of the cutter wear resistance ability and show it on the example of the production of the 4 ½ Reg thread from chrome-nickel hardened steel. The result shows that the relative wear stability of the cutter proposed by the authors with a negative front angle is greater by more than 30% compared to the conventional. Keywords: lathe tool · rake angle · tool-jointtapered thread · carbide insert wearing · thread profile accuracy

1 Introduction Certain regions of the planet, even those that have certain hydrocarbon reserves, such as the Carpathians, pay considerable scientific attention to new renewable energy [1] based on hydrotechnical [2] or solar batteries [3]. However, according to the research results presented in the World Energy Outlook report [4], liquid, gaseous and solid types of fossil fuels will continue to occupy a significant share in the world energy balance until 2050. Therefore, in order to meet the growing needs of the gas and oil production industry, it is necessary to implement the latest technologies of drilling and transportation of hydrocarbon raw materials [5–7]. An important place in the development of the latest technologies of the Carpathian region is occupied by scientific research and proposals on drilling technological equipment [8], means of arranging wells [9], and methods © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 98–111, 2023. https://doi.org/10.1007/978-3-031-31066-9_11

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based on them [10], as well as pump-compressor equipment [11], pipeline transport in mountain conditions [12] and marine oil terminals [13]. Given the enormous social and environmental importance of the tasks, they require the wide involvement of new multidisciplinary innovative approaches in education and science, especially in the environments of specialized universities [14] and when using modern methods of functionally oriented design of technological processes taking into account surface engineering [15] Practical implementation such innovations require the use of reliable threaded connections for drill string elements [16], the manufacture of which is carried out taking into account modern machining technologies [17] and the improvement of theoretical and scientific approaches to the formation of threads [18] and the latest practice of their implementation. The introduction of new approaches to threading is closely related to the study and mastering of the latest scientific and technical achievements in the field of threading by means of their mechanical processing using metal cutting tools and machines. It is known that large-sized tapered threads, which are used as connectors in drill pipes, are mostly made in turning operations. One of the indicators of the efficiency of such operations is the wear resistance of turning cutters in the process of thread formation. The relevance is due to difficult cutting conditions, i.e.the cutter is responsible for the accuracy of simultaneously manufacturing all screw surfaces of the thread: roots, crests and connections between them. And therefore it should be resistant to tool-wear for a long period and at the same time ensure the accuracy of the thread. The process of measuring the tool-wear requires meticulous repetition, accurate measuring tools, which must be quite suitable for the complex profile of the thread lathe tools.

2 Literature Review Threaded connections of drill strings consist of pin and a box [19] (Fig. 1).

Fig. 1. Schema of drill-string tool-joint tapered thread. Doe to API7 Standard. Thread parameters: H– height not trancation, h1 – height trancation, h – connection height, P– pitch, a –width of flat (near root truncation), α/2– half angle, r – root radius, r 1 – radius of corners

Their threads are tapered in shape with an asymmetrical profile, as one side of the one is longer than the opposite. The profile angle α is equal to 60°, while it is divided

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in half by the bisector, i.e. the half-profile angles α/2 are 30°. According to the standard API 7 [19], the tolerance for deviation from the half-profile angle of the thread is ±4 0’. The study [20] proposed analytical formulas for calculating the profile of an asymmetric thread and an algorithm created on its basis. However, we are talking about the process of milling the trapezoidal Buttress thread, which is used in casing, not drill strings. The stability of a turning cutter largely depends on its geometric parameters, first of all on the value of its front angle, as well as the material of the workpiece. The article [21] specifically deals with the study of the influence of the geometric parameters of the thread cutter on the cutting forces, the nature of the chips, and the stability of the tool. Moreover, the material of the workpiece is stainless steel, which is required for operation in the aggressive environment of oil wells. It should be noted that unlike those offered by global manufacturers, the threaded carbide plate used in the study is not made with a zero back rake angle, but with a dimension of 12°. However, this article is not about measuring cutter wear, but only about the positive role of this parameter on its stability. In contrast to the mentioned article, the work [22] is actually about the wear of carbide inserts with different coatings under different cutting modes of turning processing of hard-to-machine duplex stainless steel. But firstly, the study [22] is not about turning the thread itself, and secondly, in the article [21] it does not talk about the influence of the rake angle on the accuracy of the thread at all. As a matter of fact, the accuracy of the thread depending on the kinematics parameters of the lathe is investigated in articles [18, 23], where the equations describing the influence of the rake angle on the accuracy of the thread profile [18] and on the accuracy of its lead angle [23] are theoretically proven. Deformation effects in the thread turning process are studied in [24]. The positive effect of the deformation compensation method on the obtained deviations with the help of the developed algorithm has been proven, but tool wear is not taken into account as one of the factors affecting the accuracy of the thread and especially the accuracy of the thread profile. Types of wear and failure of turning cutters have been analysed and introduced as options in training manuals of many leading tool manufacturers [25]. However, the geometric data of the tool were not considered as parameters of influence on their wear resistance (Fig. 2).

Fig. 2. Variants of failure of lathe thread cutters according to the tutorial SECO

According to the authors of the study [26], the cryogenic environment of liquid nitrogen causes lower values of wear on the major and minor tool flank. According

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to the nature of the operation of the cutter, the diagram in Fig. 3A is similar to the diagram obtained under normal temperature conditions (Fig. 3B). This work does not take into account the influence of geometric parameters, in particular the rake angle, on the amount of tool wear. The results of research [27] are mathematical models that describe the dependences between vibrations and cutter wear over time for large-step threads. Such threads include those that are connecting in drill strings. Therefore, largepitch tapered threads are always used in oil pipes, which are the subject of research in the paper [28]. The authors of that article point to the importance of feed type for both cutter design and the threading process itself. The work concerns multi-thread thread cutters, but it does not deal with the identification of the influence of their geometric parameters on the process in general and wear in particular.

A

B

Fig. 3. Time diagrams of tool edge wear: A - in the environment of cryogenic liquid nitrogen; B - under the conditions of ambient room temperatures with activation of the side sections of the edge

Therefore, taking into account the significant influence of geometric parameters on the efficiency of the thread-turning process, it is necessary to investigate the comparative dependence of wear and dimensional stability of thread cutters with a zero value of the rake angle and with a rake angle that is not zero. The value of this one is recommended in the range from –3° to –5° for processing threads on parts made of low-alloy chromenickel hard-workable steels, which are used to make tool-joint tapered threads for drillstring [29].

3 Research Methodology The authors of this article, referring to works [18, 23] and others, concluded that when there are processing large-pitch drill-string tapered threads all diameter sizes: of 60 mm and up to 210 mm, the value of the rake angle γ is within ± 5° will not lead to a significant change in its geometric parameters. In particular, the deviation from the nominal half-profile angle will be not more than 6’, which is less than 15% of tolerance of deviation. The deviations of other parameters for such values of the rake angle are even less significant.

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3.1 Design Providing of a Non-Zero Value of the Front Angle and Its Manufacturing However, the problematic part of this approach is the actual provision of a non-zero (for example, negative) value of the rake angle, as proposed in the theoretical study [18] (Fig. 4A), since the mechanical fastening of the carbide plates is quite precise and provides only the basic option - with zero value of the rake angle (Fig. 4B).

A

B

Fig. 4. Thread cutter adjustment scheme: A – with a negative back rake angle γ < 0, measured at tool-Nose (point a); B – with a zeroback rake angle γ = 0 measured at tool-Nose (point A). 1 – carbide insert, 2 – shim, 3 – tool holder.

A

B

Fig. 5. The scheme of ensuring the specified value of the back rake angle γ: A – the conventional tool, back rake angle γ = 0; B – the modernized tool shank with a changed tool-base, back rake angle γ < 0

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To study the influence of the back rake angle on wear, it is proposed to change not the attachment of the carbide insert, but the cutter holder (shank), changing the orientation of its base, as shown in Fig. 5. To realize this idea, the cutter holder of the “Vorgen” company was redesigned by high-speed milling of the tool-base at an angle equal to the value of the back rake angle at the Nose of the cutter, i.e. γ = –4° (Fig. 6). At the same time, the attachment of the carbide insert, remaining unchanged, leads to the formation of the back rake angle increased in 4° at the nose of tool-insert.

A

B

C

Fig. 6. «Vorgen» industrial thread lathe tool: A – a regular holder with a clamping shim, B – a carbide insert for threading with the profile form of V-040 (according to API 7 standard); C–tool shank with a base that provides a negative front angle γ = –4°

This modernized cutter together with a conventional cutter with a similar insert is used for comparative studies of their wear resistance ability. 3.2 Determination of the Value of the Maximum Radial Wear of the Threading Urning Tool Since the equipment on which modern lock threads are mainly manufactured are CNC machine tools, therefore it is customary to apply the most optimal type of feed for this research - modified flank infeed (Fig. 7A) [25].

A

B

C

Fig. 7. The main methods of feeding for thread turning (taken from SECO handbook)

Since the dimensional stability of the carbide inserts is intended for turning tool-joint tapered thread mainly concerns the wear magnitude of cutting edge part that forms the

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thread root. The amount of dimensional wear should be determined as the difference between the initial value of the cutting height h1 = 2.993 + 0.080 mm and its value during a certain period of operation of the cutter (Fig. 8). Theoretically, this value cannot be less than the number 2.626 mm, that is, it is the size of the thread connection working height h. Figure 8 shows the diagram of the tapered thread profile of the tapered thread according to form V-040. According to the standard API 7 [19], this form has the following parameter values: Thread parameters: H = 4.376 mm – height not truncated, h1 = 2.993 mm – height truncation, h = 2.626 mm – connection height, P = 5.08 mm – pitch, a = 1.016 mm – width of truncation flat (root truncation), α/2 – half angle, r = 0.508 mm – root radius, r 1 = 0.38 mm – radius of corners, f = 0.508 mm – crest truncation, b = 0.875 mm – root truncation. From Fig. 8, we notice that the dashed line, which corresponds to the characteristic operation of the modified flank infeed method, is critically possible, because it just touches the thread profile flat. This means that it is still possible to screw the pin into the box, but if the dashed line of tool wear will cross the truncation flat, it will become impossible, because the box body and the pin will interfere each other (Fig. 8). Therefore, the maximum tool radial wear umax = h1 –h is 0.373 + 0.08 mm.H = 4,376 mm – height not truncation, h1 = 2,993 mm – height trancation, h = 2,626 mm – connection height, P = 5,08 mm– pitch, a = 1,016 mm –width of flat (root trancation), α/2 – half angle, r = 0,508 mm – root radius, r 1 = 0,38 mm – radius of corners, f = 0,508mm – crest truncation, b = 0,875 mm–root truncation.

Tool

thread

А

В

Fig. 8. Graphical determination of the amount of cutting edge radial wear - u. A - schema of the drill-string tool-joint thread profileV-040 according to Standard API 7: 1–flank, 2 –wear thread profile reached after multiple modified flank infeed; B –diagram for a general explanation of the contact of the insert and the thread

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3.3 Creation and Use of a Visual Computer Optical-Graphic Template for Determining the Wear of a Thread Cutting Edge It is proposed to determine the dimensional operation by regular photo fixation of the used cutting edge of the carbide insert and subsequent alignment of the photo with a visual template, which is made using a picture of the divisions of a real calipers and vector graphics that simulate the elongation of the divisions. The use of the opticalgraphic template proposed by the authors involves combining the unwearied contours of the cutting edge of the used plate (that is, those intended to form the crest and sides of the thread profile) with the theoretical thread profile. Photographs were obtained at 20x magnification using a USB microscopeUSB2-MICRO-250X 250xand by using soft «DigitalViewer» (Fig. 9).

Fig. 9. A visual optical-graphic template proposed by the authors for determining the dimensional operation of a carbide threaded insert for a drill-string thread according to the profile of V-040. The size of the division is 0.1 mm: Insert cutting edge parts of: 1 – crest formed, 2 – right (short) side flank formed, 3 – left (long) side flank formed, 4 – calipers divisions

3.4 Parameters of the Determination of Wear Dimensional of a Carbide Insert Intended for Turning an External Taper Thread Wear dimensional of the cutter is classically defined as a function of time (diagram Fig. 3A, B). However, it is no less relevant to define it as a function of the cutting path. Of course, this path depends on the number of turns of the thread n, its pitch diameter Dpitchthe number of passes k and the number of threaded parts in the batch m: The number of turns can be determined by the formula: n=

l , P

(1)

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where: l– length of the threaded part of the pin, mm; P – pitcn of the corresponding shape of the thread profile. So the cutting path L m for the entire batch of parts can be determined: Lm = π Dpitch nkm,

(2)

If we return to the wear dimensional as a function of time, then the formula for determining the machine time for the entire batch of parts should be used: T=

l m, NP

(3)

4 Results 4.1 The Nature of the Wear of the Cutter Edge Under the Conditions of the Feeding Method: Modified Flank Infeed The asymmetric nature of the wear dimensional of carbide inserts (Fig. 10) is obviously related to the application of the allowance cutting scheme, which is determined by the cutting method and the gradual reduction of the allowance with each subsequent pass, which is required to ensure the equality of the area of the material layer that is cut (Fig. 7A.). This scheme enables the formation of non-box-shaped chips, but causes the predominance of the left-sided wear of the most loaded part of the carbide insert, which is intended for the formation of a thread root. Based on this, the size of the wear is fixed in the radial direction, to the left of the vertical line with divisions at the size of 0.1 mm.

Fig. 10. Determination of wear (flank wear) using a visual optical-graphic template. A – wear of the nose of the tool (partially worn edge to form a thread root), B – an enlarged version of the template application, which makes it possible to more accurately determine the radial wear magnitude of of the left side of the cutting edge –0.05 mm

The setting of the values of the wear dimensional is coordinated with the measurement accuracy, which is half the size of the division, that is is 0.05 mm. Therefore, the wear dimensional, which is recorded in Fig. 10 is 0.05 mm. Therefore, umax = 0.35 mm can be considered as a criterion for complete radial operation.

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4.2 Calculation of Input and Output Data to Determine the Wear Dimensional of the Carbide Plate Intended for Turning the External Thread Root of External Thread 4 ½ Reg For this work, the medium-diameter drill-string thread 4 ½ Reg was chosen, the pitch diameter of which is 110 mm on a smaller cone base. The shape of the thread profile is V-040 (Fig. 8). According to the recommendations, the spindle rotation frequency was 80 min-1. The parameters that must be used to determine the dependence of the wear dimensional of the carbide insert on the length of the cut during of machining the 4 ½ Reg external tapered thread are taken from the standard [19]. Based on the use of formulas (1–3), calculations were made and are entered in the table (Tables 1 and 2). Table 1. Summarized input parameters for determining the wear dimensional of a hard alloy insert intended to machine the external drill-string tapered thread 4 ½ Reg No

Name of parameter

Value and dimension

1

Spindel frequency, N

80 xv−1

2

Number of feedk

12

3

Length of cutting pathLm

92 mm

4

Pitch DiameterDpitch

110 mm

5

PitchP

5,08 mm

6

Number of turns, n

18

Table 2. Calculated input parameters for determining the wear dimensional of a hard alloy insert intended to machine the external drill-string tapered thread 4 ½ Reg No

Name of parameter

Value and dimension

1

Length of cutting path per 1 feed

6,217 m

2

Machining period path per 1 feed

0,255 xv

3

Length of cutting pathper one partL

74,644≈75(m)

4

Maxinni qac dl papti| detale T

2.7 xv

4.3 Diagram of the Dependence of the Wear Dimension of Thread Lathe Tools u (µm) on the Cutting Path L (m) Fixation of the value of the wear dimension was carried out after the production of threaded surfaces on every two pins, which is actually the equivalent of a cutting path of 75 x 2 = 150 (m). In a batch of 60 parts, that is, each of the tools (with a zero back rake angle and negative one γ = –4°) has to produce 30 pin threads. Cooling took place at

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the same lubricate-cooling liquid type. The resulting examples of periods: initial Wear (from left to point A), Steady State and Failure region are presented in Fig. 11. The solid and dashed lines are constructed by approximating the corresponding black (for a cutter with a zero back rake angle) and white points (for a cutter with a front angle of γ = – 4°). As can be seen from the diagram, the running in period corresponds to the 0A section of both curves. The period of Steady State corresponds to sections AE and AC. Point F corresponds to the photo recording of the wear in Fig. 11, and point C - in Fig. 11b. Points E and C are the starting points of the Failure region (Fig. 12).

Fig. 11. Wear dimensional process of carbide insert of V-040 thread profile as a result of manufacturing a batch of 60 pieces of 4 ½ Reg pin thread: A - catastrophic failure, B - completion of Steady State. 1– section of the edge that forms a ridge, 2– section of the edge that forms a short side of thread, 3– section of the edge that forms a larger side of thread

Fig. 12. The diagram of the dependence of the wear dimensional of threading cutting edge u (μm) on the cutting path L(m). Discrete fixations of the wear size of carbide plates are marked: black dots for a standard cutter, white dots for a modernized tool with a back rake angle –4°

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5 Conclusions Analysing the diagram in Fig. 12 we come to the following conclusion: – before the Failure period is started, the conventional cutter tool hade moved of 1,650 m, and the modernized one - of 1,950 m, i.e. 118% more; – ull failure (350 μm) is if it is using a conventional cutter tool (point F and further). So it is occurred after a cutting path of 1,800 m, while for a modernized cutter with the same length of the cutting path, the dimensional failure is 150 μm (point B), which is of 50% less; – the relative wear u/L for a conventional cutting tool (u = 150 μm, at L = 1500 m) is 0.1 μm/m, and the relative wear of a modernized cutting tool (u = 100 μm, at L = 1500 m) is 0.067 μm/ m, which is of 33% less.

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27. Li, Z., Fu, X., Li, J., Jiang, B., Wang, F.: Establishment of vibration wear model for turning large-pitch thread tools and its wear suppressionmethod. Int. J. Adv. Manuf. Technol. 109, 857–876 (2020). https://doi.org/10.1007/s00170-020-05403-w 28. Khoshdarregi, M.R., Altintas, Y.: Generalized modeling of chip geometry and cutting forces in multi-point thread turning. Int. J. Mach. Tools Manufact. 98, 21–32, November 2015. https://doi.org/10.1016/j.ijmachtools.2015.08.005 29. Fomin, E.V.: Improving the durability and accuracy of threaded cutters based on modeling the thread cutting process, Ph.D. Thesis, Moscow, Russia (2007) (in Russian)

Simulation of the Structure and Formation Kinetics of a Metastable Modification of Cerium Upon Quenching from a Liquid State Oleksandr Lysenko1 , Kalinina Tetiana1 , Iryna Zagorulko2 , Predrag Daši´c3(B) , and Oleg Popil1 1 Dniprovsk State Technical University, 2 Dneprostroevska Street, Kamyanske 51918, Ukraine

[email protected]

2 G.V. Kurdyumov Institute for Metal Physics of the N.A.S. of Ukraine,

36 Academician Vernadsky Blvd., Kyiv 03142, Ukraine 3 Academy of Professional Studies Šumadija – Department in Trstenik, 37240 Trstenik, Serbia

[email protected]

Abstract. In this paper is given the results of a complex computational analysis of the structure, mechanism and kinetics of crystallization of the metastable modification of cerium, which is fixed in the products of quenching from a liquid state with a thickness of less than 80 μm, are presented. The given are results of model calculations of parameters characterizing the kinetics of competitive crystallization of Ce for layers of different thicknesses and influence of the melt layers thickness on the rate of the process of QLS and the magnitude of supercooling corresponding to different stages of crystallization of the equilibrium δ- and γ-modifications of cerium. A correlation of simulation results with the corresponding experimental data has been achieved. Keywords: superfast quenching · cerium · metastable polytype · mathematical simulation · quenching from a liquid state (QLS)

1 Introduction As is known, some crystalline substances are differed by the property of polytypism, i.e. the existence of several close-packed modifications that differ in the number and pattern of atomic layers packing [1, 2]. In particular, among unadulterated metals, various closepacked structures are found in samarium and other light lanthanides, such as La, Ce, Pr, Nd [3]. Polytype crystal lattices are built by the densest packing of variously alternating atomic layers. For example, a face-centered cubic (FCC) lattice is composed of (111) close-packed planes arranged in the ABC… sequence. Hexagonal compact lattices, including two-layer (HC) of Mg type, four-layer (DHC) of α-La type and nine-layer (9R) of α-Sm type, consist of AB…, ABAC…, ABABCBCAC… repeating combinations, the building element of which is plane of the basis of the hexagonal prism (0001). The uniform principle of construction of the considered lattices interprets by independency of their specific atomic volume from the number of layers in the unit cell, as well as © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 112–122, 2023. https://doi.org/10.1007/978-3-031-31066-9_12

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small differences in free energies. The latter circumstance determines the low rate of polytype converting and the coexistence of different polytypes in the metals structure [1, 3]. Multilayer structures, as a rule, are developed in materials with a low energy of packing defects, which occur during crystallization, plastic deformation, and phase transformations during heat treatment [1]. A very effective way to saturate metals with packing defects is hardening from a liquid state (QLS) [4]. According to sources [5, 6], of all pure metals, cerium has the lowest packing defect energy (5·10–3 J/m2 ). This suggests that when conditions for the mass occurrence of packing defect are created, for example, due to fast cooling of the molten metal, a metastable modification with a multilayer close-packed lattice can be obtained in the Ce structure. Experimental evidence of the considered structural phenomenon of quenching from a liquid state, as well as its explanation in terms of the laws of non equilibrium crystallization of highly supercooled melts, was published in [7–9]. In addition to these publications, this paper focuses on the principles of modeling the structure of multilayer close-packed polytypes, as well as the essence of the mathematical model [10, 11] used to describe the kinetics of competitive crystallization of polymorphic metals.

2 Simulation the Structure of the Metastable Modification of Cerium According to reference data [3, 12], under conditions close to equilibrium, cerium crystallizes in the form of a body-centered cubic (BCC) δ-modification, which is stable in a relatively narrow temperature range (1071 – 999) K. At the lower boundary of this interval, a polymorphic transformation occurs with the formation of a close-packed γ-Ce modification with an FCC lattice. Another close-packed structural variety of the metal (β-Ce) with a double hexagonal compact (DHC) lattice of the α-La type is formed upon cooling below 250 K. The γ-Ce → β-Ce transformation is carried out by gradually changing the order of close-packed layers (ABC…(FCC) → ABAC(DHC)), described by a low speed, incompleteness, and large temperature hysteresis [13]. Figure 1a shows the scheme of rearrangement of the FCC lattice of the γ-modification of cerium into the DHC lattice of the low-temperature β-modification. The left column of the diagram shows the initial pacing sequence of close-packed (111) planes in the basic FCC lattice (ABC…). The horizontal segments mark the places of their relative shifts. The arrows indicate the coordinates of the atoms in the shifting layer before and after the shift. The finite configuration of close-packed planes (ABAC…) is notable in bold type. As can be seen, the γ-Ce(FCC) → β-Ce(DHC) transformation is carried out by successive displacements of crystal parts by the shortest interatomic distances in two adjacent atomic planes of the base FCC lattice. The result of such displacements is the occurrence of implantation packing defects (PD+ ), the formation of which is equivalent to the incorporation of additional atomic layers into the FCC lattice, as shown in the right part of the scheme under consideration. It also follows from Fig. 1a that, for the complete transformation of the FCC lattice into a DHC lattice, implantation packing defects must be arranged in a strictly ordered manner every three atomic layers of the initial structure.

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Fig. 1. Schemes of rearrangement of the crystal lattice in the process of transformations of the FCC γ-modification of Ce into multilayer polytypes with the structures: a - DHC β-Ce; b - 7R μ-Ce.

This nature of the periodicity corresponds to the concentration of packing defects γ = 1/4. Similarly, i.e. by introducing serially located packing defects into the FCC lattice, other varieties of multilayer polytypes can also be constructed. Presumably, they also include the structure of the metastable modification of cerium (μ-Ce), which is revealed in rapidly quenched films with a thickness of l s2 > s3 > · · · > sn For a two-stage tool it is: s1 sin α1 = s2 sin α2

(4)

It follows from the expression (4) that α1 > α2 , if one wants to achieve the same length of contact on both rings. The same relationship applies to a tool with N rings. 2.2 Determination of the Dimensions of the Diameter of the Extraction Rings The dimensions of the rings should be determined in such a way as to ensure dimensional accuracy, prescribed product manufacturing quality and to enable a stable extraction process. Dimensioning of multi-stage tools in existing production practice is the result of many years of experience and requirements related to dimensional accuracy and product quality. The stability of the production process, with a minimum number of downtimes due to the replacement of the puller rings due to wear, cannot be achieved without a proper redistribution of the load within the multi-stage tool. In order to achieve a proper redistribution of the load on all rings in a multi-stage tool, mathematical models were developed for their dimensioning: a model of equal load on all rings in a multi-stage tool and a model of separation of deformations (by diameter and by wall thickness) [4].

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It has been experimentally proven that it is best to use a model based on the assumption that all rings in a multi-stage tool are equally loaded for sizing multi-stage tools. The condition of equal wear of all rings is reduced to the condition of equal deformation work for each ring. This model takes into account the solidification of the material during the drawing process via a third-order solidification curve. The diameter of any ring in the “di ” tool can be calculated based on the following expression:  4 (5) di = d 2 + · Ai π where: Ai- cross-sectional area after the i-th operation. 1−Ci i Ai = AC 0 · Ap

(6)

where: A0 - cross-sectional area of the preparation, AP - cross-sectional area of the finished piece. Table 1 showsthe calculated values of the Cicoefficients for workpieces made of. CuZn 28 brass on three-stage, four-stage and five-stage tools. Table 1. Values of coefficients Ci for brass CuZn28 1−Ci i Ai = AC 0 · Ap

Values of coefficients Ci for brass CuZn28 The number of rings in a multi-stage tool

Ai

3

4

5

C1

0,583

0,665

0,715

C2

0,269

0,410

0,500

0,193

0,317

C3 C4

0,152

2.3 Determination of the Minimum Number of Rings Nmin in a Multi-stage Tool The minimum number of rings in a multi-stage tool depending on the known logarithmic degree of deformation (φu ), which should be performed on that tool, is calculated according to the expression [3]: Nmin 1.2 · 2.1 u The obtained value of Nmin is rounded to the first larger integer.

(7)

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2.4 Analysis of the Influence of the Height of the Extraction Ring and the Total Height of the Tool L When determining the height of the draw rings in a multi-stage tool and the overall height of the tool, the technological limitations related to the existing equipment must be taken into account.When determining these dimensions, the stroke of the press and the space for placing the tool should be taken into account.

3 Experimental Research From the aforementioned analyses, it can be concluded that the correct dimensioning of the diameter of all rings in the tool has the greatest influence on the design of the optimal geometry of the multi-stage tool. That dimensioning is closely related to the redistribution of the total degree of deformation (as stated in point 2.2). In order to demonstrate this, experiments were carried out with a large number of brass workpieces of different initial and final dimensions. Five-stage tools dimensioned by three models were experimentally investigated. The dimensions of the rings according to the first model were determined so that a calculation was first made according to the model of equal load of all rings in a multi-stage tool, and then the model was deviated from because of the high costs of making the rings, so only the last rings in the tool were made according to the calculation. The front rings in the tool were assembled from previously made rings, the dimensions of which were close to those obtained by calculation. In the same way, the dimensions were obtained according to another model, in which the basis for the calculation was the model of separation of deformations by diameter and thickness of the wall. The third applied model is the model of equal loading of all rings in a multi-stage tool. These experiments were carried out with the aim of finding the maximum degree of deformation. The total degree of deformation is the same in all investigated tools (experiments E1, E2, E3 and E4) and amounts to ϕu = 1.95. Table 2 shows the percentage ratio of the logarithmic degree of deformation and the total degree of deformation for five-stage tools dimensioned according to the first two models for the products of the first group (labels of experiments E1 and E2), and for five-stage tools dimensioned according to the first and third models (the model of equal load of all of rings in a multi-stage tool) for the products of the second group (labels of experiments E3 and E4). Table 2. Load redistribution in five-stage tools FIVE-STEP TOOLS Labelof the experiment

φi /φu [%]

E1

0,251

0,192

E2

0,18

0,264

0.149

0.295

0.110

E3

0,259

0,216

0,170

0,139

0,222

E4

0,285

0,216

0.185

0.166

0,148

0,149

0,295

0,110

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Based on the data from Table 2 a distribution diagram of ϕi /ϕu in five-stage tools was made (Fig. 4).

Fig. 4. Distribution diagram of ϕi /ϕu [%] in five-stage tools for the first group of workpieces (a) and for the second group of workpieces (b)

Considering that the dimensions of the third, fourth and fifth rings in the five-stage tools in experiments E1 and E2 are the same, the load redistribution curve in Fig. 4a of the third ring coincides for these two tools. The diagram in Fig. 4.a shows a sudden jump of ϕi /ϕu on the fourth ring (in experiment E1), and on the second and fourth rings (in experiment E2). As a result of such a redistribution of the load, cracking of the workpieces occurred in the mentioned places. The presented redistribution of load in experiment E3 resulted in occasional cracking of workpieces, due to the large value of the logarithmic degree of deformation on the fifth ring in the tool. Redistribution of the load according to the theoretical model of equal loading of all rings in a multi-stage tool (experiment E4) ensured the extraction process without cracking the workpiece. These experimental results show that load redistribution in a multistage tool is crucial for the stability of the process when approaching the maximum degree of deformation.

4 Conclusion Based on the theoretical analysis of stress-strain relationships and experimental results, the steps for designing the optimal geometry of multi-stage tools are defined: - Determination of the total logarithmic degree of deformation (ϕu ) based on the crosssectional area of the workpiece and preparation; - Determination of the minimum number of rings in the multi-stage tool Nmin (expression. 7); - Calculation of the diameter of the dmi rings in a multi-stage tool according to the equal. load model (expression 5); - Determination of the angles of the extraction rings (expression 2);

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- If it is desired to have the same length of contact between the workpiece and the extraction ring (li = const) (expression 3) on all rings in the tool, then the ratio of thicknesses and angles of the extraction rings must be taken into account (expression 4). If the suggested steps for designing multi-stage tools are followed, a stable drawing process with the highest tool stability will be achieved.

References 1. Noži´c, M., Ðuki´c, H.: Influence of multiple tool geometry on drawing force. In: 8th International Conference "NEW TECHNOLOGIES, DEVELOPMENT AND APPLICATION" NT-2022, Sarajevo, Bosna i Hercegovina (2022) 2. Lee, C., Hong, S.: Curvature area prediction for the deep drawing-ironing process of a cylindrical cup using finite element method and regression analysis. J. Mech. Sci. Technol. 32(12), 5913–5918 (2018). https://doi.org/10.1007/s12206-018-1142-4 3. Ðuki´c, H., Noži´c, M.: Limit values of maximal logaritmics strain in multi-stage cold forming operations. J. Technol. Plast. 40(1) (2015) 4. Noži´c, M., Ðuki´c, H.: Novi pristup dimenzionisanju višestepenih alata. In: XXXI Savjetovanje proizvodnog mašinstva Srbije, Kragujevac (2006) 5. Adamovi´c, D., etal.: Numerical modeling of ironing process. J. Technol. Plast. 38(2) (2013) 6. Ðuki´c, H., Noži´c, M.: Model za dimenzionisanje višestepenih alata 5.Medunarodni nauˇcnostruˇcni skup “Tendencije u razvoju mašinskih konstrukcija i tehnologija”TMT 2000, Zenica (2000) 7. Adamovi´c, D., et al.: Analysis of the surface state of tools influence on the ironing process. J. Technol. Plast. 36(2) (2011) 8. Noži´c, M., Ðuki´c, H.: Istraživanje ukupnog optere´cenja višestupanjskih alata. In: MATRIB 2015, International coference on materials, tribology, recycling, Vela Luka, Hrvatska (2015) 9. Pernis, R., Bareni, I., Kasala, J., Lickova, M.: Evaluation of limiting drawing ratio (LDR) in deep drawing process. Acta Metall. Slovaca 21, 258–268 (2015) 10. Park, G., Park, R., Kwak, H., Kim, C.: Design of a combined redrawing-ironing process to manufacture a CNG pressure vessel liner. J. Appl. Sci. 11, 8295 (2021)

Research of the Surface Oil Absorption Processed by Vibration Rolling and Deforming Broaching Ihor Shepelenko(B) , Evhen Solovykh, Oleh Bevz, Stanislav Katerynych, and Andrey Solovuch Central Ukrainian National Technical University, 7 Universytetskyi Avenue, Kropyvnytskyi 25006, Ukraine [email protected]

Abstract. A technique for studying the oil absorption of a surface with a regular microreliefis proposed, which has been successfully tested in experimental studies. The main regularities of changes in the oil absorption of the surface processed by vibration rolling are established, and a comparison of theoretical and experimental data is carried out. The possibility of changing the oil absorption value of the surface and obtaining its optimal value for various operating conditions of movable conjugations by varying the processing modes is shown. The expediency of using deforming broaching to increase the supporting surface of a regular microrelief while maintaining an increased oil absorption is proved. Keywords: Regular microrelief · Surface oil absorption · Vibration rolling · Supporting surface · Deforming broaching

1 Introduction From the three states of the lubricated surface (friction without lubricant, boundary and hydrodynamic lubrication), for most friction pairs, the boundary state of lubrication is most characteristic, in which the thickness of the oil skin is estimated from tenths to several micrometers. When the oil skin is worn out or broken, the reverse process occurs simultaneously – its regeneration. This requires a certain supply of lubricant, which can be located in the cavities of the microrelief or in special recesses (pockets) on the friction surface [1]. The creation of microreliefs with regular geometric characteristics on the working surface of parts makes it possible to analytically calculate with sufficient accuracy such parameters that directly determine the operational properties of these surfaces, such as the volume of grooves (oil absorption), the supporting surface, the number of contact spots, etc. [2]. The optimal number and volume of recesses in the elements of a regular microrelief, combined with their large radius and significant surface activity of work-hardened metal in the areas of the recesses, provide not only sufficient oil absorption of the surface, but also good retention of the lubricant on the treated surface [3]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 131–138, 2023. https://doi.org/10.1007/978-3-031-31066-9_14

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However, with an increase in oil absorption, the bearing capacity of the surface decreases, which adversely affects the operational properties of the processed parts. Therefore, for each operating conditions of the movable conjugation, its own rational microrelief of the parts working surfaces is required.

2 Literature Review One of the most important problems in the field of mechanical engineering is to improve the quality of the part working surface, which can be achieved through the use of processing methods that provide the possibility of forming regular, finely controlled, analytically calculated microreliefs on the surface of parts. The ever-increasing requirements for the operational characteristics of machines and mechanisms put forward the need for a significant improvement in the operational properties of parts. The solution to this problem is the creation of more modern machine designs, the development of new advanced technologies for manufacturing parts and the improvement of existing processing methods, as well as improving the quality of finishing treatment of the parts working surface, the condition of which largely determines their operational properties [4]. Finishing treatment of parts determines the initial microrelief of rubbing surfaces, the wear of which depends on such factors as the supporting surface, its oil absorption when working with lubricant, the volume and location of oil pockets relative to the direction of friction. Thus, an effective way to improve the wear resistance of friction surfaces is to increase their oil absorption, which is understood as the ability of the surface to reserve a certain amount of lubricant that can be supplied to the friction surfaces in the event of oil starvation. The importance of creating oil pockets for friction surfaces was convincingly proven in work [5]. An analysis of literary sources has shown that in order to ensure the wear resistance and oil absorption of cylindrical parts surface, it is advisable to use the operations of vibration running in (for external surfaces) and rolling (for internal surfaces) with the formation of a regular microrelief. Moreover, for the formation of a regular microrelief on the outer surfaces, only the feed movement is reported to the multi-ball knurler, and the part, in addition to rotation, performs a reciprocating movement. When a regular microrelief is applied to the inner surfaces of the processed part, the feed motion is reported, and the rotating multi-ball roller also performs an oscillating motion [6]. When a regular microreliefis formed on the inner surfaces, it is possible to obtain surfaces of three types (Fig. 1), which determine the change in the dimensions of the workpiece during vibration rolling: the diameter of the hole can increase, remain unchanged (theoretically) or decrease [7]. The increase in size occurs as a result of smoothing the initial surface due to the metal filling of the initial surface protrusions adjacent to the protrusions of the hollows (Fig. 1, a), a particular case may be the equality in height of the initial and resulting microroughnesses (Fig. 1, b). When vibration rolling with certain modes, metal is extruded above the level of the initial surface maximum microroughness and the size of the bushing hole decreases (Fig. 1, c).

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Fig. 1. Changing the dimensions of a part during the formation of a regular microrelief [7]: a) increase in the diameter of the part; b) maintain part diameter; c) reducing the diameter of the part; Rmaxin – initial maximum microroughness height; R – height of microroughness after vibration rolling; d in – initial diameter of the part; d d – diameter of the part after vibration rolling

However, with an increase in the height of the extruded protrusions of a regular microrelief elements, the radius of their curvature decreases, and, consequently, the supporting area decreases. Thus, according to work [8], an increase in the height of a regular microrelief elements from Ra = 1.6 µm to Ra = 12.5 µm reduces the support area from 30 to 5% when the conjugated surfaces approach each other by 1.5 µm. Thus, to obtain the optimal area, a large amount of the rubbing surfaces convergence is necessary, which causes an undesirable increase in the gap of the movable conjugation. To increase the supporting area of surfaces restored by vibration rolling while maintaining increased oil absorption, it is possible to use a high-performance method of surface plastic deformation – deforming broaching as a finishing operation [9]. The purpose of this work is to study the oil absorption of a surface with a regular microrelief obtained by vibration rolling. Achieving this goal requires solving the following tasks: – to develop a methodology for studying the oil absorption of a surface with a regular microrelief; – to establish the main patterns of changes in the oil absorption of the processed surface, depending on the modes of vibration rolling; – to substantiate the expediency of using deforming broaching to achieve the optimal supporting area while maintaining the oil absorption of the surface.

3 Research Methodology The application of a regular microrelief was carried out on a device for processing internal cylindrical surfaces (Fig. 2), in which the tool oscillation and rotation carried out from one drive – the machine drive. The principle of the proposed device operation, consisting of a leading 1 and oscillating 3 nodes, as well as a multi-ball roller 2, installed on a screw-cutting lathe, is that the multi-ball roller performs rotational and reciprocating

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motion along the axis of processed part, which is reported by the feed movement. The imposition of rotational and reciprocating movements of the deforming elements and the translational movement of the part ensures the creation of a regular microrelief on the processed surface.

Fig. 2. Device for vibration rolling: 1 – leading node; 2 – multi-ball roller; 3 – oscillation node

With the help of the developed device (Fig. 2), a regular microrelief was applied on ring samples of bronze TZL 5–5-5 by vibration rolling (Fig. 3) under the following modes: the number of balls in the roller N b = 2; ball diameter d b = 3.97 mm; the amplitude of the roller oscillation l = 15 mm; the number of the deforming elements double strokes per second N = 8; processing speed V = 1.0 m/s; feed pitch varied within S = 1.14–3.50 mm/rev. Tension during vibration rolling ir was chosen so that it provided the depth of the extruded groove h = 25 µm. To study the oil absorption, the ring samples after their boring and vibration rolling were cut into sectors with an area of 1 cm2 (Fig. 3).

Fig. 3. Experimental samples processed by vibration rolling

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Before testing, the experimental sample was thoroughly washed with a solvent, dried and weighed on a laboratory balance TBE-0.21–0.001. Then, the working part of the sample was rubbed with paraffin and pressed against the outer surface of the roller (roller material: steel 45). Such a design, containing a rolling pin with a corrugated disk, a device for fastening an experimental sample and an electrical part (Fig. 4), was mounted on a screw-cutting lathe.

Fig. 4. Electrical circuit of the installation for determining the oil absorption: 1 – roller; 2 – test sample

The current is supplied to the roller from the step-down transformer Tr and rectifier B (Fig. 4) through a rotating cartridge spring-loaded with a copper-graphite brush installed in a brush holder fixed on the machine frame, and to the sample directly through the support. The presence of voltage is controlled by a voltmeter (V), and the appearance of current in the electrical circuit by an ammeter (A). To prevent leakage of current or short circuit during installation in the tool holder of the device for fastening the annular sector, two insulating plates are used, and a rheostat (R) is also provided. In the presence of paraffin layer between the surfaces of the disk and the annular sector, there was no current in the electric circuit. In the case of removing a non-conductive skin with a scraper, the ammeter (A) recorded the appearance of a metal contact between the rubbing surfaces. After that, the roller with the experimental sample was dismantled, and the test sample was re-weighed. The oil absorption of the surface V was determined by the formula: V =

M2 − M1 , ρn

(1)

where M 1 , M 2 – respectively, the mass of the experimental sample is initial and saturated with paraffin; ρ p – paraffin density (0.90 g/cm3 ). The specific oil absorption of the surface V s can be found from the expression: Vs =

V , F

(2)

where F – total area of the studied surface, cm2 . The experimental data were compared with the theoretical ones obtained analytically by the authors of work [6].

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4 Results Figures 5 and 6 shows the experimental and theoretical dependences of the specific oil absorption of a surface with a regular microrelief on the modes of vibration rolling. In this case, a good correlation is observed between the experimental and theoretical values of the specific oil absorption of the surface.

Fig. 5. Dependence of the specific oil absorption of the surface V s with a regular microrelief on the feed S at different oscillation amplitudes of the roller: 1 – l = experimental 5 mm; 2 – l = 10 mm; theoretical curve curve;

Fig. 6. Dependence of the specific oil absorption of the surface V s with a regular microrelief on the feed S at different ball diameters: 1 –d b = 3.97 mm; 2 –d b = 5.80 mm; 3 –d b = 7.94 mm; experimental curve; theoretical curve

Changing the modes of vibration rolling (feeding an annular sample (Figs. 5 and 6), ball diameter (Fig. 6) and oscillation amplitude (Fig. 5)) made it possible to increase the height value of the regular microrelief element, and also contributes to an increase in the specific oil absorption of the processed surface. Thus, by varying the modes of vibration rolling, it becomes possible to achieve for each specific friction pair the optimal volume of the cavities of a regular microrelief elements. However, an increase in the oil absorption of the surface reduces its bearing capacity. Figure 7 shows the dependence of the support area during vibration rolling on the value of convergence with the conjugated part (curve 1) and the support area of the rolled surface on the tension of the deforming broaching (curve 2). A slight discrepancy between the theoretical and experimental curves is due, in our opinion, to the rounding radii of a regular microrelief elements protrusions and their parabolic change in area along the height that are not taken into account in the calculation formulas. According to the data [10, 11], the optimal value of the supporting surface is within 30…50% of the friction surface total area (in Fig. 7 zone of the optimal supporting surface is shown in gray).

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Fig. 7. Dependence of the support area F sup of the vibro-rolled surface on the value of convergence Δ (1) and the vibro-rolled surface after deforming broaching on the tension ilim (2): experimental curve; theoretical curve

Achieving these values is possible by applying the operation of deforming broaching of the surface processed by vibration rolling with tensions within the limits ilim min …ilim max . Achieving the optimal supporting surface after the operation of vibration rolling became possible with the convergence value min …max (according to Fig. 6 – in the range of 27…47 µm). In this case, to achieve a regular microrelief according to the variant with a decrease in the size of the hole (Fig. 1, c), it is necessary that the height of the element R exceed the value of the allowable minimum tension during deforming broaching ilim min . Thus, the use of deforming broaching with allowable tensions within ilim min …ilim max ensures not only obtaining the optimal supporting area, but also maintains increased oil absorption, since evenly spaced grooves remain on the processed surface.

5 Conclusion The material presented allowed to draw the following conclusions: – to study the oil absorption of a surface with a regular microrelief, a research technique was proposed, which was tested on samples processed by vibration rolling; – it has been established that the application of a regular microrelief not only increases the oil absorption of rubbing parts working surfaces, but also allows, by varying the modes of vibration rolling, to change its value in order to obtain optimal values for various operating conditions of movable conjugations; – it has been proven that the use of deforming broaching makes it possible to achieve an optimal supporting surface while maintaining the increased oil absorption obtained by vibration rolling.

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References 1. Kovalevskaya, Z.G., Uvarkin, P.V., Tolmachev, A.I.: Some features of the formation of the surface microrelief of steel under ultrasonic finishing treatment. Russ. J. Nondestruct. Test 48, 153–158 (2012). https://doi.org/10.1134/S1061830912030047 2. Gavrilov, S.A., Shchedrin, A.V.: Improved use of metal-plating conditioner in combined machining. Russ. Eng. Res. 32, 573–576 (2012). https://doi.org/10.3103/S1068798X120 6007X 3. Dzyura, V., Maruschak, P., Prentkovskis, O.: Determining optimal parameters of regular microrelief formed on the end surfaces of rotary bodies. Algorithms 14, 46 (2021). https:// doi.org/10.3390/a14020046 4. Dzyura, V., Maruschak, P.: Optimizing the formation of hydraulic cylinder surfaces, taking into account their microrelief topography analyzed during different operations. Machines 9(6), 116 (2021). https://doi.org/10.3390/machines9060116 5. Gorokhov, V.A.: Regulation of microreliefs of surfaces of mechanical engineering products, Moscow, p. 60 (1991). [in Russian] 6. Shepelenko, I., Warouma, A., Sherkun, V.: Restoration of bronze bushes by the method of surface plastic deformation. Int. J. Eng. Technol. 5(1), 29–32 (2016). https://www.sciencepu bco.com/index.php/ijet/article/view/5651 7. Schneider, Y.G.: Service Properties of Parts with Regular Microrelief, Leningrad, p. 248 (1982). [in Russian] 8. Nagî¸t, G., Sl˘atineanu, L., Dodun, O., Ionu¸t, M., Andrei, R., Mihalache, M.: Surface layer microhardness and roughness after applying a vibroburnishing process. J. Mater. Res. Technol. 8, 4333–4346 (2019). https://doi.org/10.1016/j.jmrt.2019.07.044 9. Nemyrovskyi, Y., Shepelenko, I., Solovykh, E., Bevz, O., Leshchenko, S.: Studying the mechanics of low-plastic materials surface layer processed by deforming broaching. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V. NT 2022. Lecture Notes in Networks and Systems, vol. 472. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_15 10. Odintsov, L.G.: Hardening and finishing of parts by surface plastic deformation, Moscow, p. 328 (1987). [in Russian] 11. Shepelenko, I., Nemyrovskyi, Y., Tsekhanov, Y., Mahopets, S., Bevz, O.: Peculiarities of interaction of micro-roughnesses of contacting surfaces at FANT. In: Ivanov, V., Trojanowska, J., Pavlenko, I., Zajac, J., Perakovi´c, D. (eds.) DSMIE 2020. LNME, pp. 452–461. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50794-7_44

Genetic Algorithams Modeling of Cutting Forces During Turning Hard Steel for Economic Sustanable Production Pavel Kovaˇc1(B) , Mirfad Tari´c2 , Borislav Savkovi´c1 , Dušan Ješi´c3 , and Branislav Dudi´c4,5 1 Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia

{pkovac,savkovic}@uns.ac.rs

2 Srednja škola metalskih zanimanja, Sarajevo, Bosnia and Herzegovina 3 International Technology and Management Academy – MTMA, Novi Sad, Serbia 4 Faculty of Management, Comenius University in Bratislava, 820 05 Bratislava, Slovakia

[email protected] 5 Faculty of Economics and Engineering Management, University Business Academy,

21000 Novi Sad, Serbia

Abstract. This paper presents the modeling of the main cutting resistance when turning hardened steel using artificial intelligence, i.e. genetic algorithms. Given that the cutting forces during machining are of great importance, the application of genetic algorithms tries to reduce human intervention in the selection of optimal cutting tools and process parameters for metal cutting Of ecconomic sustanable production. In the work, the processing of hardened material is carried out, which until now was processed by grinding, but now one operation can be skipped and the processing is finished by turning. In material removal processes such as turning, the choice of cutting tools and optimal process parameters play a decisive role in improving quality and reducing production costs. Keywords: cutting force · turning · hardened steel · artificial intelligence · genetic algorithms

1 Introduction The idea of genetic algorithms is based on Darwin’s theory of evolution, which states that all life is connected and descended from a common ancestor. However, the origin of the use of genetic algorithms dates back to 1975, when John Henry Holland, an American scientist and professor of electrical and computer engineering, described the basic properties of genetic algorithms in his publication Adaptation in Natural and Artificial Systems. It is J.H.Holland who is considered the founder of genetic algorithms [1]. 1.1 The Working Principle of Genetic Algorithms It can be seen that a typical genetic algorithm scheme is performed according to the following sequence of operations: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 139–148, 2023. https://doi.org/10.1007/978-3-031-31066-9_15

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1. Initialization – the process of creating the initial population. 2. Evaluation of fitness success – we get a vector of fitness function values for the current population of fitness functions. 3. Testing the fulfillment of the final conditions (in case the conditions are met, the most successful individual is characterized as the final solution of the task). 4. Selection of the most successful group (b) of individuals and their transfer to a new population. The new population will therefore always contain the best individuals. 5. Selection of the number of individuals (n-b) that cross and mutate (b is the number of individuals selected in the previous step, and n is the population size). 6. Transfer of new individuals to the new population (the new population at this stage has the same size as the “old” population). 7. Repeating the entire cycle until the final condition is met (must be properly determined). After fulfilling the conditions, the final solution of the problem becomes the best individual of the last population (compliance with point 3) [2].

2 Data and Conditions for Performing the Experiment All data of the experiment were taken from the doctoral dissertation of Tari´c Mirfad. The conditions under which the experiment was carried out refer to the machine tool, cutting tool, workpiece material and processing mode parameters [3]. 2.1 Machine Tool The machine tool used for cutting is a universal lathe - Prvomajska DK480. The universal lathe – Prvomajska DK480 was installed in the Laboratory for cutting metal processing at the Faculty of Engineering Sciences, University of Kragujevac. The machine is shown in Fig. 1. The mentioned machine tool has the following features: • Electric motor power 10 KW, • the maximum processing diameter is 320 mm, • the maximum processing length is 2000 mm, The displacement values of the specified lathe are shown in Table 1. Table 1. Feeds on the lathe f [mm/rev]

0.045, 0.05, 0.056, 0.063, 0.071, 0.08, 0.09, 0.1, 0.125, 0.14, 0.16, 0.18, 0.2, 0.224, 0.25, 0.28, 0.315, 0.355, 0.4, 0.45, 0.5, 0.56, 0.63, 0.71, 0.8, 0.9, 1.0

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Fig. 1. Universal lathe - Prvomajska DK480

2.2 Characteristics of the Tools Used in Processing Based on the source and tool availability, two types of tiles were selected; from cubic boron nitride (CBN) designation: CNMA 12 04 04 ABC 25/F and CCMW 12 04 04 from the manufacturer ATRON from Germany [4]. These two types of tiles were chosen because of their different rake face. Figure 2 shows the cut plates of the mentioned labels used in the experiment.

Fig. 2. a) CNMA12 04 04 (CBN), b) CCMW 12 04 04 (CBN).

The markings of the cutting plates according to the DIN 4983 standard define the geometry more closely, namely: plate shape C → rhombus; chest angle N → α = 0°, C → α = 7°; tolerance class M; plate type → with A, W and G shaped openings; cutting blade length → 12.7 mm (12); cutting plate thickness → 4.76 mm (04); tool tip radius → 0.4 mm (04). All tiles have a rake face (γ = 0°) of zero [3]. Since there are two types of tile geometry with a rake face of Ƴ = 0° and γ = 6°, it is necessary to choose the appropriate tool holders in which the cutting tiles will be placed and achieve the mentioned rake face. In accordance with DIN 4983, two label carriers PCLNR 25 25 M12 and SCLCR 25 25 M12 [3] were selected. The markings of the tool holder according to the DIN 4983 standard define more closely: the clamping system P → through the opening; tile shape C → rhombus; knife attack angle L → κ = 91°, κ1 = 5°; back angle N → α = 0°, C → α = 7°; cutting

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direction R → right; body cross-section → height 25 mm; body cross-section → width 25 mm; tool holder length M → 150 mm; the length corresponding to the tile cutting blade is 12 mm. Taking into account the selected cutting inserts and tool supports, it can be concluded that the experiment will be performed with CBN inserts, for two cases with different rake faces [5]. 2.3 Workpiece Before performing the experiment, the workpiece was prepared. The workpiece heat ˇ 3840) with a working hardness of 55 HRC, a circular section treated steel 90MnCrV8 (C of Ø34 mm and a length of 500 mm. In order to make cutting easier and for more reliable measurement results, the workpiece is clamped in the chuck with one end, and the other end rests on a spike. A certain layer of material was removed from the workpiece in order to avoid throwing-ovality and to make the results more credible [6, 7]. A bar length of 500 mm needs to be divided into 24 fields of 10 mm length on which to perform longitudinal machining with CBN inserts without the presence of coolants and lubricants (CAL) as shown in Fig. 3. Each field is planned for one experimental point. In this way, processing in one clamping is enabled, and thus the same conditions are ensured for all experimental points. The material of the workpiece is alloy tool steel for cold work 90MnCrV8 (Cˇ 3840) or so-called merino tool steel for universal use. It has high hardness and minimal deformation; it is mainly used for measuring tools, scissor knives, spiral drills, thread cutting tools, reamers, controls, sheet metal cutting tools, has high hardenability and is dimensionally stable during heat treatment. The mechanical properties and chemical composition of the workpiece are shown in Table 2.

3 Discussion and Results of the Experiment In this paper, a predefined model of the first order was used to model the cutting force function F (γ = 0°) and F (γ = 6°): F = C × v p1 × f p2 × a p3

(1)

Due to the relatively large number of variables, the space to be searched is huge. On the basis of tests and calculations already carried out, due to the faster finding of the optimal solution, limits were introduced in the search space. Thus, the positioning of possible solutions, coefficients for determining cutting forces F (γ = 0°), is localized at: 3200 ≤ C ≤ 4200 −1 ≤ p1 ≤ 0 0 ≤ p2 ≤ 1 0 ≤ p3 ≤ 1 The only difference between the modeling of the main cutting force function F (γ = 0°) and the cutting force function F (γ = 6°) is precisely in the values of these limits.

0,85–0,95

Mn

1,8–2,2

Cr 0,2–0,5

32

13.8

20–300°C

32

12.1

Thermal expansion coefficient 10−6 mm/(m·k) 350°C

20–100°C

Radna tvrdo´ca

20°C

13.3

55HRC

Material strength Rm

Thermal conductivity coefficient w/(m·k)

cca 780 N/mm2

20–200°C

max. 230 HB

Hardness (during delivery)

Physical properties (mechanical and thermal properties)

Si

0,1–0,4

C

Chemical composition (%)

14.3

20–400°C

P

14.1

31,5

700°C

Max 0,03

20–500°C

0,05–0,2

V

Table 2. Chemical composition and mechanical properties of the workpiece

14.2

20–600°C

S

14.6

20–700°C

Max 0,03 Genetic Algorithams Modeling of Cutting Forces 143

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Fig. 3. Measurement of the main cutting resistance of cutting in the turning process with CBN inserts [3]

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So, to determine the coefficients that figure in the formula for cutting forces F (γ = 6°), the following limits are used: 2500 ≤ C ≤ 3000 −0.5 ≤ p1 ≤ 0.5 0 ≤ p2 ≤ 1 0 ≤ p3 ≤ 1 Below are the results of the coefficient values for determining the main cutting force functions F (γ = 0°) and F (γ = 6°) obtained by genetic algorithm using MATLAB software. • Cutting force F (γ = 0°): C = 3488.816; p1 = −0.305; p2 = 0.445; p3 = 0.746. • Cutting force F (γ = 6°): C = 2630.066; p1 = −0.138; p2 = 0.833; p3 = 0.605. In Table 3, there are the output values of F (γ = 0°) and F (γ = 6°) that did not participate in the formation of the Function-File, i.e. genetic algorithm, which will later be compared with the output values obtained through the model. These output values are chosen randomly. The experimental processing modes and measurement results that will be used to form the genetic algorithm are shown in Table 4 for cutting forces F (γ = 0°) and for cutting forces F (γ = 6°). Table 5 shows a comparison of the output values for the cutting forces F obtained by the model and the output values that were not used to form the genetic algorithm, as well as their deviation.

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Table 3. Output values of the main cutting resistance F (γ = 0°) and F (γ = 6°) that did not participate in the formation of the genetic algorithm F (γ = 0°) [N]

F (γ = 6°) [N]

No.

v (m/min)

f (mm/rev)

a (mm)

1

160

0,05

0,10

42

27

2

90

0,20

0,50

290

310

3

120

0,10

0,22

94

84

4

120

0,045

0,22

55

50

5

80

0,10

0,22

111

78

6

120

0,10

0,70

211

178

Table 4. Values of the main cutting resistance F – experimental values, values obtained by the GA model, as well as deviations expressed in E [%] No. Variable factors

Main cutting resistance F (γ Main cutting resistance F (γ = 0°) = 6°)

v f a Fexp [N] F g.a. [N] E (m/min) (mm/rev) (mm) [%] 4,89

Fexp [N] F g.a. [N] E [%]

1

90

0,05

0,10

44

41,85

29

28,94

0,20

2

90

0,20

0,10

65

77,55

19,31 104

91,84

11,69

3

160

0,20

0,10

60

65,07

98

84,83

13,43

4

90

0,05

0,50

150

139,03

7,31 115

76,63

33,36

5

160

0,05

0,50

144

116,65

18,99 114

70,78

37,91

6

160

0,20

0,50

190

216,18

13,77 290

224,61

22,54

7

120

0,10

0,22

95

93,97

1,08

80

79,84

0,20

8

120

0,10

0,22

87

93,97

8,00

90

79,84

11,29

8,44

9

120

0,10

0,22

90

93,97

4,40

82

79,84

2,63

10

80

0,10

0,22

110

106,34

3,33

78

84,43

8,24

11

180

0,10

0,22

83

83,04

0,04

60

75,49

25,82

12

120

0,25

0,22

180

141,27

21,51 150

13

120

0,10

0,07

52

39,99

14

120

0,10

0,70

200

222,83

15

180

0,10

0,22

82

83,04

1,26

70

16

120

0,045

0,22

60

65,86

9,77

35

171,27

14,18

40

39,93

0,16

11,41 176

160,81

8,62

75,49

7,84

41,05

17,29

23,09

(continued)

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Table 4. (continued) No. Variable factors

Main cutting resistance F (γ Main cutting resistance F (γ = 0°) = 6°)

v f a Fexp [N] F g.a. [N] E (m/min) (mm/rev) (mm) [%] 17

120

0,25

0,22

180

141,27

18

120

0,10

0,07

40

39,99

Fexp [N] F g.a. [N] E [%]

21,51 150 0,02

Average deviation [%] →

43

171,27

14,18

39,93

9.90

7,13 13.15

Table 5. Comparison of the outputs for F obtained by the genetic algorithm model and the outputs that were not used to form the genetic algorithm model No.

Main cutting force F (γ = 0°)

Main cutting force F (γ = 6°)

Fexp [N]

Fexp [N]

F g.a. [N]

E [%]

F g.a. [N]

E [%]

1

42

35,11

16,39855

27

26,73

0,99062

2

290

257,65

11,15641

310

243,17

21,55698

3

94

93,97

0,03516

84

79,84

4,9557 17,8965

4

55

65,86

19,75454

50

41,05

5

111

106,34

4,20122

78

84,43

8,24587

6

211

222,83

5,60597

178

160,81

9,65504

Average deviation [%] →

9.5231

10.5501

4 Conclusion In the paper, it can be concluded that modern methods for modeling the processing process can be successfully applied in cutting processes, especially for cutting resistance with the help of the parameters used. During the training of genetic algorithms, the input data used are presented, and these include the input quantities: speed, displacement and depth of cut. The input quantities correspond to the output quantity, which in this case is the main cutting resistance during turning (F). The results obtained can be said to be acceptable. Taking into account the fact that, unlike some other types of artificial intelligence, specific coefficient values are obtained here, which can later be used to obtain different resistance values.

References 1. Chollet, F.: Deep learning v jazyku Python, Grada Publishing, a.s (2019) 2. Floreano, D., i Mattiussi, C.: Bio-Inspired Artificial Intelligence: Theories, Methods and Technologies. The MIT Press, London (2008)

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3. Tari´c, M.: Modelovanje procesa obrade struganjem termiˇcki obradenog cˇ elika, Doktorska disertacija, Fakultet tehniˇckih nauka, Novi Sad (2018) 4. Katalog HAHN+KOLB: Werkzeuge Maschinen Betriebseinrichtungen ATORN ORION (2015) 5. Vukeli´c, Ð., Tadi´c, B.: Rezni alati. FTN, Novi sad (2017) 6. Mádl, J., Holešovský, F.: Integrita obrobených povrchu z hlediska funkˇcních vlastností, str. 229. UJEP, FVTM (2008) 7. Miliki´c, D., Gostimirovi´c, M., Sekuli´c, M.: Osnove tegnologije obrade rezanjem. FTN, Novi Sad (2015)

Analysis of Some Parameters in Explosive Forming Darko Šunji´c1(B) , Stipo Buljan2 , and Eduarda Gomes3 1 Faculty of Mechanical Engineering, Computing and Electrical Engineering,

University of Mostar, 88000 Mostar, Bosnia and Herzegovina [email protected] 2 Federal Ministry of Energy, Mining and Industry, 88000 Mostar, Bosnia and Herzegovina 3 proMetheus, Instituto Politécnico de Viana do Castelo, 4900-348 Viana do Castelo, Portugal

Abstract. High-speed forming technologies include explosive forming, electromagnetic forming, and electrohydraulic forming. Explosive forming was most developed in the 50s of the 20th century for the needs of the development of the aviation industry and the space industry. Since that these technologies are still relatively unexplored, it is interesting to analyze certain parameters, and in this paper the emphasis is on the techniques of measuring detonation speed, deformations and pressure during explosive forming. Keywords: explosive forming · metal forming · technologies · parameters · pressure · deformation

1 Introduction High-speed deformation processing technologies experienced their most progress in the 50s of the 20th century, where it was stated that NASA funded more than 80 projects at one time [1]. High-speed technologies include explosive forming, electrohydraulic forming, and electromagnetic forming. Explosive forming, as the name suggests, uses explosives as a source of energy. Theoretically, in this way it is possible to achieve any amount of energy that is needed, and explosives as a source of energy are relatively cheap [2]. Explosive forming is successfully applied with deep drawing, expansion, hardening, relaxation of residual stresses, etc. Water is most often used as a medium in this technology, although other media in gaseous and solid state can also be used. It is interesting to notice that after changing the medium, water instead of air, the amount of explosives decreased by 80% [3]. Regarding the systems in which this technology can be used, we find open and closed systems, and the methods are contact and noncontact. Conventional technologies are characterized by deformation speeds of 10 m/s, while deformation speeds during blasting are from 100 m/s to 300 m/s and even up to 1000 m/s. Explosive forming is successfully used in the production of tank floors, satellite antennas with a large diameter (up to 5 m), various vessels, sailing ships, parts for spacecraft, etc. The great advantage of this technology lies in the fact that it is possible in a very simple way (sometimes even in one step) to get a finished product without © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 149–155, 2023. https://doi.org/10.1007/978-3-031-31066-9_16

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expensive tools, presses, or production lines. Depending on the number of pieces, the type of material and the load, the tools can be made of concrete, steel, cast iron, plastic and even cardboard. From the above, it is clear that this technology is used exclusively in individual or small-batch production, which is one of the disadvantages. Also, it is necessary to have a special place for the experiment, which is usually some kind of polygon, although it is possible to perform the experiment in anenclosed space, but then the sound effects are much more pronounced, so it is recommended that the experiments be performed outdoors. In addition to the above, it is necessary to hire qualified personnel, i.e., personnel specially trained to work with explosives.

2 Measurement of Detonation Velocity To determine the detonation speed of an explosive, the following items are required: test tubes, lead and steel plate, initiator, and detonating rod. The prepared test explosive cartridges are placed in the test tube and need to have touch in the tube. The length of the explosive charge in the test tube between the openings is called the gauge length of the explosive charge. It is necessary to prepare two pieces of detonation rod with a precisely determined detonation speed, one of which is 900 mm long and the other 600 mm long. The ends of the sticks are placed next to each other. The other ends are fed through holes in the tube into the explosive charge, the longer end of the rod being fed closer to the capsule. The connected parts go to the lead plate and the lead plate is connectedto the steel plate. The schematic representation is given in Fig. 1 [4].

Fig. 1. Dautrich method

The initiation of the capsule is done electrically or using a slow-burning stick. When the detonation wave reaches the rod, it will be transmitted to it. On its way through the pipe containing the explosive, the detonation wave will encounter a shorter rod that will also detonate. The collision of the shock waves of the two rods on the lead plate will create a notch. After detonation, the distance of the notch from the left end of the

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lead plate is measured, and from this the required detonation speed of the explosive is calculated according to Eq. 1. VE =

v·L 2a

(1)

where VE denotes the detonation speed of the explosive being tested in m/s, L is the measured length of the explosive charge in mm, a is the distance of the collision point of the detonation waves in mm and v is the detonation speed of the standard detonation rod in m/s. The test is performed three times and the average value is taken [5].

3 Measurement of Deformations in Explosive Forming The “pin contractor” method, i.e., the pin clamping method, involves a series of pins that are connected to a R-C circuit. R and C indicate a resistor and a capacitor, respectively. If the resistor is connected in series with the capacitor, this will gradually charge through the resistor until the voltage across it reaches the supply voltage. As the flexible pins are “hit”, the signals of the associated discharged RC circuits are recorded on the oscilloscope against the corresponding time base. Therefore, the time in which a certain radial location reached a known vertical position from rest is known, and it is possible to calculate the deformation profile and deformation rate. High-speed streak photography involves placing a line of reflective dots, symmetrical about the center, on a blank (Fig. 2). Reflecting points are also placed on the retaining ring in line with those on the blank to provide a measurement reference. A high-speed camera used in strip or oscillographic mode, i.e., without framing, is mounted at a tilt [6–8].

Fig. 2. High speed streak photography

4 Measurement of Pressure in Explosive Forming One of the ways of measuring pressure during explosive forming is by using a crusher system. The crusher system consists of a crusher, a copper roller, and a rubber for centering the copper roller. Crusher itself consists of a body, a piston, and a cover.

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Fig. 3. Inner and outer crusher system

The parts of the crusher systems shown in Fig. 3 are: 1 - crusher body, 2 - cover, 3 piston, 4 - copper roller, 5 - rubber for centering, 6 - copper lining. Crushers are divided into internal and external according to their position. The inner one is placed in the space where the pressure is created, and the outer one is placed in order that the gas pressure acts only on the face of the piston. At position 4 there is a copper roller that has the shape of a cylinder and is distinguished between: non-pre-kneaded, once pre-kneaded and twice pre-kneaded. For each series of non-pre-kneaded and one-time pre-kneaded copper rollers, the manufacturer creates tables that give the relationship between the maximum gas pressures and the residual height, i.e., the height of the roller’s kneading. The initial height of the roller h0 [mm] is the height of the roller before kneading. The remaining height hz [mm] is the height of the roller after kneading. The kneading height hg [mm] is the difference between the initial and residual height of the roller. For twice pre-kneaded rollers, no tare tables are supplied, but data on pre-kneading pressures and hardness coefficient are given. The pressure measured with an individual crusher is not considered in the following cases: i) when the crushing is less than 0.10 mm for pressures up to 1000 bar, and 0.15 mm for pressures greater than 1000 bar; ii) when the roller is crushed laterally; iii) when the copper roller got cracks or chamfered kneading surfaces more than 0.008 mm. If the bevel is not greater than 0.08 mm, the height of the roller equal to the mean value of the smallest and largest height is taken. When determining the pressures based on the measurements of two crushers, the arithmetic mean of the measured pressures of both crushers is taken as the measured pressure, if the individual values do not differ from each other by more than: 20 bar when measuring pressures of less than 500 bar; 4% when measuring pressures higher than 500 bar. In the case of non-pre-kneaded rollers, the measured residual height hz [mm] is also entered based on it, or based on the calculated kneading height hg [mm]. In the case of once pre-kneaded copper rollers, the maximum pressure is read from the tare tables, based on the residual height hz . For twice pre-kneaded copper rollers, the hardness coefficient is first calculated, which shows the increase in pressure in bars when the rollers are crushed by 0.01 mm: α=

P2 − P1 100 · (h1 − h2 )

pm = p2 + α(h2 − h3 ) · 100

(2) (3)

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The measured value of the maximum gas pressure is corrected due to the temperature of the copper roller for the difference between the temperature of the roller and the taring temperature of the roller. The correction is calculated according to Eq. 4. Pt =

−k · Pm · t 100

(4)

where h1 and h2 [mm] are the remaining heights of the copper roller corresponding to the pre-kneading pressures p1 and p2 , h3 is the residual height after the explosion, Pm is the measured value of the maximum pressure, read from the tare tables, t = tv − t0 is the difference between tempering temperature and temperature during taring of a series of copper rollers (if this temperature is not given on the taring table, it is assumed to be + 200 °C) and k is the coefficient of procedural pressure change when the temperature changes by 10 °C [9]. Crushers used to measure pressure can be 3 × 4.9 to 8 × 13 mm in size and are used to measure pressures up to 6000 bar. In addition to the crusher system, it is possible to use the pressure measurement technique using special strain gauges where the recorded deformation could be connected to the applied pressure and thus the pressure would be measured (Fig. 4). The sensitivity and dynamic characteristics of the strain gauges are the main limitation of this pressure transducer system. Although this technique is very simple, it is not often used or developed in detail due to commercially available membrane measuring tapes [10].

Fig. 4. Measurement technique using special strain gauges

When using a capacitive transducer (Fig. 5), a change in the capacitance of the transducer is recorded due to the pressure-induced deflection of the sensing element. By calibration, the relation between the applied pressure and the recorded change in capacitance can be obtained. The main problem that can occur with such transducers is the short duration of the recording time and the length of the transducer required to eliminate the possibility of interference of reflected shock waves from the free surface at the non-“shocked” end of the transducer [11].

Fig. 5. Measurement technique using a capacitive transducer

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In certain crystal structures with an asymmetric charge distribution due to loading, the directional deformation of the lattice results in a relative displacement of positive and negative charges, which leads to equal external charges of opposite polarity on the crystal faces. This effect is called the piezoelectric effect. The main advantage of the piezoelectric transducer (Fig. 6) is that the signal response followed the stress-strain curve and provided that the curve is linear for the operating range, the response of the transducer would be linear to the pressure [12].

Fig. 6. Measurement technique using a piezoelectric transducer

5 Conclusion Explosive forming technology is still relatively unexplored and as such is subject to the development of testing techniques for measuring certain parameters necessary to achievesuccessful analysis of experiments. Some of these parameters are deformation, pressure, detonation velocity and explosive mass. The measurements of all these parameters are developed for an individual experiment. The disadvantage of these techniques is that they are applicable for an experiment that is repeated under the same conditions, and thus, they are not reproducible or sufficiently developed for wider use. A review of the literature shows that technology has a lot of “space” for progress in this field, and this interest is proven by the large number of works published on this topic. Acknowledgment. This work was published as part of the scientific research project "The influence of detonation speed on the mechanical properties of materials during freeform explosive forming" number 05-35-2042-1/22 which was funded by the Federal Ministry of Education and Science.

References 1. Mynors, D.J., Zhang, B.: Applications and capabilities of explosive forming. J. Mater. Process. Technol. 125, 1–25 (2002) 2. Šunji´c, D., Buljan, S.: Application of explosives in metal forming. In: Karabegovi´c, I. (ed.) NT 2018. LNNS, vol. 42, pp. 144–148. Springer, Cham (2019). https://doi.org/10.1007/9783-319-90893-9_17

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3. Sunjic, D., Buljan, S.: Determining the amount of explosives in metal forming. In: Katalinic, B. (ed.) Proceedings of the 30th DAAAM International Symposium, pp. 0592–0598. Published by DAAAM International, Vienna, Austria (2019), ISBN 978-3-902734-22-8, ISSN 17269679. https://doi.org/10.2507/30th.daaam.proceedings.080 4. Su´ceska, M.: Eksplozije i eksplozivi: njihova mirnodopska primjena, Brodarski institut (2001) 5. Šunji´c, D., Buljan, S.: Determination of velocity of detonation using dautrich method. Adv. Technol. Mater. 43(2) (2018). https://doi.org/10.24867/ATM-2018-1-006 6. Fye, P.M., Eldridge, F.E.: Diaphragm gauge studies of underwater explosion. Compend. Underwater Explosion Res. 3, 517–594 (1951) 7. Hobson, G., Amini, E.: Fundamentals of an explosive forming machine. Int. J. Mach. Tool Des. Res. 4(2), 73–90 (1964) 8. Smaill, J.S.: Pressure instrumentation in explosive forming: the non-linear transient displacement of a circular plate. University of Cunterbury (1984) 9. Standard narodneobrane, Maksimalnipritiscibarutnihgasova-mjerenjekrešernimsistemom, Službenivojni list br. 5. (1985) 10. Milligan, R.V.: The gross hydrostatic-pressure effect as related to foil and wire strain gages. Exp. Mech. 7(2), 67–74 (1967) 11. Grabowsky, W.R., Durran, D.A.: Gauge for measuring impulsive pressure in a container subjected to large time-varying applied voltages. Rev. Sci. Instrum. 39(1), 35–39 (1968) 12. York, T.M.: Stress dynamics in high speed piezoelectric pressure probes. Rev. Sci. Instrum. 41(4), 519–521 (1970)

Design and Manufacturing of Conformal Cooling Channels for Injection Molding: A Review Janez Gotlih(B) , Timi Karner, Rok Belšak, Mirko Ficko, Lucijano Berus, Tomaž Brajlih, Snehashis Pal, and Miran Brezoˇcnik Faculty of Mechanical Engineering, University of Maribor, Smetanova Ulica 17, Maribor, Slovenia [email protected]

Abstract. It has been shown that conformal cooling in injection molding has the potential to replace conventional cooling due to its many advantages. The overall quality of the injection molding process is closely related to heat removal from the product and the mold, which is most uniform and efficient with conformal cooling. The disadvantages of conformal cooling are mainly in the manufacture of the mold, which is more expensive and time-consuming, which also affects the production of spare parts. To examine the current state of conformal cooling, an overview is given, organized according to the life cycle of the injection molding process. The main topics covered are process simulation, mold design and optimization, mold manufacturing, injection molding process control, and final quality evaluation based on product quality and financial benefits. Finally, the most promising solutions and their limitations are presented. Keywords: conformal cooling · injection molding · tool design · tool manufacturing · simulation · optimization

1 Introduction Injection molding is a polymer processing method based on heating and cooling of the polymer. During the process, not only the polymer but also the injection mold is subjected to heating and cooling cycles. One of the main tasks of the mold is to take the melt at a temperature of 200 °C to 300 °C and cool it as quickly as possible to the temperature at which the product is ready to be ejected from the mold. Therefore, one of the main problems in injection molding is heat extraction from the product and the mold [1]. The temperature of the mold and the melt are important factors in this process. From a product quality standpoint, the temperature difference between the mold and the melt should be as small as possible, and from a production standpoint, the temperature difference should be as large as possible. The compromised nature of the process is a challenge to maintaining a successful process and indicates that a high degree of control is required. Better process control is provided by conformal cooling, which is enabled by advances in additive manufacturing [2]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 156–169, 2023. https://doi.org/10.1007/978-3-031-31066-9_17

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To provide an overview of recent advances in the field, this article examines the latest methods and techniques reported on the design and fabrication of conformal cooling channels in injection molding. The article is organized according to the injection molding life cycle and the sections can be summarized as follows: Sect. 1 contains an introduction that focuses on the key facts related to the topic of this article. Section 2 presents process simulation and mathematical modeling methods for mold design and process optimization. Section 3 presents mold fabrication techniques, followed by experimental verification of simulation results, product quality evaluation, and financial aspects of the overall process. Section 4 concludes the review with a summary of the most promising solutions and their limitations.

2 Process Simulation and Modelling Today, the development of a new product is no longer conceivable without the use of CAD/CAM/CAE software for product lifecycle management. Thus, even in the development of the injection molding process, there is no way around the use of CAE software. CAE software is used to gain insight into the injection molding process, improve the shape and layout of cooling channels, evaluate the efficiency of the cooling system, shorten cycle time, improve product quality, and reduce the cost of the process [3–6]. Studies can be conducted under different process parameters and boundary conditions, and the effects of different polymers and molding materials can be investigated. The most used CAE software for injection molding simulation in the literature are Moldflow, Moldex3D, Ansys and Sigmasoft. In [3], a parametric optimization of the position and shape of a conformal cooling channel (Fig. 1) for injection mold design was performed using the Moldflow software package. The main objective of the optimization was to reduce the cooling time; the second objective was to achieve an optimized homogeneous temperature distribution over the entire mold surface. In [4], two maraging steel injection molds with two different conformal cooling channels were designed and the differences between the injection molds in terms of cooling time, temperature difference between the parts, temperature difference on the mold surface and warpage of the parts were numerically investigated using Moldex3D simulation software. In [5], Ansys was successfully used for transient thermal analysis of the thermal response of rapid mold heating and cooling for hot and cold runners, and to determine the effects on mold heating and cooling efficiency and injection molding cycle time. Using Sigmasoft simulation software [6], different mold insert materials and three cooling system designs were investigated for their effects on hot spot cooling in the product: a copper pin cooling system, a conformal cooling channel system, and a biomimetic blood vessel-like channel system. It was found that the blood vessel-like channels cooled the main hotspot more efficiently than the conformal cooling system and the copper pin cooling system, and that cycle time can be reduced the most by using the blood vessel-like structure in combination with a thermally conductive mold insert. CAE software is based on mathematical models that predict process parameters such as heat fluxes, cycle times and product quality. Park and Dang [7, 8] developed a mathematical model of the cooling process in which the channel arrangement was represented

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by geometric parameters. The model enabled the development of a smart mold with spiral conformal cooling channels on the thicker walls of the product for efficient cooling of hot spots. In [9], Park et al. presented a method to develop optimal cooling channels in terms of cooling efficiency and manufacturability. The method combined analytical formulas to evaluate cooling time and CAE simulations. In addition, parameters such as pressure drops, cooling channel exit temperatures, and exergy losses can be determined through simulations. In [10], simulations showed that the pressure drops and the exergy losses in the conformal cooling channel are greater than in the classical cooling channel.

Fig. 1. Temperature of the cooling medium for the initial (left) and optimized (right) close-contour cooling system (Reprinted from [3]).

2.1 Injection Molding Process Optimization Once the mathematical models are created, they can also be used to optimize the injection molding process. The injection molding process has many variables by which it can be improved, so heuristic algorithms have been successfully used for this purpose [12]. The goal is usually to shorten the cycle time and reduce production costs. However, product quality must also be considered, which is best improved by increasing cooling time, which ultimately leads to lower productivity [13–16]. In a comparative study, Abbès et al. [17] attempted to increase productivity by reducing the cycle time. Using simulations, they showed that using a hybrid steel/copper alloy mold insert with high conductivity and conventional cooling channels can reduce cycle time by more than 50%, while using a hybrid steel/steel mold insert with conformal cooling channels can reduce cycle time by more than 65%. MohdHanid et al. [18] employed response surface methodology, genetic algorithm and firefly swarm optimization and compared the optimization methods for straight drilled and milled groove square shape conformal cooling channel shapes. Based on the experimental results, they showed that the performance of milled groove square shape conformal cooling channels could be improved by the optimization approach. Huang et al. [11, 19] used the Taguchi method and gray correlation analysis to optimize the injection molding process and used a

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Fig. 2. Overall experiment flow chart. (Reprinted from [11]).

multi-criteria quality analysis to find the parameters that ensure uniform temperature distribution and reduce product deformation (Fig. 2).

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Fig. 3. Additively manufactured TPMS structures: (a) Various TPMS shapes (50% volume fraction). (b) Various volume fractions (CYL-G type TPMS). (c) Microscopic image of the TPMS structure (CYL-G type TPMS with 50% volume fraction). (Reprinted from [20]).

Fig. 4. Conformal cooling channel design guidelines. (Reprinted from [21]).

2.2 Mold Design The design of a mold is crucial to ensure optimal conditions for the injection molding process and the quality of the products. To ensure the latter, cooling performance is particularly important. For conformal cooling channels enabled by additive manufacturing, the shape and layout of the channels are the main research targets [22]. Circular, rectangular, elliptical, elongated, and triangular shapes of the channels have been studied [23]. In addition, the channels can contain body-centered cubic grids, which have been shown to have the potential to increase heat dissipation and decrease cycle times [24]. Oh et al. [20] used microcellular cooling structures instead of typical cooling channels

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(Fig. 3) and showed that cycle time can be reduced by 40% by integrating microcellular cooling structures into the mold. As a guide for tool designers, Jahan and El-Mounayri [21] presented a table of conformal cooling channels for cooling cylindrical and conical product features (Fig. 4).Another advantage of additive manufacturing is the almost unlimited design freedom of the cooling system. This provides the opportunity to consider and compare different cooling channel designs [25–28]. Simple zigzag, spiral, and isocontour conformal cooling channels have been developed to match the product geometry [29, 30]. To maximize the benefits of conformal cooling, even complex product-specific conformal cooling channels have been developed and combined with materials with high thermal conductivity [31]. Since the design of conformal cooling channels requires a lot of experience and time, automatic algorithms for the layout of conformal cooling channels have been developed. Torres-Alba et al. [32] proposed a discrete multidimensional method that autonomously designs a cooling system using a nondeterministic genetic algorithm. Li et al. [33] developed a topology optimization approach to design a conformal cooling system. Chung [34] used a gradient-based algorithm and a robust genetic algorithm to determine the optimal layout of the cooling channels. Gao et al. [35] used a machine learning-based design method based on surrogate modeling and artificial neural networks to design a conformal cooling system and found that they can achieve much lower temperature variance and pressure drop of the coolant with the proposed method compared to conventional conformal cooling.

3 Mold Manufacturing Rapid manufacturing techniques for injection molds were studied in detail by Kuo et al. [36]. Low-cost direct and indirect mold manufacturing methods were found to be suitable to produce injection molds with integrated conventional cooling channels, and the effects on overall production cost, cooling time, and flexural strength were studied.

Fig. 5. Tool core base after hardening with reference features for SLM (a), all four tool cores prepared for hardening after completed SLM upgrade (b). (Reprinted from [37]).

Additive manufacturing technology is the key to producing an injection mold with conformal cooling channels. Minguella-Canela et al. [38] used selective laser melting

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technology to produce a replacement for the original insert of a mold. The new insert allowed cooling times to be reduced by up to 8% while maintaining all other relevant mold properties, resulting in significant cycle time and cost savings during the injection molding process. Additive manufacturing process parameters have been shown to have important effects on injection molds produced with additive manufacturing [39, 40]. Mazur et al. [41] investigated the fatigue strength of conformally cooled inserts produced by selective laser melting (SLM). The results of the mechanical tests showed that the additively manufactured inserts had lower mechanical properties than the conventionally manufactured ones; however, the mechanical properties increased significantly after residual stresses were relieved by heat treatment. To combine the best of both worlds, conventional and additive manufacturing, the concept of hybrid tooling was introduced, where the base of the mold insert is produced by conventional machining and the conformally cooled part of the insert is then upgraded to the machined surface by additive manufacturing [37, 42] (Fig. 5). Chan et al. [43] proposed a time-efficient method for manufacturing mold inserts using a hybrid additivesubtractive powder bed melting process to reduce the manufacturing and post-processing time. Chan et al. [44] pointed out the importance of heat treatment of the additively manufactured mold and found that an age-hardening treatment directly after fabrication gave the best combination of hardness, tensile strength, and ductility of the fabricated mold. Kuo et al. [45] also pointed out that optimal heat treatment can prevent coolant leakage and shorten the manufacturing time. Since large molds are not easy to fabricate using the well-known metal additive manufacturing technology, a cost-effective method for fabricating large epoxy composite molds with wax conformal cooling channels was presented in [46]. In addition, the thermal conductivity of the mold can be improved by adding fillers [47]. It was also found that in some cases, the combination of highly thermally conductive materials can facilitate the additive manufacturing of conformally cooled molds [48]. In [49], the advantages and disadvantages of epoxy molds for injection molding with a focus on epoxy composites, increasing productivity through conformal cooling, reducing mold costs through waste reuse, and emerging Industry 4.0 technologies for smart manufacturing and mold design were reviewed. The fabrication of injection molds by selective laser melting also has some advantages and disadvantages arising from the fabrication process itself. Liu et al. [50] found that cooling channels fabricated by selective laser melting have lower dimensional accuracy and higher surface roughness compared to drilled channels, resulting in lower flow rate and poorer cooling performance. Kuo et al. [51] found that to improve the roundness of conformally cooled channels fabricated by the fused filament manufacturing process, the printing temperature, fan speed, printing speed, and traverse speed should be adjusted. Wen et al. [52] investigated the microstructure, hardness, and especially corrosion behavior of samples fabricated by selective laser melting. They found that the samples prepared by selective laser melting have finer cellular microstructure and anisotropy in hardness, but the hardness values are 20% higher than those of cast samples. In terms of corrosion, the samples prepared by selective laser melting have better corrosion resistance but have deeper corrosion holes than cast samples. Lu et al. [53]

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compared the residual stresses between conventional cooling and conformal cooling channels and found that the residual stresses were lower with conformal cooling than with conventional cooling with baffles. 3.1 Experiments and Verification of Numerical Results The performance of conformal cooling has been verified by experiments, which generally show good agreement with the numerical results (Fig. 6) [47, 54]. The most common approach for experimental evaluation is process and product quality testing. Kitayama et al. [55] confirmed through numerical and experimental results that conformal cooling shortens cycle times and reduces warpage. Goktas and Guldas [56] found experimentally that the use of conformal cooling channels reduced the cooling time by 22% and observed that the warpage of the manufactured products decreased by almost 50%. Papadakis et al. [57] and Kirchheim et al. [58] used a thermal imaging camera to measure the actual temperature distribution during the injection molding process, which agreed with the numerical results. 3.2 Product Quality In terms of product quality, warpage, sink marks, flow lines, surface deformation, weld line formation, short shots, and jetting are considered [22]. Shrinkage of plastic products has been shown to be higher when a solid mold with a straight cooling channel is used, compared to a laminated steel mold with a conformal cooling channel and a soft mold with a conformal cooling channel [59]. To reduce warpage, a conformal cooling channel system with a solid mold has been shown to have significant potential [60]. 3.3 The Financial Aspect For the injection molding industry, the financial aspect is the most important [61]. In this context, it is important to evaluate the impact of conformal cooling channels on the cost efficiency of the whole process. Combrinck et al. [62] investigated the manufacturing cost and lead time of a conventionally and an additively manufactured insert. They found that the conventionally manufactured insert pays for itself after fewer injection molding cycles than an additively manufactured insert due to its lower manufacturing costs, but that at high volumes the additively manufactured insert becomes more profitable due to its shorter cycle times. It has also been shown that the choice of tooling material can reduce costs, as it reduces production costs and cooling time [63–65]. In [66], the effects of the cooling medium, polymer material, and mold material on the financial aspect of the process were studied. It was found that cooling water with ultrafine air bubbles is the best cooling medium and that the mold material has a greater impact on cooling efficiency than the cooling medium. Based on the total production cost of the injection mold and the cooling efficiency, an epoxy resin mold with 41% aluminum powder was found to be the optimal mold material, since a saving of about 24% of the total production cost was achieved compared to an injection mold made of commercially available materials.

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Fig. 6. Comparison of the predicted and actual cooling time of injection molded products. (Reprinted from [47]).

4 Conclusion This review article provides an overview of recent advances in the field of conformal cooling in the injection molding process. The article highlights the motivation for using conformal cooling and focuses on the most important facts about the subject. The article is organized according to the life cycle of the injection molding process. First, process simulation and modeling techniques are discussed with an overview of commonly used CAE software and its application benefits. The most advanced solutions enabled by numerical analysis are the automatic design of the cooling system and the use of customized channel shapes with integrated cooling structures that improve cooling performance. Mold manufacturing processes are then presented, and it is found that additive manufacturing processes outperform conventional processes in terms of process performance, product quality, and, at high production volumes, also financially. The advantages of rapid manufacturing processes are also discussed. It should be noted that there is not yet a simple solution for the design of the injection molding process. Along the process life cycle, many decisions must be made that have far-reaching consequences and lead to different process results. In addition, many of the decisions are contradictory, which makes decision making very complex. Continuous research is needed to increase knowledge in this area and enable a more sustainable injection molding process. Acknowledgement. The authors thank the Slovenian Ministry of Higher Education, Science and Technology and the Slovenian Research Agency (Research Core Funding No. P2-0157) for financial support that made this work possible.

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Mind Maps for Key Points of a Reverse Engineering Project Svitlana Ivanova1(B) , Lubomir Dimitrov2(B) , Viktor Ivanov3(B) , Galyna Urum1(B) , and Olena Olefir1(B) 1 South Ukrainian National Pedagogical University Named After K.D. Ushynsky, Odesa,

Ukraine [email protected] 2 Technical University of Sofia, Sofia, Bulgaria 3 Odesa National Maritime University, Odesa, Ukraine

Abstract. The choice of the option of further use of damaged equipment - replacement or repair, is always a difficult task. Rapid technological advances have made it imperative to explore the redesign option. The movement towards a circular economy has added the option of repurposing. It is proposed to compare these options using the diagram Damage - Cost - Functionality - Time. In this diagram, each of the options corresponds to a geometric figure. The Decision Rule for choosing the type of project comes down to choosing a geometric figure. The proposed diagram can be viewed as a mind map. Another key point of a reverse engineering project is the assessment of the degree of equipment damage. The combined use of the DSM matrix and the morphological matrix of damage made it possible to visualize the search for the cause of damage and the degree of damage. Keywords: reverse engineering · redesign · repurposing · mind map · DSM matrix · morphological map of damage

1 Introduction Terms with the “re” prefix are becoming more and more popular: remanufacturing, repair, reverse engineering, redesign, repurposing. This is due to the requirements of the transformation of the economy into: green, circular, decarbonization, zero waste, digitalization, etc. [1]. To solve reverse engineering problems, approaches and knowledge from the field of project management, technology, engineering, economics, and heuristics are used. What is new is the use of pattern recognition theory. Initially, pattern recognition theory found application in software reverse engineering [2]. Then the approaches tested by programmers began to be applied to digitized surfaces of 3D objects [3]. In project management, decisions are usually based on the analysis of diagrams, flowcharts, and network diagrams. Is it possible to find such a graphical presentation of the initial data so that the diagram is a pattern, and artificial intelligence can make a decision on choosing a project option? Let’s consider all aspects of this problem. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 170–181, 2023. https://doi.org/10.1007/978-3-031-31066-9_18

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Not only the term reverse engineering, but other terms are used for similar types of projects. First of all, these are the terms redesign, remanufacturing, repurposing. Figure 1 shows the number of Google searches from 2004 to the present for each of these terms. We see that the surge in reverse engineering requests falls in 2004–2006, and then the number of requests decreases. The number of requests for the term remanufacturing is also decreasing. At the same time, the number of requests for the term redesign has slightly increased. We believe that this is due to the fact that the same project is given different names. What was previously referred to as reverse engineering and remanufacturing is now more commonly referred to as redesign. In this regard, we will indicate what we mean by reverse engineering.

Fig. 1. The number of Google searches from 2004 to the present for terms: reverse engineering, redesign, remanufacturing, repurposing.

The initial stage of reverse engineering is decoding faulty equipment, which consists in analyzing the technical condition and identifying its assemblies [4]. After this, it is necessary to make a decision about variants: purchase new, purchase assemblies, repair, and redesign or search for alternative use of equipment. The number of requests for the last option - repurposing is constantly increasing (see Fig. 1). The repair and manufacture of machine assemblies, which can be copies of damaged ones, is the task of reverse engineering too [5]. Thus, we believe that the concept of reverse engineering is the most general and includes: redesign, remanufacturing, repurposing. Four main aspects of reverse engineering are identified: failure analysis; cost; the difficulty of the operation; market changes and obsolescence [6]. The authors specifically distinguish between the concepts of failure analysis and operation difficulty. Among the main aspects, the DFA (Design for Assemblies) method is not indicated, although the proposed method includes it as an integral part. Note that redesign is also included as part of reverse engineering. Reverse engineering necessarily includes a heuristic component. A reverse engineering methodology based on the TRIZ method was developed, which made it possible to find unexpected solutions in various fields. Note that the authors solve the problem of alternative use of various products and call it reverse engineering [7]. The need for a heuristic stage - generating ideas is also indicated in the publication [6]. Reverse engineering finds applications in the most unexpected areas. So, due to rapid technological progress, it is difficult to ensure the compatibility of mechatronic

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systems when repairing a car. Therefore, often the design and manufacture of blocks for automotive electronics is a reverse engineering task to ensure the compatibility of new equipment with the old one [8]. Much attention is paid to the DFA method, which provides a clear separation of the product into assemblies. This facilitates the replacement of damaged or obsolete assemblies, as well as the organization of repairs. It is proposed to design new products based on the DFA principle in order to facilitate future redesign. Note that the authors combine reverse engineering and redesign into one methodology [9, 10]. The importance of a modular system of equipment is also noted, which allows the functionality to be divided into separate areas, each of which is provided by autonomous assemblies. This, in turn, makes it possible to replace such assemblies with products from other manufacturers. The article raises the most common question of reverse engineering, what to do with a damaged product - replace it with a new one or repair the old one [11]. The same question “When the equipment has reached its life expectancy, or its practical usefulness what do we do, Repair or Replace?” is solved in the example of the operation of water treatment equipment. The main steps necessary for making a repair decision are given: define a present physical condition, provide an equipment survey, cite potential improvements, a proposal for implementation improvements, and pilot testing. In the case of purchasing new equipment, these stages are engineering review for new equipment, new equipment choice and costs, pilot testing, cost for transportation and installation. [12]. The term “Decision Rule” is quite correctly used when deciding on the further use of equipment [13]. The use of the “Replace/Repair Decision Rule” creates the basis for the algorithmization and automation of the reverse engineering project. The question of further use of damaged equipment or obsolete equipment does not have a clear answer. It is assumed that general recommendations cannot be given and in each individual case they are looking for the right solution based on specific circumstances [12]. General recommendations are given in the case that products are made accordingly to a DFA method, but not all products are designed according to these rules [11]. A dependency has been proposed for the decision rule, but it only applies to process equipment [13]. The objective of the work is to find design parameters that would allow us to formulate a decision rule applicable to various types of products. As well as the search for such a form of representation of the decision rule, this would allow visualizing the solution options in the form of a mind map. The decision on the further use of the equipment largely depends on the degree of damage. The objective of the article is also to visualize the degree of damage to the product to support decision making.

2 Types of Reverse Engineering Projects A classification of reverse engineering projects is proposed depending on the degree of damage to the product, the requirements for the functionality of the restored product, as well as the budget of the project, and the time it takes to complete [4]. Each of the project types received a special name. Buying new equipment to replace the damaged one is an “original” project. Replacement of product assemblies - “original

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assemble”. Designing and manufacturing a product with better functionality - “redesign”. In case of serious damage to the product, it is possible to use it, but with limited functionality – “repurposing”. For example, a heavily worn out-of-date design bus can be used as a mobile cafeteria [4]. Let’s use this classification of projects. The choice of the option for further use of the equipment is associated with the involvement of specialists from various fields of knowledge, additional calculations, and lengthy discussions. The whole process is stretched in time, which leads to additional costs. Is it possible to find such key parameters for each of the listed types of project, so that by external formal, easily identifiable signs, it would be possible to determine what type of project is needed in this case? Any reverse engineering project begins with determining the degree of damage and the causes of equipment failure. This is a complex task that always contains elements of heuristics. Once this issue has been resolved, the allowable maximum costs and time of the project are considered. Typically the project customer can specify these restrictions quite clearly. The management of the enterprise (project customer), together with the engineers and technologists of the project team, needs to decide on the functionality: the same improved or limited. Considered parameters of the project are depicted on the diagram, which is a rectangle, all sides of which are axes (Fig. 2). The value of the time axis was given to the bottom side of the plot rectangle. One side will represent the axis of damage. The other side is the functionality axis. The top side is the cost axis. Damage is displayed as a percentage. The lower left corner of the rectangle corresponds to complete destruction. The upper left corner of the rectangle corresponds to the absence of damage. The maximum costs (upper right corner of the rectangle) correspond to the cost of similar new equipment, including the cost of its delivery and installation. The smallest amount of costs (upper left corner of the rectangle) corresponds to disposal costs. The lower left corner of the rectangle corresponds to the time to replace the equipment assemblies, provided that these assemblies are available in the enterprise’s warehouse. The maximum time is set based on the needs of the technological process of the enterprise. The maximum functionality corresponds to the existing product functionality (upper right corner of the rectangle). Minimum (lower right corner of the rectangle) means not being able to perform any functions. As you can see, the boundaries of variation of all four parameters are determined regardless of the design of the product, the specifics of the technological process, and economic indicators. The limits of variation are clearly defined and applicable to a wide variety of specific cases. Consider the first option - “original”. In the case of complete destruction of the product, the degree of damage to 100% is the lower left corner. There is no possibility of partial operation of the product. In the case when it is necessary to restore the full functionality of the product, there is also no time spent on making a decision - everything is obvious, and it needs to buy new equipment urgently. On the time axis, this is the lower left corner. The costs correspond to the purchase of new equipment and the functionality of this equipment is the same as that of the damaged product. That is, it is the upper right corner for both the cost axis and the functionality axis. Thus, in this simplest case, the diagonal of the rectangle (yellow line) is a visualization of a project to purchase

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Fig. 2. Project type - “original”

new identical equipment to replace the damaged one. The following source data also correspond to this version of the project. Damage may not be 100%, but rather serious (50% or more), in this case, it may take more time to make a decision and the equipment is still capable of performing some functions. The visualization of this case will be a triangle (blue lines) its vertex, as in the previous case, is the upper right corner. Thus, in the general case, the visualization of the need to purchase new equipment, identical to the existing one, is the configuration of the diagram (Damage - Cost - Functionality Time) a triangle that can degenerate into a diagonal. Consider a variant in which one or more assemblies are damaged, the degree of damage is from 20% to 50%. A lot of time to make a decision, in this case, is not required. It is quite obvious that one or more assemblies need to be replaced. This is a project - “original assemble”. There is also no need to spend a lot of time on design work. Costs correspond to the cost of one node plus delivery and installation. These costs are much less than the cost of new equipment and usually do not exceed 30%.The functionality of the equipment can be completely restored. The diagram configuration of the described embodiment is given by the blue lines. If the costs are somewhat higher and it took time to resolve logistics issues or assembly problems, then we get a yellow configuration. The configuration when replacing the assembly is close to a trapezoid. Moreover, the lower base is a diagonal or a straight line located close to it (Fig. 3). The impetus for the redesign project is significant damage. The result of such a project is higher functionality, which takes a lot of time. Functionality is usually higher than that of an existing product. It takes a lot of time to develop a new design. As a result, it may take more time than the maximum allowable value originally specified by the customer. This is offset by higher equipment performance to catch up on downtime. Typical for this type of project is the configuration in the form of a triangle, the base of which coincides with the bottom side of the rectangle (blue lines). Damage may

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Fig. 3. Project type - “original assemble”

not be complete and design time may be within tolerance. Then the configuration will correspond to the yellow triangle. The redesign project requires a lot of design time and always has a heuristic component (Fig. 4). The most interesting version of the project, from the point of view of heuristics, is “repurposing” (Fig. 5). There are many options for further use of equipment, and for each of these options, the design of a modified design is required. The repurposing option is also considered for significant damage to the product. If the costs of purchasing new equipment and upgrading are too high for the customer, it is advisable to find another application for the product that retains limited functionality. The functionality of the new product is planned to be much less than that of the existing product. It takes a lot of time to develop a new design. But the repurposing project takes less time to complete than the redesign project because the required functionality is much lower. The costs should also be significantly less; otherwise, the repurposing project does not make sense. This type of project is characterized by a configuration in the form of a quadrilateral, one of the vertices of which coincides with the lower left corner of the diagram or is located close to this point. In the extreme case, the quadrilateral turns into a point coinciding with the lower left corner of the diagram - this is the disposal of completely unusable equipment.

3 Damage Degree and Cause of Failure As noted above, the starting point of any reverse engineering project is to determine the degree of damage and the causes of product failure. The cost of equipment and components is usually known. The time required for repair and redesign can be estimated from previous experience. Thus, the most difficult factor to assess is the degree of damage. Moreover, not only the degree of damage to each specific element and the total

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Fig. 4. Project type - “redesign”

Fig. 5. Project type - “repurposing”

number of elements in the product is important, but also the nature of the interaction of damaged elements. If the elements of one assemble are damaged, then it is easy to replace it. If a large number of elements belonging to different assemblies are damaged, then a complete replacement of equipment may be better than repair. In order to consider the issue of alternative use, it is necessary that some nodes remain undamaged.

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We were able to visualize the types of reverse engineering project, let’s try to visualize this procedure. To describe the interrelations of machine elements, a design structure matrix (DSM) is used. To analyze the interrelations between the elements of the gearbox, a DSM matrix was built [14, 15]. This matrix allows you to establish groups of elements between which there is a close interrelation. For example in a car, these are units: engine, transmission and wheels. The morphological map of damage is used to find the cause of the damage [4, 16]. These two matrices can be combined as shown in Fig. 6.

Fig. 6. DSM matrix & morphological map of damage

The first row and the first column contain the element numbers. The symbol & denotes pairs of elements that interact. Inside the rectangles marked with bold lines are the elements included in the assembly. Elements are divided into four groups, depending on the degree of damage. Damaged elements that require replacement are given in red, heavily damaged elements that can be repaired in blue, elements with minor damage that can be continued in operation in green and undamaged in yellow. The mating surfaces of the elements are also marked with a certain colour, taking into account the degree of damage. Such a combined DSM-morphological map, from our point of view, gives a more visual representation of the possible causes of the machine destruction. Using this matrix, you can visualize the process of damage propagation in the machine. Element 7 interacts with elements 5, 8 and 9. We assume that the number of the element that translates the damage corresponds to the column number, and the number of the element that is damaged is the row number. Element 7 damages the mating surfaces of elements 5, 8 and 9. Thus, we mark with the ↑ symbol the cells corresponding to column 7 and rows 5, 8 and 9. The mating surfaces of elements 7–5, 7–8, 7–9 are to be repaired (blue colour). Element 8 transmits damage to elements 8 and 9. The mating surface of elements 8 and 6 is to be repaired (blue colour). The mating surface of elements 8 and 9 is damaged allowing to continue operation (green colour). Element 5, which received damage due to interaction with element 7, in turn, transmits damage to element 6 (blue colour). Element 6 acts on elements 4 and 8. The degree of damage to the mating surface of elements 6 and 4 corresponds to green. The mating surface of elements 6 and 8 transmits damage from elements 6 to 8, and, as noted above, from element 8 to 6.

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Such a visualization of the interaction of product elements and the degree of their damage is a convenient tool for finding the root cause of a machine failure. Element 4 has one damaged surface, element 5 has two damaged surfaces, one is green and the other has a greater degree of damage - blue. Element 6 has three damaged surfaces two blue and one green. Element 8 also has three damaged surfaces - two blue and one green. Finally, element 7 has three damaged surfaces requiring repair. Element 7 has the most damage, interacts with the other two most damaged elements 6 and 8 and can be considered as the root cause of the destruction. A tool has been obtained to determine the cause of product failure, damaged elements and assemblies. And, no less important, the assemblies remain undamaged. In this case, the assembly containing elements 1–3 can be used in the repurposing project, if the purchase of new equipment is not planned. The proposed compatible DSM-morphological map can be used as a mind map by the project team. Numerical evaluations are provided for four types of reverse engineering projects. The limits of variation of parameters typical for each type of project are indicated: damage, time, cost, functionality (Table 1). In order to make it possible to represent the differences between the types of projects in numerical form, we introduce the concept of the evaluation function Q. Q = Rd · Du · Ce · Fu, where Rd - Rate of Damage, Du – Duration, Ce - Cost estimate, Fu – Functionality. Smaller values of the parameters are multiplied among themselves and get the lower limit of the function. Multiplying large parameter values gives the upper limit of the function. The proposed function makes it possible to establish numerical differences between three types of projects. The “original assemble” project corresponds to a function value from 0,001 to 0,04. Values in the range of 0,04–0,15 are typical for the “original” project. The “redesign” project has the highest function values. The “repurposing” project cannot be recognized by the proposed function. The function values for a given project overlap with the “original assemble” and “original” projects. Table 1. Factors and variable levels of factors Signs of recognition Project types Original Original assemble Redesign Repurposing

Damage

Time

Cost

Functionality

0,81,0 0,10,4 0,50,8 0,70,9

0,050,15 0,10,3 0,71,0 0,50,8

1,0

1,0

0,10,4 0,71,0 0,10,3

0,80,9 0,91,1 0,10,5

Q

Risk

Qr

0,040,15 0,0010,04 0,220,88 0,0040,11

0,030.05 0.060.10 0.100.20 0.100.30

0,040,14 0,0010,035 0,200,70 0,0040,08

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The implementation of any project is fraught with risk - R. The risks of “original” and “original assemble” projects are relatively low. The “redesign” project comes with a lot of risk. And the most risky is the “repurposing” project, although it involves the lowest costs. Evaluation function modified by Qr. Qr = Rd · Du · Ce · Fu · (1 − R), The upper and lower limits of the function Qr are obtained by analogy with the algorithm described above. The table shows that the “original”, “original assemble” and “redesign” projects are still clearly recognizable. The “repurposing” project has function values that overlap with those of the “original assemble” project. With the “original” project, the values partially overlap. To recognize a “repurposing” project, you must additionally use the product of the two parameters Damage and Cost. The specified values of the Damage, Time, Cost, Functionality parameters are quite approximate and can be refined for a specific engineering industry based on information about completed projects for Redesign and Repurposing. For some parameters of Original and Original assemble projects, large companies have regulatory documentation. Taking into account the specifics of the equipment, the evaluation function and additional conditions for recognizing the Repurposing project can be refined. A reverse engineering project can be considered as a set of heuristic, metrological, design and calculation procedures [17]. In such a statement, after a set of metrological procedures, including the study of damage to individual elements, additional procedures must be performed. These are the procedures for forming a DSM matrix, morphological map of damage, a combined matrix, determining the assemblies included in the product, searching for the causes of failure, determining the assemblies that require replacement and undamaged assemblies. After evaluating the economic parameters of the project and clarifying the customer’s requirements, the procedures for constructing a table with the boundary values of the parameters, calculating the evaluation function, constructing the Damage - Cost - Functionality - Time diagram, and selecting the project type are performed.

4 Conclusion We believe that the key points of a reverse engineering project are determining the cause and degree of damage to the product and choosing the type of reverse engineering project. Four types of reverse engineering projects considered. The “original” project means the purchase of new equipment. The “original assemble” project is the replacement of product components. The projects of “redesign” and “repurposing” are also being studied. Decision rule for determining the causes of equipment failure and the degree of damage is given in the form of a mind map. This mind map combines DSM matrix and morphological map of damage. A graphic visualization of the decision rule was found for each of the project types - “original”, “original assemble”, “redesign” and “repurposing”. Diagrams corresponding to the project type take into account for parameter: damage, cost, functionality, time. These diagrams do not require preliminary calculations. The limits of parameters variation are defined regardless of product design, technological process features and economic indicators. The limits of variation can be quite clearly indicated. Each type of reverse engineering project is associated with a specific geometric

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figure. In the case of the “original” and “redesign” project, these are different types of triangles. For a project “original assemble” is a trapezoid and for “repurposing” it is quadrilateral. Thus, diagrams corresponding to the project type can be used as mind map. The decision rule, in this case, is formalized and comes down to identifying the type of geometric figure. Acknowledgments. This work has been accomplished with financial support by the Grant No BG05M2OP001-1.002-0011 "MIRACle (Mechatronics, Innovation, Robotics, Automation, Clean technologies)".

References 1. Stahl, K.: Foreword, “Best of Gears 2022.” Forsch Ingenieurwes 86, 249 (2022). https://doi. org/10.1007/s10010-022-00595-x 2. Shi, N., Olsson, R.A.: Reverse engineering of design patterns from java source code. In: 21st IEEE/ACM International Conference on Automated Software Engineering, ASE’06, pp. 123–134 (2006). https://doi.org/10.1109/ASE.2006.57 3. Gauthier, S., Puech, W., Bénière, R., Subsol, G.: CAD-driven pattern recognition in reverse engineered models. In: GRAPP 2019 - 14th International Conference on Computer Graphics Theory and Applications. https://doi.org/10.5220/0007360702440254. (lirmm-02084850), pp. 244–254. Czech Republic, Prague (2019) 4. Ivanov, V., Dimitrov, L., Ivanova, S., Volkova, M.: Reverse Engineering in the Remanufacturing: Metrology, Project Management, Redesign. In: Karabegovi´c, I. (eds.) International Conference “New Technologies, Development and Applications”, LNCS, vol. 233, pp. 169–176. Springer, Cham (2021).https://doi.org/10.1007/978-3-030-75275-0_20 5. Buonamici, F., Carfagni, M., Furferi, R., Governi, L., Lapini, A., Volpe, Y.: Reverse engineering modeling methods and tools: a survey. Comput.-Aided Design Appl. 15(3), 443–464 (2018) 6. El-Nounu, A., Popov, A., Ratchev, S.: Redesign methodology for mechanical assembly. Res. Eng. Design 29(1), 107–122 (2017). https://doi.org/10.1007/s00163-017-0255-6 7. Hentschel, C.: Attribute-Domain Matrix: A Reverse Engineering Method for Innovation. Creativity and Innovation Management 18(2), 81–89 (2009) 8. Freiberger, S., Albrecht, M., Käufl, J.: Reverse engineering technologies for remanufacturing of automotive systems communicating via CAN bus. J. Remanufac. 1(1), 1–14 (2011) 9. Lefever, D.D., Wood, K.L.: Design for assembly techniques in reverse engineering and redesign. In: International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, vol. 97607, p. V004T04A014, ASME (1996) 10. Stone, R.B., Wood, K.L., Crawford, R.H.: A heuristic method for identifying modules for product architectures. Des. Stud. 21(1), 5-31. (2000). https://doi.org/10.1016/S0142-694 X(99)00003-4 11. Decker, W., Nelson, J.: Repair, Replace or Throw Away: Linking Sustainment Strategies to Data Requirements. Defense acquisition, univ Ft Belvoir VA (2015) 12. Richerand, F.A.: Produced water treatment equipment: replace or repair? World oil 229(2), 117 (2008) 13. Gillespie, J.S., Hyde, A.S.: The replace repair decision for heavy equipment (No. FHWA/VTRC 05-R8). Virginia Transportation Research Council (2004) 14. Browning, T.R.: Design structure matrix extensions and innovations: a survey and new opportunities. IEEE Trans. Eng. Manage. 63(1), 27-52. (2015). https://doi.org/10.1109/TEM.2015. 2491283

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15. Yassine, A.: An introduction to modeling and analyzing complex product development processes using the design structure matrix (DSM) method. Urbana 51(9), 1–17 (2004) 16. Arciszewski, T.: Morphological analysis in inventive engineering. Technol. Forecast. Soc. Chang. 126, 92–101 (2018). https://doi.org/10.1016/j.techfore.2017.10.013 17. Ivanov, V., Bovnegra, L., Ivanova, S., Naleva, G., Kononova, O. (2023). Reverse Engineering and Design Process as Set of Procedures. In: Tonkonogyi, V., Ivanov, V., Trojanowska, J., Oborskyi, G., Pavlenko, I. (eds.) Advanced Manufacturing Processes IV. InterPartner 2022. LNME. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-16651-8_2

Heuristic Search for the Design of Silent Chain Transmissions Using Graphs Svitlana Ivanova1(B) , Lubomir Dimitrov2 , Viktor Ivanov3 , Anatolii Konoplov3 , and Natalia Cheredarchuk3 1 South Ukrainian National Pedagogical University Named After K.D. Ushynsky, Odesa,

Ukraine [email protected] 2 Technical University of Sofia, Sofia, Bulgaria 3 Odesa National Maritime University, Odesa, Ukraine

Abstract. The problem of “rectangling” or “polygonal action” has not been solved for chain drives, either bush roller chains or toothed chains. The search for a fundamentally new chain design was carried out using the heuristic method of enhancement creative activity. It is shown how, using the heuristic techniques that make up the method, the designer comes step by step to a new design. In the proposed six design options, the “rectangling” effect is completely eliminated. The design with the location of the drive sprocket on a straight chain section is considered. In this case, the following types of gearings can be used: pin sprocket – cycloidal rack, involute sprocket – gear rack, involute sprocket – pin rack. A design option is possible, in which the sprocket engages in the section where the chain wraps the tension roller. The chain, when wraps the tension roller, forms a compound gear wheel. In this case, the following types of gearings can be used: pin gear – cycloidal sprocket, cycloidal gear – pin sprocket, involute gear – involute sprocket and cycloidal gear – cycloidal sprocket. A significant reduction in the dynamic loads acting on the chain has been achieved. Keywords: silent chain · problem rectangling · heuristic method · graph interaction network

1 Introduction The main disadvantage of chain transmission is the fluctuation of the gear ratio. This is due to the fact that the teeth of the chain do not have theoretically correct engagement with the teeth of the sprocket. The process of conjugation of the teeth of the chain and the sprocket occurs only in the phase of the chain entering into engagement with the teeth of the sprocket. The main efforts of researchers are aimed at reducing dynamic loads in this initial phase [1–4]. The chain links are then fixedly placed between the teeth of the sprocket. This phase of chain and sprocket contact can be represented as the contact of chain links with a polyhedron. This phenomenon has been called “rectangling” or “polygonal action”. In the phase of the chain entering into engagement, chain © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 182–192, 2023. https://doi.org/10.1007/978-3-031-31066-9_19

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transmission functions like a gear train, and when the chain links is stationary between the teeth of the sprocket, like a sleeve gear coupling. To eliminate this disadvantage of chain drives, many different design solutions have been developed. Chains equipped with teeth even received the special name “silent”. However, the problem has not been solved - new publications devoted to “silent” chains serve as proof of this. A double-sided timing chain is proposed, one side of the chain engages with the drive sprocket, and the other with idler sprockets. This design makes it possible to reduce changes in the position of the chain branch when chain links entering into engagement [5]. The smooth entry of the chain into engagement is provided by the chain, which has rolling joints of a complex profile [6]. The chain is equipped with rolling joints, in the form of cams, the profile of which is matched with the profile of the sprocket teeth, so that the change in the position of the chain branches in space is minimal. The phase of the chain entering into engagement with the sprocket, as in the previous article, is presented as the contact of the rack with the involute wheel. The sprocket has an involute profile, and the chain teeth are outlined by a straight line [7]. Smooth chain entering into engagement is ensured by using a modified involute sprocket profile. In addition, the sprocket is made of two crowns with an offset two-phase profile [8]. Profile shifting of the involute sprocket tooth can be performed taking into account the change in the position of the chain [9]. The design solutions described above refer to toothed chains. The problem of rectangling has not been solved for them, since all the achievements in the sources described refer to the phase of the chain entering into engagement. Attempts to solve the problem of inconstancy of the gear ratio have also been made for bush-roller chains [10]. The engagement of the chain and sprocket is considered as an involute-pin. In order for the process of conjugation of the teeth to occur, not only in the engagement phase, but when the chain wraps around the sprocket, the sprocket teeth are outlined by an involute-trochoid profile. To drive the gas distribution mechanism, a bush-roller chain with a quasi-involute sprocket profile is proposed. In this case, the movement of the chain is equal to the movement of the sprocket tooth point on the pitch circle. Thus, the branch of the chain is always tangent to the pitch circle of the sprocket [11]. As you can see, similar ideas are implemented for a chain of a different type [5]. For the proposed profile of the sprocket teeth, an analysis of the transmission dynamics was performed. It is shown that the rectangling effect for this chain is less than for chains made according to the standards GB1244 i DIN8196T1-87 [11]. The search for a sprocket tooth profile that provides a smooth chain engagement and minimal wear was found by replacing the chain engagement with a four-link articulatedlever mechanism (Bobillier construction) [12]. Involute-pin gearing has found application in escalator drive mechanisms [13, 14]. The chain goes around the sprockets, which are located at the top and bottom of the transmission, these sprockets act as guides. The drive sprockets are located on the straight section of the chain. Thus, one pair of sprockets perceives the tension forces, and other sprockets or a sprocket are driven. Sections of the chain are loaded more uniformly. The engagement of the drive sprocket and the chain is involute-pin. The issues of the kinematics of the involute-pin engagement are considered in detail in relation to the escalator drive.

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For chain drives, there is a problem of transverse oscillations in long drives [15]. First of all, these are conveyors and escalators. It is proposed to use a double-sided chain, one side of which is engaged with the drive and idle sprockets, and the other side transfers the load to the escalator links. The surface of the escalator link meshing with the chain is a gear rack [16].

2 Research Methodology To solve the problem of searching for possible options of the chain transmission design, in which there is no gear ratio fluctuation, we use a heuristic method of enhancement creative activity, which includes the following techniques: • • • • •

Creation of a cognitive model; Construction of the graph “Interaction network”; Graph transformation; Replacing an element with its property and replacing the property with an element; Search for all possible options for the arrangement of elements corresponding to the same graph [17].

The cognitive model makes it possible to establish relationships between the objects chosen on the basis of the analogy and the main parameter, the provision of which is devoted to the study. The main parameter is smoothness of work. An analogy is made with gear and belt transmissions. Thus, the search for an initial idea will begin with the creation of a cognitive model: transmissions - chain, belt and gear according to the parameter of smoothness of work. In this case, the two superclasses of attributes are the transmission and the parameter; the subclasses are the types of transmissions and the content of the parameter (Table 1). Table 1. Cognitive model of superclass relations: Transmissions - Smoothness of work. TRANSMISSION

ATTITUDE

SMOOTH WORK

Gear

Provided

Conjugated profiles at any angle of rotation

Belt

Provided

Wrap of a round pulley

Chain

Not provided

Wrap of a polyhedron, profiles approximately conjugate

As can be seen from the cognitive model, in order to create a chain transmission design in which there is no gear ratio fluctuation, two conditions must be met: the chain wraps around a round pulley and theoretically correct conjugation. To search for such a design, it is advisable to use the graph “Interaction network”, which reflects the transmission‘s engagement. The two main properties of a chain drive are to ensure the correct position of the links in space and the transfer of force from the sprocket teeth to the chain links. To reflect these two properties, it is enough to consider only

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the sprocket and the chain links in contact with it. Thus, in the “Interaction network” graph, we will include nodes: a sprocket S and chain links – z1 , z2 , z3 . The nodes corresponding to the links are connected to the sprocket node by two types of edges. The blue edges correspond to the link support property, that is, they ensure the correct position of the links in space. The orange edges of the graph correspond to the property of transmitting force by engagement (Fig. 1). Let’s transform the graph. We believe that the link support property is implemented by the sprocket, and the force transmission property by engagement exists separately from the sprocket. If the sprocket does not provide the function of transmitting force by engagement, then its surface may be cylindrical, like a belt pulley. In this case, the smooth work of the transmission will be provided. Chain links - z1 , z2 , z3 move along the smooth cylindrical surface of the pulley, which is the guide. To ensure the property to transmit force by engagement, the links must be equipped with teeth. But these teeth cannot contact the pulley. They are in contact with other teeth E. That is, instead of the sprocket property to transmit force by engagement, three new elements E in the form of teeth have been introduced into the design. Let’s transform the graph again.

Fig. 1. Construction of the graph “Interaction network” and graph transformation

The teeth can be part of one part - a gear. Thus, the properties that the sprocket provided for supporting the chain and transmitting forces in engagement are now performed by different elements: a pulley and a gear. Different sides of the chain perform different functions, similar to two-sided chains. One side is designed for contact with a smooth surface and the other side for contact with a toothed surface. We have an idea for a new design. The design of a chain drive with tensioners is widespread. They are used to tension the branches of the chain and increase the wrap angle. Consider the construction of a chain transmission, which uses two tensioners in the form of a pulley (Fig. 2b). This chain transmission can be associated with a model in the form of a graph (Fig. 2a). The chain is a node Ch, connected by edges with sprockets z1 and z2 to rollers R1 and R2 , sprockets and rollers rotate around axes A1 , A2 , A3 , A4 . We use a heuristic technique: the search for all possible options for the location of parts corresponding to the same graph [18]. The graph does not indicate the placement of sprockets and rollers in space. That is, we can change the rollers and sprockets in places. We get a chain drive in which the location of the chain branches and its tension is provided by tension rollers. Sprockets interact with the chain in a straight section (Fig. 2c).

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Since the chain does not encircle the sprocket, the position of the chain links does not change due to conjunction with the teeth of the sprocket. The chain goes around the cylindrical rollers; there is no “Rectangling” in the chain drive. Thus, there is no fluctuation in the gear ratio and the resulting dynamic loads. It was possible to get rid of the disadvantage of a chain drive, which is considered to be always inherent in it and to which a paragraph is devoted in any textbook of machine elements.

Fig. 2. Graph and chain diagram (Search for all possible options for the arrangement of elements corresponding to the same graph).

We have found a design in which the sprocket interacts with the chain in a straight section. The next task is to obtain a design without gear ratio fluctuations, in which the chain is engaged when wrapping around the sprocket. We use the idea obtained by using the cognitive model. The chain interacts with the pulley, and the other side engages with the gear wheel. We reuse a heuristic technique: search for all possible options for the location of parts corresponding to the same graph. We move the sprockets to the contact zone of the chain and pulley. Then the chain with one of its sides is in contact with the pulley, and with its other side it engages with the sprocket (Fig. 2d). The idea formulated in the cognitive model has been implemented. A design has been obtained in which the location of the chain branches and its tension is provided by tension rollers, and the sprockets interact with the chain when it wraps around the rollers.

3 New Design Options Consider the designs of chain drives that implement the found idea and manufacture, which is possible from a technological point of view. The first factor that varies is the location of the sprocket. The sprocket can engage with the chain in a straight section (see Fig. 2c) and when the chain is wrapped around the pulley (see Fig. 2d).

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The second variable factor is the type of engagement. When the chain wraps around the pulley, a gear sector is created. In this case, the engagement of the sprocket and the chain can be represented as the gearing of two wheels. Then it is possible to realize involute and cycloidal gearing. In the case of engagement of a sprocket with a chain, a rack-pinion gearing is implemented in a straight section. To realize a pin-rack gearing, which has been research in details, it is necessary that the pins are made on the wheel and the teeth on the rack (Fig. 3a) [19]. In this case, the chain must be provided with cycloidal profile teeth. Another possible option is the traditional involute rack-pinion gearing. In this case, the sprocket has teeth with an involute profile, and the chain has teeth imitating a straight-sided rack (Fig. 3b). In the first and second cases, it is necessary to manufacture a chain of a new design. Of interest is the option with the use of bush-roller chains manufactured by the industry. To do this, use the involute-pin gearing. The sprocket teeth have an involute profile, while the chain teeth have a pin shape (Fig. 3c).

a Pin sprocket – cycloid rack

b Involute sprocket – gear rack

c Involute sprocket – pin rack

Fig. 3. Variants of the chain transmission design realizing rack and pinion engagement

This option is similar to the chain drive used for escalators. The similarity is superficial, but the difference is fundamental. Due to the flexibility of the chain, it is impossible to ensure the correct position of the teeth in the gearing. To implement theoretically correct gearing, the chain should not deform, but should move in a straight line like a rack. To solve this problem, a guide (Gu) located under the engagement zone was introduced into the transmission design (see Fig. 3). The involute gear-pin rack gearing is relatively new and not well researched. In rackpinion transmission, with a traditional cycloidal-pin mesh, the center of the pin located

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on the pinion outlined a cycloid when the wheel rolls in a straight line. Therefore, if pins are made on the wheel, then the rack must have teeth outlined by a cycloid. In the case when the pins are made on a rack, the center of the pin, lying on a straight line, forms an involute when this straight line rolls along a circle. The pinion tooth addendum is outlined by an involute, and the tooth root is outlined by an arc of a circle, the radius of which corresponds to the radius of the pin. This is an involute gear-pin rack gearing. The gear train is implemented in those designs where the engagement occurs in the area where the chain goes around the pulley. The teeth of the chain wrap around the pulley to form a gear sector that meshes with the sprocket, which acts as the pinion of the gear train. In this case, the following engagement options are possible. The sprocket has teeth in the form of pins, then the chain must have teeth outlined by a cycloid (Fig. 4a).

a Pin gear – cycloidal sprocket

b Cycloidal gear – pin sprocket

c Involute gear - involute sprocket. Сycloidal gear – cycloidal sprocket

Fig. 4. Variants of the chain transmission design realizing pin-wheel gearing

A cycloidal-pin gearing is implemented. The preferred option is to use a bush-roller chain produced by the industry. Then the chain roller performs the function of a pin, and the sprocket has a cycloidal profile. In this case, a cycloidal-pin gearing is also realized (Fig. 4b). In the case of using a toothed chain, two options for engagement are possible. The chain and sprocket teeth may have cycloidal profiles and cycloidal gearing is realized. Or the chain and sprocket teeth may have involute profiles and involute gearing is realized (Fig. 4c).

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Note that in schemes Fig. 4b and Fig. 4c, sprockets manufactured by the industry cannot be used. It is believed that the profile of the sprocket teeth is cycloidal. In fact, instead of a cycloid, a set of arcs of circles and a straight section are used. For these schemes, it is necessary to manufacture sprockets with a cycloidal profile. Consider the kinematics of the proposed chain transmission. When the chain wraps around the roller, the chain links realize a compound gear pinion. The number of teeth zc of this gear is, zc = rt where r - radius of the pitch circle, t - the pitch of the chain. For bush roller chains, pitch radius r = r0 + R, ,where r0 – tension roller radius, R – roller radius of bush-roller chain. For toothed chains, pitch radius r = r0 + A, where A – distance from the bearing surface of the chain link to the pitch line of the tooth. In the schemes in Fig. 4, the gear ratio does not depend on the radius of the tension rollers. The linear speed of the chain is the same at any point. Thus, the equality: r1 ω1 = r2 ω2 , for drive 1 and driven 2 sprockets. The chain drive usually fails due to wear on the chain pins. In the proposed design, dynamic loads are sharply reduced; the chain can transmit large forces. The overlap coefficient in the design under consideration is several times less than in a conventional chain drive, and the forces in gearing a pair of teeth are much greater. In this regard, it is not clear which element will limit the load capacity of the transmission - pins or teeth. Let’s compare the load capacity of the involute-pin gearing and bush-roller chain. We will estimate the strength of the chain transmission on the basis of the standard method, and the strength of the involute-pin gearing directly on the basis of the Hertz formula. The radius of curvature ρ is variable depending on the engagement phase. ρ=

Rrs , R + rs

where r s – sprocket tooth curvature radius. From the experience of operating gears, pitting occurs in the middle of the tooth involute surface at a radius rm . rm =

rb + ra , 2

where r b – base radius, r a – addendum radius. The radius of curvature rsm - in the middle of the tooth involute surface rsm = rm sinαm , where αm – pressure angle in the middle of the tooth involute surface. The radius of curvature. ρ=

Rr m sinαm , R + rm sinαm

Maximum load capacity, taking into account the allowable contact stresses [σH ]. F=

[σH ]2 bRrm sinαm (0, 418)2 R + rm sinαm

The formula for calculating the maximum gearing load capacity includes the radius Rm , which depends on the number of sprocket teeth. Thus, with the same chain, transmissions with different load capacities can be realized (Fig. 5).

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Fig. 5. Load capacity of the chain (1) and sprocket (2) (chain 32A-1 accordingly ISO 606:1994; radius r0 = 150 mm, z2 = 50)

From Fig. 5 it can be seen that in a transmission with a number of drive sprocket teeth of 20 or less, the load capacity is limited by the contact strength in the gearing, and with a larger number of teeth, the strength of the chain is limiting.

4 Conclusion The use of the heuristic method of enhancement creative activity made it possible to see what the insolvability of the “rectangling” problem is. Graph “Interaction network” gave the idea - the teeth of the chain should be part of a gear or rack and move, respectively, in a circle or a straight line. Technique «Search for all possible options for the arrangement of elements corresponding to the same graph» turned out to be effective. Thanks to this technique, a compound wheel was found that forms a chain when it wraps around the tension roller. The obvious advantage of the proposed designs is the absence of gear ratio fluctuations and a sharp decrease in dynamic loads. Chain transmission can be used in machines where smooth work is required and where chain transmission has never been used before, such as metalworking machines. The disadvantages of the design are also obvious; these are significant dimensions and a low overlap coefficient. This limits the use of transmissions in transport. For escalators and conveyors, some increase in dimensions is permissible. The new design requires a detailed study of many issues. Only the aspect of load capacity has been considered. It has been established that the contact strength of the teeth is the limiting factor in the load capacity of the transmission with a small number of sprocket teeth, and with an increase in the number of teeth of the drive sprocket, the limiting factor is the wear of the chain pins. Acknowledgments. This work has been accomplished with financial support by the Grant No BG05M2OP001-1.002-0011 “MIRACle (Mechatronics, Innovation, Robotics, Automation, Clean technologies)”.

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References 1. Zengming, F., Kong, F., Chengguo, D., Fanzhong, M.: Flexible multi-body contact analysis of rounded-jointed silent chain and sprocket. In: 5th Asian conference on multibody dynamics. The Proceedings of the Asian Conference on Multibody Dynamics. Kyoto, Japan (2010) 2. Cheng, Y., An, L., Yin, S., Wang, X.: Multi-variation characteristic of dual phase Hy-Vo silent chain transmission system. Mech. Mach. Theory 103, 40–50 (2016). https://doi.org/10.1016/ j.mechmachtheory.2016.04.011 3. Cheng, Y., Wang, X., Qi, H., Li, L., Fu, Z., Wan, N.: Noise characteristics test of Hy-Vo silent chain for hybrid vehicles. In: 2016 Joint International Information Technology, Mechanical and Electronic Engineering Conference. Sian, China (2016). https://doi.org/10.2991/jimec16.2016.1 4. Marinko, J.: Simulacijakinematikezobateverige. Doctoral dissertation, Univerza v Ljubljani, Fakultetazastrojništvo (2019) 5. Cheng, Y., Yin, S., Wang, X., An, L., Liu, H.: Design and analysis of double-side meshing and dual-phase driving timing silent chain system. StrojniskiVestnik – J. Mech. Eng. 62(2), 127–138 (2016). https://doi.org/10.5545/sv-jme.2015.2837 6. Su, W.Y., Wu, Y.R.: Design optimization of a rocker-joint silent chain and sprocket drive based on the mesh performance indices. Appl. Mech. Mater. 197, 104–109 (2012). https:// doi.org/10.4028/www.scientific.net/AMM.197.104 7. Jurj, L., Velicu, R., S˘aulescu, R.: Geometry of silent chain-involute sprocket. In: MATEC Web of Conferences, vol. 184, p. 02003 (2018).https://doi.org/10.1051/matecconf/201818402003 8. Cheng, Y., Wang, Y., Li, L., Yin, S., An, L., Wang, X.: Design method of dual phase Hy-Vo silent chain transmission system. StrojniskiVestnik-J. Mech. Eng. 61(4), 237–246 (2015). https://doi.org/10.5545/sv-jme.2014.2318 9. Sun, W., Liu, X.L., Liu, J.J., Zhang, W.: Center distance change of silent chain drive effect on sprocket tooth profile modification. Key Eng. Mater. 522, 574–577 (2012). https://doi.org/ 10.4028/www.scientific.net/KEM.522.574 10. Kroll, R.: U. In: Kroll, R. (ed.) Metzler Lexikon Gender Studies Geschlechterforschung, pp. 393–395. J.B. Metzler, Stuttgart (2002). https://doi.org/10.1007/978-3-476-05004-5_21 11. Wang, Y., Ji, D., Zhan, K.: Modified sprocket tooth profile of roller chain drives. Mech. Mach. Theory 70, 380–393 (2013). https://doi.org/10.1016/j.mechmachtheory.2013.08.006 12. Protasov, R., Andrienko, S., Ustinenko, A., Bondarenko, A., Matushenko, N.: Geometry modeling of gear and chain drive with evolute profile and research of its contact stress. Fiabil. Durabil. Fiabilitatesi Durabilitate vol. 1 (2017) 13. Blatnická, M., Sága, M., Blatnický, M.: Design of pallet, frame and chain of soldering station conveyor. MATEC Web Conf. 157, 01001 (2018). https://doi.org/10.1051/matecconf/201815 701001 14. Bondaryev, S.V., Gorbatenko, Yu. P., Zakora, O.V.: Zastosuvannyacivkovogoevol‘ventnogozacheplennya v pry‘vodieskalatora. Zactocyvanncivkovogo evolventnogo zaqeplenn v ppivodieckalatopa. Research Bulletin of NTUU. Kyiv Polytechnic Institute, pp. 108–115 (2011) 15. Choi, W., Johnson, G.E.: Transverse vibrations of a roller chain drive with a tensioner. In: International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, vol. 11795, pp. 9–28 (1993) 16. Boltrek, H., Freeport, N.Y., Joseph, K. K., Verona, N.J.: Patent U.S. No. 3,707,220. Modular passenger conveyor construction, Washington, DC: U.S. Patent and Trademark Office (1972) 17. Ivanov, V., Urum, G., Ivanova, S., Volkova, M.: Development of the positive engagement continuously variable transmission design with the application of graph theory. Eastern-Euro. J. Enterp. Technol. 3(1), 9 (2018)

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Continuous Improvement and Performance Assessment in Knowledge-Based Organizations Aurel Mihail Titu1(B) , Andreea Maria Ungureanu2 , and Florin-Alexandru Lungu3 1 Lucian Blaga” University of Sibiu, 10 Victoriei Street, Sibiu, Romania

[email protected]

2 Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest,

313 Splaiul Independen¸tei, 6th District, Bucharest, Romania 3 National Research and Development Institute for Cryogenics and IsotopicTechnologies,

4 Uzinei Street, RamnicuValcea, Romania

Abstract. Ever since the emergence of the economic environment, there have been concerns about the quality of products and services provided. This concept has evolved over time, reaching very high levels and quality requirements becoming very rigorous. Thus, quality management is a permanent issue in a continuously changing society. To have an effective and efficient quality management system, organizations must demonstrate that they have the ability to consistently deliver products and services that meet legal, customer and regulatory requirements. But this is not enough, companies having to demonstrate performance and improvement. In this scientific paper will be analyzed modern management models in organizations, performance evaluation methods and the close connection between key performance indicators (KPI) and continuous improvement. Keywords: Management · Knowledge · Continuous improvement · KPI · Quality Management

1 Introduction Modern management models in knowledge-based organizations are usually based on quality management, knowledge management, change management, relationship management, human resources management, etc. These approaches are not new at all, they appeared a long time ago, but in a society that is constantly changing, the need for adaptability to the “times we live in” is imposed. So where does this concept of modern management models come from? Often from the need for change. As Frank Wilczek said: “If you don’t make mistakes, you’re not working on hard enough problems. And that’s a mistake”, it is known that the best ideas came out after some mistakes. As far as management in organizations is concerned, it is obvious that these quotes can be applied. Because the organization is seen as a complex system, based primarily on the unity of a human group, which has as its common objective the fulfillment of the organization’s purpose. The human resource is and will always be the most important and the most difficult to manage of all, and no matter how much society © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 193–200, 2023. https://doi.org/10.1007/978-3-031-31066-9_20

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would like to replace it with new equipment or intelligent robots, it will not be able to be completely replaced which makes the possibility of mistakes inevitable. Most of the time mistakes are necessary, thus creating the need for change. They often generate innovative ideas and management solutions that improve the system as a result. Of course, changes can be generated both from internal causes in this case or external to the organization (political, economic, environmental factors, etc.).

2 Modern Management Models in Organizations The concept related to quality has been approached since the emergence of the economic environment, passing through several stages: quality control, quality assurance, quality management. In this sense, international standards, sets of requirements, legislation were created to regulate the quality management approach, thus facilitating its implementation in organizations. The most common tool used is ISO 9001 that specifies requirements for a quality management system [1]. According to the latest revision of the standard ISO 9001, organizations that implement a quality management system, in the planning stage, approach the assessment of risks and opportunities according to the new aspect introduced by risk-based thinking. Many times, top management in organizations tend to identify potential tangible risks/opportunities, with often material impact on the organization, then acting to address them. Also in the last version, great attention is paid to leadership and commitment and it is mentioned that this cannot be an outsourced process. In this sense, in many cases we can meet organizations that have a quality management system, they prove compliance with all the requirements imposed by the standard or others applicable but they cannot demonstrate the expected performance. In recent years, a special importance has been transferred to the human factor, on the awareness of the personnel in the organization, on the organizational knowledge. The standardization bodies update their sets of requirements according to the evolution of society and according to the obstacles they have identified. In this way, aspects of riskbased thinking, the process approach (PDCA) for continuous improvement, leadership and commitment, and the management of relations with interested parties are promoted. PDCA can be applied regardless of whether we are talking about a process, the stage of a process, an activity or an organization as a whole. In the Fig. 1 we can see a general illustration of the process approach by using the Deming cycle [2].

Fig. 1. The PDCA for continuous improvement cycle (Plan-Do-Check-Act)

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Specialists note that there is a close connection between emotional skills and success in management. The growing interest in the development of emotional intelligence and emotional competences in the managerial and business context was determined by the fact that the biggest problems faced by organizations today do not belong to their technical, technological or functional side, rather than the emotional one. The success of an organization is dependent on the emotional skills possessed by the human factor involved [3]. The work environment is determined by the relationships between employees, manager-subordinate, organization-employees. We often meet employees who do not give their best at work, who make the strictly necessary effort to keep their job. A study carried out by a website for finding jobs shows that the main reasons why many employees leave their workplace are the toxic company culture, low salaries, poor management and the lack of a healthy work-life balance [4]. It was found that the more complex human activities become, with more varied goals and the more varied human interactions they involve, the more IQ (Intelligence Quotient) is no longer a good predictor of performance and EQ (Emotional Quotient) becomes a factor more significant until it is even the measure of success (Table 1). Table 1. Comparison between how cognitive and emotional intelligence intervene at work Cognitive intelligence

Emotional intelligence

It works well only when we are calm

It works well in any situation

It works more slowly, inefficiently when fast decisions are challenged

It works more quickly, we can rely on it in critical situations

It helps to process abstract information, to be good at math, to memorize

It helps to be creative, to solve complex problems, to change

It helps to do calculations

It helps to understand better with other people and to build relationships

It helpsto make decisions in conditions of certainty

It helps to make decisions in conditions of uncertainty

It helps to direct people, to impose on them

It helps to be empathetic, to motivate

3 Performance Evaluation Methods in Knowledge Based Organizations The link between an organization’s operational and strategic management is provided by knowledge management, which is an essential component of the managerial process. While strategic management refers to decision-making procedures that are futurefocused, operational management has a temporal horizon determined by the calendar year. As a result, many organizations have more or less developed parts of knowledge management, but they lack the coherence needed to be defined as a new managerial process. When we discuss the adoption of knowledge management, we are referring to organizations where knowledge has taken the place of other, more important resources, and

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where its administration needs to be a distinct, well-defined area with new responsibilities [5]. How do we evaluate the performance in this type of organizations? The organization is required by ISO 9001 to decide what needs to be monitored and measured. It must also choose the monitoring, measurement, analysis, and evaluation techniques required to produce reliable results. Organizations need to focus on discipline-specificperformance as well as the effectiveness of the management system. The performance indicators that have been defined for each QMS process should be the main focus of the control methods used for monitoring and measurement in order to achieve the desired results. The quality plan should describe or make reference to the monitoring and measure ment techniques, sample programs, and accept ancecriteria, or it can use a combination of particular practices, processes, documents, and methods. The organization’s top management should assess the QMS on a regular basis to ensure that it remains appropriate, sufficient, and effective. It should also be in line with the organization’s strategic direction. Decisions and actions pertaining to areas for improvement, any changes that may be required to the QMS, and resource requirements must be included in the management review’s outputs. The company has to keep the records as proof of the management reviews’ findings [1]. There are many newer or older methods that organizations use to evaluate their performance. Each method has its constraints, for that it is recommended to use several methods to achieve the desired results (Table 2). Table 2. Examples of methods for performance evaluation Method

Characteristics

Analytical Hierarchy Process

Method used to determine the weight of perspectives, strategy objectives and KPI [6]

Balanced Scorecard

System that identifies and corrects the internal business system to enhance the external outcome based on it [7]

PerformancePrism

Allows organizations to develop strategies, business processes and measures geared to the specific needs of all important stakeholder groups [8]

PerformancePyramid

Includes a hierarchy of financial and non-financial performance measures

The Balanced Scorecard has four perspective: finance, customer, internal business processes and learning and growth. These four balanced scorecard perspectives are hierarchically interconnected. The majority of firms want to improve their financial results as their main goal. When there is a focus on learning and growth through out the organization, this is made possible. Learning and developmentincrease an organization’s capabilities internally. With increased internal capability, the business may concentrate on improving internal operations, which influence external outcomes. Customers and others take holders are direct

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affected by the external outcomes. More positive external results will increases takeholder and customer satisfaction. Together, these factors improve the financial result. In order to accomplish the strategic goals, a balanced scorecard stream lines activity in these four areas [9] (Fig. 2).

Fig. 2. Key Performance Indicator and Balanced Scorecard

25% of this method focuses on human resourcesregardingjobsatisfaction, training opportunities, motivation, specialist and knowledge skills. Thus, it can be seen that special attention must be paid, top management having the attribution of being able to distinguish cognitive from emotional intelligence, as it facilitates the increase of the above-mentioned aspects and results in an increase in global performance.

4 KPI and Continuous Improvement KPIs are measurable indicators of performance over time for a certain objective. KPIs offer goals for teams to strive towards, benchmarks to evaluate progress, and insights that aid individuals throughout the organization in making better decisions. When implementing a quality management system, it is very important how to set the performance indicators, because a poor planning or formulation will lead to the impossibility of measuring and quantifying them. In this sense, like the objectives, KPIs can be formulated as SMART (Specific, Measure, Attainable, Relevant, Timeframe). Besides figuring out what is going to be measured, it is important to look at how exactly the KPI will be calculated. The most common ways of measuring the data to create KPIs are: understanding data counts, measuring with percentages, sums or totals, averages of data, ratios to compare numbers [10]. Let’s see some formulas for KPI: Sales growth = Cost per hire =

100 ∗ (end sales revenue − beginning sales revenue) beginning sales revenue

(1)

internal recruitment costs + external recruitment costs total number of hires

(2)

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As we can see, most KPIs are linked to objectives, processes or activities with tangible results that can be calculated with mathematical formulas or other specific methods. But how can we calculate or quantify KPIs for objectives related to social responsibility for instance, if we have proposed them? Currently, there is not a generally valid approach as social responsibility is very unique and tends to bind and integrate solemnly to each organization’s main activities and potential growth areas. Therefore, measuring the performance on social responsibility strategy and campaign is not a standardized practice and it needs to be adapted to the business particularities, views, goals and business model. Corporate Social Responsibility has become a highly debated subject among government officials, academics, and business people. The whole public is now paying attention. The general population has high expectations for how much business will improve their social lives. In order to enhance their reputation and establish legitimacy in the are a where they operate, many firms work on a variety of social programs, including health care, education, economic welfare, infrastructure development, human rights and environmental protection [11, 12]. CSR concerns have managed to identify KPIs that can be quantified [13]. Some examples are given in Table 3. Table 3. Areas and KPIs identified for CSR concerns Area

KPIs

Employee engagement

% of employees that were happy with a project, % of employees which are engaged in a given project, number of hours volunteered, diversity & inclusion (using surveys), skill development etc

Customer engagement

Event participation, feedback and involvement, complaints and resolving complaints etc

Sustainability

Community participation and involvement, contribution to society, sustainable consumption, access to technology etc

Environment

The consumption and use of energy, overall emissions, use of water and materials, effluents and waste etc

Financial and profit returns

Profit, revenue growth, % increase in market share etc

Regarding improvement, we must draw attention to the two terms used in association with it: continuous and continual. The meanings of the two words are frequently interchangeable. There are, however, some significant differences between the two. Continual improvement entails repeating the process and pausing in between cycles. A continual approach will have a phased system in which changes are made, followed by a pause to evaluate the success, and then additional improvements can be made. It is promoted in the last version of ISO 9001, being part also of process approach through Deming Cycle. A continuous improvement strategy, however, is a constant flow that does not end. An ongoing process of development, a continuous approach is one that always seeks to

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improve. Lean is one of the most popular methods for continuous improvement. This strategy seeks to establish a “Kaizen culture”, which employs a variety of tools (5S, Kanban, Value Stream Mapping etc.) and methods to minimize waste and maximize customer value [14]. Thus, KPIs are strictly related to the improvement process as they provide a clear vision of the stage of achieving the objectives. The more frequently they are measured, the sooner preventive or corrective actions can be taken to avoid potential non-conformities or increase their possible positive effects.

5 Conclusions Lately, in knowledge-based organizations, more and more emphasis is placed on the human factor and how it could be improved in the workplace, since the overall performance of the organization is directly proportional to the commitment of the staff, to the image that has on the company, with the interest given to achieving global objectives. Thus, both old and new concepts are approached to find the best solutions. Both the sets of requirements of the international standards, the current legislation as well as the good practices and the development of society promote concerns regarding social responsibility and how to measure its effectiveness. It is important to note that a better understanding of emotional intelligence both on the part of Top management, decision-makers, and employees can increase in a positive way the evolution of the organization, the organizational environment, the relations between the hierarchical levels. In order to maintain an efficient quality management system, in the planning stage, organizations establish achievable objectives, take into account associated risks and opportunities and define KPIs for their quantification. This concept is the basis for continuous and continual improvement. Also, in modern organizations, special attention is paid to the CSR approach, since social responsibility concerns are no longer an option and in the future they could be mandatory. Successful organizations manage to keep under control and monitor aspects regarding finances, customers, internal business processes, but also learning and development opportunities at the workplace. In this sense, performance evaluation methods are used to identify possible problems in the company.

References 1. International Organization for Standardization: Quality Management Systems—Requirements (ISO 9001:2015) (2015) 2. Al-Bakoosh, A.A., et al: Implementation of the PDCA continuous improvement cycle (PlanD0-Check-Act) as a tool for improving the quality of the cast AA5083 alloy produced in the foundry laboratory. IOP Conf. Ser.: Mater. Sci. Eng. 884, 012114 (2020) 3. Cândea, R.M., Cândea, D.: Competent, ele emot, ionale s, i succesul în management, Editura Economica, Bucures, ti (2005) 4. https://www.flexjobs.com/blog/post/survey-resignation-workers-considering-quitting-jobs/. Accessed 20 Dec 2022

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5. Bratianu, C.: Managementulcunostintelor. EdituraUniversitara, Bucuresti, Conceptefundamentale (2015) 6. Andrias, P.M., Vanany, I.: Design and implementation for performance measurement system in the power plant operation and Maintenance Company. IOP Conf. Ser.: Mater. Sci. Eng. 1072, 012007 (2021) 7. Four Perspectives of Balanced Score cards With Examples - Harappa [crossref] 8. Alladyn, E.: Revision of performance measurement tools and methods, e-Finanse: Financial Internet Quarterly, ISSN 1734-039X, Sciendo, Warsaw, vol. 15, Issue 2, pp. 20–35 (2019). https://doi.org/10.2478/fiqf-2019-0009 9. Saranya, M., Anithaashri, T.P.: Novelapproach to enhance network security using key performance indicator in business analytics. IOP Conf. Ser.: Mater. Sci. Eng. 992, 012015 (2020) 10. Lipatova, S.V., et al.: Anintegrated model as a tool for implementing an enterprise management method. J. Phys. Conf. Ser. 1333, 072015 [cross ref] 11. Rudito, B., Famiola, M., Anggahegari, P.: Corporate social responsibility and social capital: journey of community engagement toward community empowerment program in developing country. Sustainability 15, 466 (2023). https://doi.org/10.3390/su15010466 12. Santoso, M.B., et al.: Identification of stakeholder involvement in the conduct of corporate social responsibility (CSR) IOP Conf. Ser.: EarthEnviron. Sci. 311, 012049 (2019) 13. CSR Growth, Reshaping the Way Businesses Think and Act [crossref] 14. Duffy, G.L.: Modular Kaizen Continuous and Break through Improvement. American Society for Quality, p. 53203. Quality Press, Milwaukee (2014)

Cognitive Cyber-Physical Production Systems: A New Concept of Manufacturing Systems on the Route to Industry 5.0 Elvis Hozdi´c1(B) and Zoran Jurkovi´c2 1 Faculty of Mechanical Engineering, University of Novo mesto, Na Loko 2, 8000 Novo mesto,

Slovenia [email protected] 2 Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia

Abstract. The European Commission has announced a new production philosophy for a sustainable, human-centric and resilient European industry. It has recently emerged under the name Industry 5.0 and opens up new perspectives for the development of advanced manufacturing systems. The concept of Industry 5.0 brings forth a new paradigm in the field of manufacturing systems, the so-called adaptive cognitive manufacturing systems (ACMS) paradigm. A fundamental building block of ACMS is the new generation of manufacturing systems called cognitive cyber-physical production systems (C-CPPS). This paper presents the development of a new production system. Its development stems from earlier work on a generic conceptual model of a cyber-physical production system (CPPS). The conceptual model of the C-CPPS incorporates the key technologies of Industry 4.0 for the development, adaptation and implementation of a CPPS and the advanced cognitive technologies of Industry 5.0 for the symbiosis of humans and automation. Keywords: cognitive cyber-physical production systems · enabling technologies · human-centric · industry 5.0 · resilient · sustainable

1 Introduction Industry is the main engine of economic development [1]. In the last decade, European and global industry have been in an era of digitalization and cybernetics, with companies seeking to adapt their manufacturing structures and systems to the principles of Industry 4.0 [2]. The key drivers of Industry 4.0, such as decentralization, connectivity, horizontal and vertical integration, collaboration, digitalization, cybernation, smart machines and products, and automation [2], have revolutionized the industry sector. These elements have paved the way for new organizational forms and innovative management principles. The novel organizational forms and innovative management principles have become the key elements of Industry 4.0 manufacturing systems [3], the so-called Smart Manufacturing Systems (SMS) [4]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 201–212, 2023. https://doi.org/10.1007/978-3-031-31066-9_21

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These SMS enable the processes of digitalization and cybernation. Over time, different concepts of SMS and advanced automation technologies have been developed, such as: cyber-physical production systems (CPPS) [5], cloud manufacturing [6], ubiquitous manufacturing systems [7], socio-cyber-physical systems (SCPS) [8], sociocyber-physical manufacturing systems (SCPMS) [9] and personalized manufacturing [10]. The key technologies of Industry 4.0 and SMS are actively involved in European industry, but the COVID19 pandemic caused many problems for the economy, industry, production activities, transport, etc. According to a literature review [11–14] many companies faced the following problems: (1) workers need to wear masks and maintain a minimum distance from each other, (2) workers must be quarantined for several weeks, (3) demands for some products reduced, (4) demands for other products increased as a result, but future demand could disappear, and (5) due to insufficient transportation capacity, products cannot be delivered to the customer. Modern industry, manufacturing companies and their manufacturing systems need to be oriented toward agile, networked, service-oriented, green and social manufacturing practises that are, among otherthings [15] more environmentally friendly, socially and economically sustainable and more human-centred [16, 17] and also more resilient [18, 19]. The new idea of Industry 5.0 appeared as an extension of Industry 4.0 to include social and ecological dimensions [20]. In this paper, we first introduce various concepts and definitions of industrial revolution, manufacturing paradigm and manufacturing systems from the perspective of various researches and then present the advanced technologies for Industry 5.0. In the central part of this paper, we present a generic conceptual model of a CPPS and its basic manufacturing structure and a defined system framework for a C-CPPS. Finally, we present our vision, challenges and a research agenda for future work in the field of sustainable, human-centric, and resilient manufacturing systems.

2 Industrial Revolutions, Manufacturing Paradigms and Manufacturing Systems Industrial revolutions mark the most radical changes in the development of industry. These changes are characterized by certain achievements that influenced both the direction of the development of industry as a whole and new system solutions in the structuring of production systems and the organization of work. The first important achievement was the invention of steam power, which became the driving force for a variety of machines, paving the way for the mechanization of industrial production and the construction of factories. This is referred to as the first industrial revolution, the so-called Industry 1.0. The steam-powered machine drove other machines and enabled a larger spatial and production concentration of them within a single factory and the concentration of the factories themselves. Craft production and the job shop were developed, see Fig. 1.

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Industry 1.0 marks one of the most important events in the history of human society, bringing about extensive technological and social transformations. Development continued in the direction of new discoveries, such as direct and alternating current, light bulbs, power plants, transmission lines, internal combustion engines, and telecommunications, which happened in the second half of the 19th Century. Steam as a source of energy in factories was replaced by electricity, gas and oil. This development led to the second industrial revolution, called Industry 2.0, which is characterised by the following economic changes: an increase in the spatial concentration of operations; the expansion of world trade; the development of technology for global trade, thereby significantly reducing costs and increasing the security and efficiency of trade; the development of factory production systems based on scientific principles of management; and the development of mass-production principles in Henry Ford’s automobile factories. Dedicated manufacturing system and agile/lean manufacturing were developed. The third industrial revolution, known as Industry 3.0, began in the 1960s. This period marks important technological achievements in the field of electronics and informatics, as well as in the field of production automation. It is commonly referred to as the computer or digital revolution, as it was fuelled by the development of computers and computercontrolled machines and industrial robots. The fundamental characteristic of Industry 3.0 is the introduction of flexible production based on automation and robotization.

Fig. 1. Timeline of Industrial Revolutions

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The fourth generation of industry or Industry 4.0 is a continuation and upgrade of the third industrial revolution. Terminologically, Industry 4.0 means the horizontal integration of the flow of data, information and knowledge between partners, suppliers and users, as well as the vertical integration within the production organizations themselves – from product development and manufacturing to the use of services at the end of a product’s lifecycle [21]. Industry 4.0 evolved in 2011 with the concept of the SMS paradigm [22]. The SMS utilizes the concepts of the CPPS [5]. The CPPS are a basic building blocks of the SMS and enable the 4th industrial revolutions concept [3, 5, 23–26]. Once implemented, these concepts, advanced cognitive technologies and artificial intelligence will make manufacturing the hallmark of the next industrial revolution [26], the so-called Industry 5.0. 2.1 Towards Industry 5.0 The term Industry 5.0 has become known in the last five years, mainly through academic works [27–31].The first authors to use the term Industry 5.0 were Özdemir and Hekim in the paper [27], in which they discussed “how human activities and technologies can be reconciled in an increasingly networked world”. According to [32], Nahavandi proposes another requirement for Industry 5.0 in the paper [28], emphasising the need to “find a solution that allows manufacturers to increase productivity without removing human labour from the manufacturing industry”. Different industry practitioners and researchers have presented different definitions of Industry 5.0. In [33], Industry 5.0 is seen as the next industrial revolution. According to [34], Industry 5.0 is “a necessary step from Industry 4.0 and provides a different focus that emphasises the importance of research and innovation to support industry in its long-term service to humanity within planetary boundaries”. The Industry 5.0 concept has been defined by the European Commission as follows [34]: “Industry 5.0 recognizes the power of industry to achieve societal goals that go beyond jobs and growth to become a resilient provider of prosperity, by making production respect the boundaries for our planet and placing the wellbeing of the industry worker at the centre of the production process”. The concept of Industry 4.0 is more technology-oriented, while Industry 5.0 is more value-oriented and focuses on the practical implementation of available technologies in industry [35]. Based on a literature review [1, 16–18, 30, 32, 36–39], and the publications of European Commission [34], three key enablers of Industry 5.0 stand out: human-centredness, sustainable and resilient. The human-centredness refers to the development of new production systems that involve workers. Sustainability refers to production systems, i.e., promoting energysaving, cleaner production processes and circular economy. Resilience refers to production systems and organisational attitudes to overcome the economic crisis and maintain advantages over competitors [32].

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In [37], the authors set the framework of the concept of Industry 5.0, which is based on the symbiosis of three segments, namely technological, social and environmental, which constitute the essence of Industry 5.0. The human symbiosis with technology was also presented in [36]. Similarly, Bernar and Welh described “Smart Working” practices in [40]. In [16, 41], ElMaraghy et al. presented a vision for a new, future paradigm of adaptive cognitive manufacturing systems (ACMS). Future manufacturing systems such as human-centric adaptive manufacturing, living manufacturing systems, human-cyberphysical manufacturing systems, resilient manufacturing systems, cyber-physical cognitive manufacturing systems, represent systems with a new paradigm and the concept of Industry 5.0, see Fig. 1. 2.2 Key Technology for the Industry 5.0 Concept Based on the publication of the European Commission [42], the authors have identified the enabling technologies for the transition from Industry 4.0 to the concept of Industry 5.0 in the paper [38]. The key technologies of the Industry 5.0 concept such as Edge Computing, Big Data Analytics, Internet of Everything, Blockchain, Digital Twins, 5G & Beyond, Cobots and Artificial Intelligence, are described in [33, 43]. These enabling technologies for the Industry 5.0 concept are highlighted in Fig. 2.

Fig. 2. Key enabling technologies of Industry 5.0 [43]

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The key enablers of the Industry 5.0 concept are CPPS, artificial intelligence and cognitive technologies. The implementation of cognitive technologies and artificial intelligence in CPPS opens the way for a new generation of advanced production systems, the so-called cognitive cyber-physical production systems (C-CPPS). Based on a literature review in this section, we present a new concept for CPPS below.

3 Cognitive Cyber-Physical Production Systems The evolution of the manufacturing systems paradigm from the SMS paradigm to the new paradigm, called Adaptive Cognitive Manufacturing Systems (ACMS) paradigmwas announced in [16]. This new paradigm opens the way to a new industrial revolution (Industry 5.0), and enables the development of a new concept of production systems in the spirit of cyber-physical systems (CPS). The starting point for the development of a new concept of production systems, the so-called The C-CPPS, is the generic model of CPPS developed in [3], see Fig. 3.

Fig. 3. Generic model of a CPPS (Adapted from [3])

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According to [3], the generic CPPS model consists of three constitutive elements, i.e. a social element (social system), a cyber element (cyber system), and a physical element (physical work system). The constitutive elements of the CPPS model are acting in their specific spaces (a social space, a cyberspace and physical space) as shown in Fig. 3. The structure of the physical work systems (PWS) is based on the structure of the elementary work systems (EWS) [44]. In the manufacturing domain, the Subject as a basic building block of the social system, establishes the collaborative interactions with other stakeholders of the social process with the aim of implementing business processes. Interactions within the social systems in today’s global world are not only within the social space. Advanced information and communication technologies (ICT) enabled the transfer of mutual interactions between stakeholders and the cyberspace. The basic building block of the CPPS model in the cyber space is the cyber system (CS). The CS is an essential part of cyber space that enables the realization of species manufacturing functions such as data and knowledge management, learning, simulations, control, etc., as well as the connection with physical and social elements and the network connecting to the IoT, IoS and production networks. The connectivity between CS and the PWS and between CS and the social system or the Subject enables the key technologies of the Industry 5.0 concept. The C-CPPS concept is the next step in the development of CPPS. It focuses on the use of advanced cognitive technologies of Industry 5.0, artificial intelligence and the role of the Subject. In this paper, the EWS or its cyber system is considered. Similar to the CPPS concept [3], the basic structure of the EWS cyber system in the C-CPPS concept is divided into three basic parts: 1) data acquisition, 2) self-learning, and 3) state monitoring and identification, see Fig. 4. The important part of EWS cyber system is a self-learning function (Fig. 4). The EWS cyber system of the C-CPPS ensures the continuous implementation of the digitalized self-learning function. The input data to the self-learning function is data acquisition from the physical system and stored in the database of the EWS cyber system, as well as the data obtained from participation in the IoT. The mechanisms for implementing the self-learning function within the self-learning activity are represented by various learning algorithms (e.g., algorithms for data mining and knowledge discovery) that are built into the software equipment. The outputs from the EWS self-learning function are knowledge models (e.g., a descriptive knowledge model built using the data-clustering method, a predicative knowledge model for rule-based prediction and a knowledge model for diagnostic a condition) that can be used by various digital mechanisms to support command and control in the EWS cyber system. The knowledge model is managed by the data and knowledge management system. The knowledge model offers information about the structure of the system, about the elements of the EWS physical system, about the current state elements of the EWS physical systems based on current data, etc. The EWS cyber system of the C-CPPS structure is based on the virtual work system (VWS) structure [45]. The C-CPPS concept introduces the cognitive technologies and artificial intelligence such as a software entity having four basic functional elements: perceptor, evaluator, effector, and inference mechanism.

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Fig. 4. Structure of the EWS cyber system (Adapted from [3])

By using the key technologies of Industry 5.0, the EWS cyber system in the CCPPS concept not only has powerful sensing, computing analysis, and control functions, but also the ability to enhance learning and generate knowledge. In the C-CPPS concept, the Subject will transfer part of its cognitive and learning brainwork to the EWS cyber system. This enables the elements of the EWS cyber system (e.g., software agents and multi-agent’s systems, knowledge-based systems, artificial neural networks, genetic algorithms) to cognize and learn. In the proposed C-CPPS concept, there is a change in the role of the Subject. His/her role is taking shape mainly in two directions: 1) in the direction of generating new ideas and innovations with the intensive use of explicit knowledge, social technologies, creativity and intuition (the Subject as a carrier of knowledge, i.e., a knowledge coworker), and 2) in the direction of C-CPPS management in real time based on an on-line information, diagnostics, prognostics and decision models (the Subject as a decision maker, i.e., manager), see Fig. 5. Such a role of the Subject in the C-CPPS concept will undoubtedly affect the agility, efficiency, adaptability and robustness C-CPPS.

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Fig. 5. Timeline of the Subject role (Adapted from [46])

4 Conclusions, Challenges and Future Research The European Commission has announced a new production philosophy for a sustainable, human-centred and resilient European industry, which has recently emerged under the name Industry 5.0. This paper presents a vision of the future development of the CPPS on the way to a new Industry 5.0. Future cyber-physical manufacturing systems will: 1) maximally digitized, cybernetized, connected, flexible and agile, 2) strongly supported by the new enabling cognitive technologies of Industry 5.0 and 3) make it possible to increase cooperation between man and machine, and emphasize all three aspects of sustainable development. This paper also represents part of the research work in the framework of a doctoral thesis [47] and continuing research in the domain of production systems of the Technologies and Systems research group at the Faculty of Mechanical Engineering, University of Novo mesto.

References 1. Zizic Crnjac, C., Mladineo, M., Gjeldum, N., Celent, L.: From industry 4.0 towards industry 5.0: a review and analysis of paradigm shift for the people, organization and technology. Energies 15(14), 5221 (2022) 2. Hozdi´c, E., Kendi´c, S., Jurkovi´c, Z.: Complex adaptive manufacturing system concept as a cyber-physical production system: solutions to the Covid-19 pandemic challenges. In: CyberPhysical Systems, Boca Raton, pp. 129–156. CRC Press (2022)

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3. Hozdi´c, E., Kozjek, D., Butala, P.: A cyber-physical approach to the management and control of manufacturing systems. Strojniški Vestn. J. Mech. Eng. 66(1), 61–70 (2020) 4. Davis, J., Edgar, T., Porter, J., Bernaden, J., Sarli, M.: Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Comput. Chem. Eng. 47, 145–156 (2012) 5. Monostori, L.: Cyber-physical production systems: roots, expectations and R&D challenges. Procedia CIRP 17, 9–13 (2014) 6. Zhang, L., et al.: Cloud manufacturing: a new manufacturing paradigm. Enterp. Inf. Syst. 8(2), 167–187 (2014) 7. Wang, X.V., Wang, L., Mohammed, A., Givehchi, M.: Ubiquitous manufacturing system based on cloud: a robotics application. Robot. Comput. Integr. Manuf. 45, 116–125 (2017) 8. Morosini, E., Hartmann, J., Makuschewitz, T., Scholz-Reiter, B.: Towards socio-cyberphysical systems in production networks. Procedia CIRP 7, 49–54 (2013) 9. Hozdi´c, E., Butala, P.: Concept of socio-cyber-physical work systems for industry 4.0. Tech. Gaz. 27(2) (2020) 10. Espinoza Pérez, A.T., Rossit, D.A., Tohmé, F., Vásquez, Ó.C.: Mass customized/personalized manufacturing in industry 4.0 and blockchain: research challenges, main problems, and the design of an information architecture. Inf. Fusion 79, 44–57 (2022) 11. Tissir, S., El Fezazi, S., Cherrafi, A.: Lean management and industry 4.0 impact in COVID19 pandemic era. In: Proceedings of the 5th NA International Conference on Industrial Engineering and Operations Management, pp. 3123–3129 (2020) 12. UNCTAD: Impact of the COVID-19: pandemic on trade and development - transitioning to a new normal, Geneva, Switzerland (2020) 13. Chen, T., Lin, C.-W.: Smart and automation technologies for ensuring the long-term operation of a factory amid the COVID-19 pandemic: an evolving fuzzy assessment approach. Int. J. Adv. Manuf. Technol. 111(11–12), 3545–3558 (2020). https://doi.org/10.1007/s00170-02006097-w 14. Kumar, A., Luthra, S., Mangla, S.K., Kazanço˘glu, Y.: COVID-19 impact on sustainable production and operations management. Sustain. Oper. Comput. 1, 1–7 (2020) 15. Tao, F., Cheng, Y., Zhang, L., Nee, Y.C.A.: Advanced manufacturing systems: socialization characteristics and trends. J. Intell. Manuf. 28(5), 1079–1094 (2017) 16. ElMaraghy, H., Monostori, L., Schuh, G., ElMaraghy, W.: Evolution and future of manufacturing systems. CIRP Ann. 70(2), 635–658 (2021) 17. Monostori, L., Váncza, J.: Towards living manufacturing systems. Procedia CIRP 93, 323–328 (2020) 18. Romero, D., Stahre, J.: Towards the resilient operator 5.0: the future of work in smart resilient manufacturing systems. Procedia CIRP 104, 1089–1094 (2021) 19. Patriarca, R., Bergström, J., Di Gravio, G., Costantino, F.: Resilience engineering: current status of the research and future challenges. Saf. Sci. 102, 79–100 (2018) 20. Müller, J.: Enabling technologies for industry 5.0 - results of a workshop with Europe’s technology leaders, Luxembourg (2020) 21. Westkämper, E.: Towards the Re - Industrialization of Europe. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-38502-5 22. Nacional Institute of Standard and Technology (NIST). Smart Manufacturing Operations Planning and Control (2014). https://www.nist.gov/programs-projects/smart-manufacturingoperations-planning-and-control-program 23. Monostori, L., et al.: Cyber-physical systems in manufacturing. CIRP Ann. Manuf. Technol. 65(2), 621–641 (2016) 24. Bauernhansl, T., ten Hompel, M., Vogel-Heuser, B.: Industrie 4.0 in Produktion, Automatisierung und Logistik. Springer, Wiesbaden (2014). https://doi.org/10.1007/978-3-658-046 82-8

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25. Kegermann, H., Wahlster, W., Johannes, H.: Recommendations for implementing the strategic initiative industrie 4.0 final report of the industrie 4.0 working group, Frankfurt an Main (2013) 26. Spath, D., Gerlach, S., Schlund, S.: Cyber-physical system for self-organised and flexible labour utilisation. In: 22nd International Conference on Production Research, ICPR 2013, p. 6 (2013) 27. Özdemir, V., Hekim, N.: Birth of industry 5.0: making sense of big data with artificial intelligence, ‘the Internet of Things’ and next-generation technology policy. OMICS A J. Integr. Biol. 22(1), 65–76 (2018) 28. Nahavandi, S.: Industry 5.0—a human-centric solution. Sustainability 11(16), 4371 (2019) 29. Lu, Y., et al.: Outlook on human-centric manufacturing towards industry 5.0. J. Manuf. Syst. 62, 612–627 (2022) 30. Mourtzis, D.: Towards the 5th Industrial revolution: a literature review and a framework for process optimization based on big data analytics and semantics. J. Mach. Eng. 21, 5–39 (2021) 31. Nardo, M., Forino, D., Murino, T.: The evolution of man–machine interaction: the role of human in Industry 4.0 paradigm. Prod. Manuf. Res. 8(1), 20–34 (2020) 32. Margherita, E.G., Braccini, A.M.: Socio-technical perspectives in the fourth industrial revolution - analysing the three main visions: industry 4.0, the socially sustainable factory of operator 4.0 and industry 5.0. In: 7th International Workshop on Socio-Technical Perspective in IS Development (STPIS 2021) (2021) 33. Maddikunta, P.K.R., et al.: Industry 5.0: a survey on enabling technologies and potential applications. J. Ind. Inf. Integr. 26, 100257 (2022) 34. European Commission: Industry 5.0: towards a sustainable, human-centic and resilient European industry (2021) 35. Pathak, P., Pal, R.P., Shrivastava, M., Ora, P.: Fifth revolution: applied AI & humanintelligence with cyber physical systems. Int. J. Eng. Adv. Technol. 8(3) (2019) 36. Longo, F., Padovano, A., Umbrello, S.: Value-oriented and ethical technology engineering in industry 5.0: a human-centric perspective for the design of the factory of the future. Appl. Sci. 10(12), 4182 (2020) 37. Grabowska, S., Saniuk, S., Gajdzik, B.: Industry 5.0: improving humanization and sustainability of Industry 4.0. Scientometrics 127(6), 3117–3144 (2022) 38. Xu, X., Lu, Y., Vogel-Heuser, B., Wang, L.: Industry 4.0 and industry 5.0—inception, conception and perception. J. Manuf. Syst. 61, 530–535 (2021) 39. Neumann, W.P., Winkelhaus, S., Grosse, E.H., Glock, C.H.: Industry 4.0 and the human factor – a systems framework and analysis methodology for successful development. Int. J. Prod. Econ. 233, 107992 (2021) 40. Bednar, P.M., Welch, C.: Socio-technical perspectives on smart working: creating meaningful and sustainable systems. Inf. Syst. Front. 22(2), 281–298 (2019). https://doi.org/10.1007/s10 796-019-09921-1 41. ElMaraghy, H., ElMaraghy, W.: Adaptive cognitive manufacturing system (ACMS) – a new paradigm. Int. J. Prod. Res. 60(24), 7436–7449 (2022) 42. European Commission: Enabling technologies for industry 5.0: results of a workshop with Europe’s technology leaders (2020) 43. Mourtzis, D., Angelopoulos, J., Panopoulos, N.: A literature review of the challenges and opportunities of the transition from industry 4.0 to society 5.0. Energies 15(17), 6276 (2022) 44. Peklenik, J.: Complexity in manufacturing systems. CIRP J. Manuf. Syst. 24, 17–25 (1995) 45. Butala, P., Sluga, A.: Dynamic structuring of distributed manufacturing systems. Adv. Eng. Inform. 16(2), 127–133 (2002)

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Construction of an Automated Door as a Smart Device Mehmed Cobo1 , Alma Žiga2(B) , and Malik Cabaravdic2 1 FabLab, Sarajevo, Bosnia and Herzegovina

[email protected]

2 Faculty of Mechanical Engineering, University of Zenica, Street Fakultetska 1,

72000 Zenica, Bosnia and Herzegovina {alma.ziga,malik.cabaravdic}@unze.ba

Abstract. Home automation, i.e., automation of home devices is the process of introducing additional functions to existing devices. This usually means partially transforming or completely replacing a standard device with smart devices, after which the control of manual operations can be performed remotely via the Internet. In addition to a number of advantages that smart devices provide from automation of tasks to monitoring specific operations, this paper also analyzes the potential disadvantages of smart devices. In the paper, a smart device is being made, where the goal is to control the door via the web interface of any device with an Internet connection. The key components of the door are servo motor and levers which link shaft of servo motor to the door. The major part of the paper is devoted to the construction of the servo motor which is the drive element of the door, whose construction process is divided into two parts: the software part and mechanical part. The software part consists of a PID controller and a web server, and the mechanical part consists of the electric motor and electronic components. The mechanical relationship between the motor and the door was analyzed and the solution, which supports the local mode of operation of the door and control via the web interface at the same time, was chosen. ESP32 microcontroller and an Arduino platform for implementing code were chosen for data processing and motor movement control. HTML, CSS, JavaScript and “web socket” technologies were used to build the user interface and two-way communication, while the C++ language allows interaction with the microcontroller. Realistic 3D model of the automated door drive element was created using SOLIDWORKS software. Among other things, the key elements of the research in the paper are the increase of privacy and speed of data exchange, which is enabled by the direct connection of devices and users. Keywords: home automation · Arduino · automated door · ESP32 · servo motor

1 Introduction In scientific works ([1–6]) the benefits of smart and automated devices are often mentioned, however, they rarely go beyond presenting a model of the system. In contrast, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 213–220, 2023. https://doi.org/10.1007/978-3-031-31066-9_22

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an automated door [7] was built at full scale, where a functional prototype was built and tested. The most common approach to making a “smart device” is a mechanical device + connection to a web server from the manufacturer + an application for an Android/iOS phone = a new device ([1, 8]). That is, the devices are connected via some kind of wireless connection to a local computer that has Internet access through which contact is made with the device [3]. This has proven to be a good approach for most users, as it is simple. However, networking and privacy do not go well with each other, especially when there are systems with artificial intelligence such as Amazon Alexa, Google Home that can “learn” while processing commands. When such a system is used, it means that there is a database on some server about users and even their habits. This approach has advantages of convenience for the user, but also disadvantages, where 3 potential problems can be observed: 1. Security/Privacy - all communication takes place through a web server that is an intermediary and the phone application is closed source, 2. Reduced flexibility – the interface is primarily within the application, 3. Reduced capabilities if the device is used in a LAN network or off-line. Door automation is usually found in shopping centers or places with high traffic. The most commonly seen design is such that the two panels move translationally in opposite directions. We also see a similar design in ([4, 5, 7]) where the door consists of one panel that moves translationally. In this work, the task is to create a system that can be applied to most doors that are opened by rotary movement. In case it is not able to use the remote opening, the door can be used normally as it has been working. The entire automated door project consists of several parts: • Creation of a servo motor that performs all movements • Creating a website as a user interface • Adding security/authentication for door access. In the work, the focus is on the making a servo motor, which is the drive element of the door. The motor is controlled via an ESP32 microchip with two cores, which is based on RTOS (Real Time Operating System) so that one core can monitor sensors and make calculations, and the other can maintain the web server at the same time. Every part, starting from the microcontroller to the door is 3D modeled in the SOLIDWORKS software in real size 1:1. Such an approach provides an insight into the final appearance of the system and enables the correction of errors during design as well as the prediction of the movement of individual parts. Servo motor provides overall good mechanical characteristics such as torque, rotational speed, positional accuracy and rotational range compared to other drive elements, e.g. hydraulic cylinders. With small system masses, “overshooting” or oscillations around the end position occur due to inadequate PID (Proportional Integral Derivative controller) coefficients, slow data update in the loop, high motor power and/or low inertial force. For each system, it is necessary to set unique PID coefficients so that motor testing and selection of appropriate coefficients should be performed. Variables adjust to the nature of the microchip, such as readout resolution and data processing speed. This

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servo motor is the so-called “continuous servo motor” that has no movement restrictions in any direction, and such a creation is possible by using a position sensor that is not “bound” to the environment. The research is carried out in the direction of achieving a direct P2P (Point-to-Point) Internet connection between the client and the device and the local LAN (Local Area Network) network through a router (Fig. 1.). This would mean that there is no intermediary in the transfer of information, as is the case with systems where communication takes place through a web server. This approach should have a shorter data transfer time compared to a system where a web server was used. During the automation, the original way of using the door is kept, and at the same time, the remote way of controlling the door. The reason for this is to allow people who do not have access to remote controls to use the door. The advantage of this approach would be that in the event of a power failure, the automated door would not be immobilized. Adding security can be provided by digital implementation. A mechanism for protection against unauthorized access, i.e. authentication through a unique code, is built into the user interface website.

Webpage interface

WI-FI

ESP32 microcontroller PWM I2C

Motor controller (H-bridge) PWM

AS5600 magnetic positon sensor (encoder)

DC motor

Fig. 1. Scheme of the automated door construction

The automated door consists of the following elements: • • • • • • • •

ESP32 controller Motor controller Drive element - direct current motor Position sensor - AS5600 magnetic position sensor Source of electric voltage 26 - 30 V Voltage converter to 5 V Metal housing for all components Mechanical levers or links for connecting the motor to the door

Door was moved to a particular angle

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2 Servo Motor Construction Servo motor is a part of a closed-loop system and is comprised of several parts namely a control circuit, servo motor, shaft, potentiometer, drive gears, amplifier and either an encoder or resolver. It rotates parts of a machine with high efficiency and with great precision. The output shaft of this motor can be moved to a particular angle, position and velocity that a regular motor does not have. The servo motor utilizes a regular motor and couples it with a sensor for positional feedback. The controller is the most important part of the Servo Motor designed and used specifically for this purpose [9]. The drive motor is a DC motor for its simplicity and low cost. A jigsaw motor was used for the demonstration, and specifically this motor has a reducer that increases the torque of the motor. A jigsaw motor runs on AC voltage, but it is essentially a DC motor. The explanation follows from the principle of operation of the DC motor: a source of DC voltage is connected to the stator, while the same voltage is connected to the rotor, which is electromagnetically rotated by 90 °. In doing so, an electromotive force is created and the rotor rotates. Since the motor is designed to operate at 230 V, it can easily be converted to a DC motor that operates at a lower voltage. By connecting the windings in a parallel connection and replacing the carbon brushes with copper ones, theoretically, the motor will have the same power at about 3 times less voltage if all the electrical resistances of the windings are equal. The two stator windings must be equal, only the rotor resistance can differ. After connecting the motor, it is necessary to connect it to the motor controller. The usual way of control is by using an H-bridge. The motor controller is connected to the ESP32 microcontroller and controls the motor digitally.

3 Program Code Construction The construction of the code is divided into two parts: • the part responsible for motor control • the part responsible for communication via WIFI connection. The first part is essentially a PID controller. A PID controller is a control loop mechanism employing feedback that calculates the difference between the desired setpoint and a measured process variable and applies a correction based on proportional, integral, and derivative terms (denoted P, I, and D respectively). Construction of the PID controller code takes place in two phases: make the servo motor to stop at a certain point and make a servo motor to follow the trajectory of different time-dependent points. The idea is that if the motor can be easily stopped at a certain point, a curve of various points can be created, i.e. the position of the angle of the shaft in relation to the original position, depending on time. This approach makes it possible to define the motor speed profile as desired. This means that it is possible to make a slight acceleration of the engine, as well as deceleration, while accurately controlling the position, and therefore the speed.

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3.1 Establishing Device-User WIFI Communication The ESP32 can act as a Wi-Fi station, as an access point, or both [10]. If the ESP32 is connected to a wireless router, it can be accessed through the local network. In this situation the router acts as an access point and the ESP32 is set as a station (Fig. 2). It is necessary to be connected to home router (local network) to control the ESP32. To enable the connection to the microcontroller, the plan is to connect the ESP32 to a local router and set up a server that will serve a web page to any client that connects to the ESP32 by typing the 192.168.xxx.xxx address into a web browser. “x” is replaced by the appropriate numbers assigned by the router to the ESP32. The numbers “192.168” are usually universal for almost every router, while the rest changes depending on the configuration of the router. The condition is that the ESP32 and the client are on the same LAN. The web server consists of a web page that is displayed by accessing the device, and the task of the web server is to transfer data from the client to the ESP32 and back. On the ESP32, the code can be divided into two parts: program code responsible for controlling external parameters and PID controller and Web server programming code. In addition to the web page, the web server must have a part of the code responsible for establishing the server itself, and it is mainly constructed through libraries.

Fig. 2. ESP32 set as a station

Since the ESP32 has two cores, it is obvious that the code will be divided into two parts and placed on both cores, namely the web server code on core number 1, because by default it has control over the WIFI functions of the microcontroller, and the other part of the code on core number 0. Both codes are executed independently of each other and there is no mutual conflict at all. If it is necessary to exchange variables between two cores, it must be ensured that they are of global type. 3.2 Designing the User Interface Every device must have a user interface to communicate with the user. For smart devices, this is usually an application that is built in a React Native (JavaScript) or Kotlin environment [11].

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Since access to automated doors is expected most often via mobile phone, the appearance and shape of the interface is intuitively designed according to the shape of the mobile phone. The appearance of the complete interface is presented in the Fig. 6. 3.3 Authorization and Security of Automated Doors The web server hosted by the ESP32 is available both locally and globally. However, precisely because of the global approach, one problem appears: the privacy. Exposing the automated door to the Internet means that anyone can access the ESP32 server and thus control the door. Within a local network there is no need to worry about third parties wanting to access the door because the ESP32 is behind a firewall. That comfort disappears as soon as the firewall is removed. That is why it is very important to protect the ESP32 web server from unauthorized access. One of the ways of protection is the authentication of the person who accesses the server. Accessing the ESP32 via the Internet establishes a real-time connection with the user or users. At that moment, one can get access to all the commands and information available to the ESP32. In order to prevent unauthorized door control and confidential data reading, verification is performed by checking the code that is stored in the internal memory of the microcontroller. On the first visit to the web server of the automated door, it is noticed that all interaction commands are disabled. Then the user is identified and the user is required to enter a code. If the entered code matches the code stored in the ESP32, the commands are activated only for that client/user, that is, for the device through which the door is accessed.

4 Installation of Automated Doors The automated door is switched on by connecting it to a 24 V voltage source. Within a few seconds, the ESP32 starts connecting to the WIFI network and the door becomes available for control via a LAN connection and the Internet. The coefficients of the PID controller are not optimized for this system and because of this a current user interface mod has been created that allows for quick changes of the coefficients while the gate is moving. The user interface now has 3 sliders for the 3 coefficients: Kp, Kd and Ki and they are placed from top to bottom respectively (Fig. 3).

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Fig. 3. Automated door user interface (with sliders – on the left, without sliders – on the right)

The only purpose of the sliders in Fig. 3 is to select the appropriate coefficients Kp, Kd and Ki, and since this was done the sliders became unnecessary to remain in the user interface, and the microcontroller was reprogrammed (Fig. 4.) to function without the sliders and with unchanged Kp, Kd and Ki coefficients.

Fig. 4. Reprogramming ESP32 after calibration

5 Conclusion Communication between the client and the automated door is enabled by a direct local and Internet connection. In this version, the response time is almost instantaneous, however, making such a connection is demanding, because certain conditions must be met and modifications must be made to the home network. The data exchange between the automated door and the client is in real time, however, as could be seen in the practical part, a time delay of up to 1 s is satisfactory.

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References 1. Lita, I., Visan, D.A., Mazare, A.G., Ionescu, L.M.: Door automation system for smart home implementation. In: IEEE 23rd International Symposium for Design and Technology in Electronic Packaging (SIITME), pp. 345–348 (2017) 2. Pakpahan, R.L.H., Sudiharto, D.W., Satwiko, A.G.P.: The prototype of automated doors and windows by using voice commands. In: International Seminar on Application for Technology of Information and Communication (ISemantic), pp. 323–326 (2016) 3. Alkar, A.Z., Buhur, U.: An internet based wireless home automation system for multifunctional devices. IEEE Trans. Consum. Electron. 51(4), 1169–1174 (2005) 4. Zungeru, M., Abraham-Attah, P.O.: A digital automatic sliding door with a room light control system. arXiv preprint arXiv:1303.1728 (2013) 5. Kristyawan, Y., Rizhaldi, A.D.: An automatic sliding doors using RFID and arduino. Int. J. Artif. Intell. Robot. (IJAIR) 2(1), 13–21 (2020) ˇ 6. Cobo, M., Izrada Robotske Ruke Sa Tri Stepena Slobode Kretanja Pomo´cu Arduino Platforme. Mechanical Faculty, Uiversity of Zenica, Zenica (2018) 7. Corpuz, R.S., Longjia, M., Li, Z.Y.: Development of atmel microcontroller based automatic sliding door. Asia Pacific Higher Education Research Journal (APHERJ) 2(1) (2015) 8. Gunge, V.S., Yalagi, P.S.: Smart home automation: a literature review. Int. J. Comput. Appl. 975, 8887–8891 (2016) 9. Gastreich, W.: What is a servo motor?’ and how it works (2018). https://realpars.com/servomotor/#:~:text=A%20servo%20motor%20is%20a,regular%20motor%20does%20not% 20have. [Accessed 19 12 2022] 10. Santos, S.: ESP32 access point (AP) for web server. Random Nerd Tutorials (2019). https:// randomnerdtutorials.com/esp32-access-point-ap-web-server/. [Accessed 21 12 2022] 11. Reshko, A.: Best Programming Languages for Mobile App Development. FortySeven (2020). https://fortyseven47.com/blog/best-programming-languages-for-mobile-app-develo pment/. [Accessed 21 12 2022]

Improvement of the Technique of Optimal Technological Routes Planning for Machining of the Machine Parts Surfaces Yaroslav Kusyi1(B) , Oleh Onysko2 , Andrii Kuk2 , Olha Kostiuk2 , and Bohdan Solohub2 1 Department “Robotics and Integrated Mechanical Engineering Technologies”, Institute of

Mechanical Engineering and Transport, Lviv Polytechnic National University, 8 Bandery Street, Academical Building № 14, Lviv 79013, Ukraine [email protected] 2 Department “Computerized Mechanical Engineering”, Institute of Mechanical Engineering, Ivano-Frankivsk National Technical University of Oil and Gas, 15 Karpatska Street, Ivano-Frankivsk 76019, Ukraine

Abstract. Increasing important requirements for quality parameters of mechanical engineering products and changing the criteria for evaluating the efficiency of technological systems: machine-clamping device-tool-workpiece requires the correction of the technological preparation of production at the Development and Manufacturing stage of Parts in their Life Cycles. Traditional methods of designing technological routes for processing machine parts do not ensure the fulfillment of the set technological tasks. The developed technique of technological routes planning for the treatment of the parts surfaces by machining allows to analyse of the degree of their material degradation using the LM-hardness method and is realized during the manufacturing of the drum’s shaft of the belt conveyor. The values of the coefficients of variation during the machining of the shaft decrease from 10.10–18.80% (for blank) to 0.33–0.57% (after various types of grinding) in the technological chain “blank-final detail”, which indicates the increase in the homogeneity of the material for functional surfaces of the shaft and the reduction of its susceptibility to damageability. Keywords: technological process · technological inheritability · LM-hardness method · homogeneity · object-oriented technology · functionally-oriented technology

1 Introduction In recent decades, research priorities in the reliability theory of technical systems [1, 2] have changed very dynamically in accordance with the high requirements for mechanical engineering details and machines, and their intensive operation conditions [3, 4]. At the same time, the development of new approaches [5–7] for the details manufacturing of various branches of mechanical engineering and the assembly of products with their © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 221–232, 2023. https://doi.org/10.1007/978-3-031-31066-9_23

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necessary operational characteristics and reliability indicators determines the step-bystep evolution of functionally-oriented technologies. Currently, operational safety and complex reliability are the most priority characteristics of modern mechanical engineering systems, which involve the analysis of failures and their consequences with a thorough investigation of their physical nature of processes and phenomena [2, 7, 8]. The complex solution of production tasks is determined by the technological provision of accuracy characteristics, parameters of the surface layer of mechanical engineering parts, priority operational characteristics, and reliability indicators [9–11]. However, all parameters of the quality for the parts and machines are closely related to the possibilities of management and prediction of behaviour in their Life Cycles (PLM - Product Life Cycle Management) in accordance with the important concepts and postulates of Industry4.0 [12, 13].

2 Literature Review 2.1 Analysis of Methods of Technological Route Planning for Parts Manufacturing in According with the Principle of Object-Oriented Technologies In mechanical engineering, traditional and progressive methods of technological route planning for the machining of functional surfaces of machine parts are used. Traditional methods of technological route planning for the machining of parts surfaces for providing of the principle of object-oriented technologies include tabular and discrete-analytical methods [14]. The principle of object-oriented technologies during the manufacturing of mechanical engineering parts involves the step-by-step performance of interconnected stages using typical technological processes. Refinement of the quality parameters for the surfaces of the parts takes place according to the principle of technological inheritability after each technological step to provide the regulated requirements. The minimum technological cost of parts manufacturing is an optimization criterion during the development of a rational variant of the technological process [15]. The tabular method is characterized by ensuring the regulated requirements for the accuracy and quality of functional surfaces using typical technological routes for their machining. It is a preliminary method that is used for determining the production type and form of its organization during design and technological preproduction in the Life Cycle of a Part/Product. The implementation of tabular method requires the highest level of designer ang technologist qualification. But the operational conditions of the parts aren’t analysed during their technological route planning [14]. Determining of the general refinement is the goal of the technological route planning of machining for the certain functional surface of parts using the discrete and analytical method. Possible methods of surface machining are calculated by using of the refinement coefficient εi , which numerically evaluates the inheritability of the properties of mechanical engineering part from the previous to the current technological step [14]: εi [TOPi−1 ]/[TOPi ],

(1)

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where [TOpi-1 ], [TOpi ] are the limiting characteristics for the possible machining methods of the functional surface of the part at the previous and current technological steps respectively. In mechanical engineering production, the machining accuracy of a functional surface of the mechanical engineering parts is the most priority criterion for the calculation of the refinement [14]: εi = Ti−1 /Ti ,

(2)

where T i-1 , T i are the tolerance of the size ensured at the previous and current technological steps according to the achievable tolerance grade respectively. The deviations of selected tolerance degree are chosen in accordance with normative tables for a certain size range. The estimated refinement εest. is determined using the accuracy criterion [14]: εest. = Tbl. /Tpart ,

(3)

where T bl. is the tolerance of the blank in accordance with its regulated accuracy and roughness for a certain method of obtaining a work piece after the blank production stage; T part is the tolerance of the mechanical engineering part according to the regulated requirements of the technical documentation. The number of technological methods by machining n is determined by [14]: n = g(εest. )/0.46.

(4)

The check of the number of the technological methods by machining n is implemented by [14]: n 

εi ≥εest. .

(5)

i=1

The accuracy of the functional surfaces of the mechanical engineering part regulated by the designer needs to be consistent with the height parameters of roughness Ra or Rz [16]. However, for some details (machine stands, machine platens, etc.), technical requirements of the surface layer quality of their functional surfaces are higher than the accuracy specifications. Thus, the current refinement is calculated by the height parameters of roughness Ra or Rz [14]: εi = Ra(Rz)i−1 /Ra(Rz)i ,

(6)

where Ra (Rz)i-1 , Ra (Rz)I are the roughness parameters Ra or Rz for certain part surface at the previous and current manufacturing steps respectively. The estimated refinement of εest. is determined by [14]: εest. = Ra(Rz)bl. /Ra(Rz)part ,

(7)

where Ra (Rz)bl. , Ra (Rz)part are the surface roughness parameters of the blank and part respectively.

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2.2 Analysis of Developed Methods of Technological Route Planning for Parts Manufacturing in Accordance with the Principle of Functionally-Oriented Technologies The complication of the operating conditions of machine parts requires a set of accuracy characteristics, quality parameters of surface layers, and deviations of shape and mutual arrangement of surfaces during their technological process planning for product manufacturing. Providing of accuracy for the surface’s shape and mutual location is more difficult than maintaining the size with tight tolerances, and the normalization of geometric indicators allows to control of the quality parameters in the connections of machines. The operating conditions of machines and their details differ significantly. However, they have a dominant influence on the consideration of hereditary properties during parts manufacturing. Wear is the main type of damage and failure to the connected surfaces of mechanical engineering parts. In particular, the functional surfaces of shafts, housings, gears, levers, bushings, guides, etc. work in intensive conditions of friction, fatigue, corrosion etc. Technological defects formed at the development and production stage in the Life Cycles of machine parts transform into damage under the influence of various indicators: force loads, temperature effects, mechanical interactions, electric and magnetic fields, aggressive environments, etc. during their operation. Technological provision of structural homogeneity of the surface layer for the functional surfaces of mechanical engineering parts is a necessary condition for the operability of parts and machines [17–19]. Therefore, increased requirements apply to the wear resistance of the functional surfaces of the moving connected elements, because their wear increases the stress level in machine parts [20]. Image processing methods [21] and methods of assessing the strength of products with cracks [22, 23] are effectively used to investigate damage to the surfaces of metal structures. The defined physical and mechanical characteristics are used in mechanical engineering to estimate the state and dynamics of changes in the properties of details materials at important substages and stages in their Life Cycles [3, 14]. In particular, the analysis of the plasticity and strength of the material of the parts is carried out by calculating the results of macro-hardness measurements. In addition, macro-hardness determines the degree of resistance to brittle fracture and plastic deformation upon contact with the indenter [17]. At the same time, the weak sensitivity of macro-hardness to many types of structural transformations in the surface layers of parts materials and a certain ambiguity in the relationship between measured values of macro-hardness with strength, yield strength and other physical and mechanical characteristics limits the use of the classical method of controlling macro-hardness in engineering practice [24, 25]. The results of measurements of the absolute or average values of the macro-hardness of the parts materials are interpreted ambiguously, because they depend on the accepted conditions and the specifics of the measurement methods [3, 17]. Therefore, macro-hardness is only presented as a generalized characteristic for evaluating the elastic-plastic properties of the material of machine parts. At the same time, the average value of macro-hardness, obtained as a result of experimental investigations

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of material properties, doesn’t contain reliable information about its current stress-strain state [24, 25]. The average value of macro-hardness is used to estimate the condition of the surface layer of the part’s material during traditional experimental investigations. In contrast, the LM-hardness method developed at G. S. PISARENKO IPS OF NAS OF UKRAINE under the guidance of academician A.A. Lebedev, offers a significantly different approach to the analysis of changes in the surface layers of the material of mechanical engineering parts. A.A. Lebedev theoretically substantiated and experimentally confirmed the expediency of estimating the structural state using derivatives of the absolute values of material characteristics, in particular, the dispersion of the results of measurements carried out on the same samples under the same conditions. This method is most easily implemented in engineering practice using macro-hardness as a mechanical characteristic. The LM-hardness method is implemented by evaluating the dispersion of macro-hardness as a priority mechanical characteristic of the material of engineering parts [3, 24, 25]. The Weibull distribution is used to solve problems in material science, in particular, for developing statistical theories of strength. At the same time, homogeneity is an indicator characterizing the state of the material of mechanical engineering parts for evaluating the results of macro-hardness control. Homogeneity is represented by the Weibull distribution [24, 25]: P(σ ) = 1 − e−( k ) , σ m

(8)

where the structurally sensitive parameter – the Weibull homogeneity coefficient (WHC) (m) determines the degree of degradation of the structure of the surface layer of the material. It is calculated by [24, 25]: m=

d (n) , 2,30259 · S(g(H ))

(9)

where d(n) is a certain parameter that depends on the number of measurements n [3];   n n   1  2 1  S(g(H )) =  · g(Hi ) − g(H ) , g(H ) = · g(Hi ). (10) n−1 n i=1

i=1

The ratio of the sizes of the existing defects and the studied sample determines the structural heterogeneity of the object of research. The main influence of statistical factors on the strength of a structurally heterogeneous material occurs during the evolution of microcracks under the action of determined normal stresses. The structural inhomogeneity of the part material is determined, in particular, by the value of WHC (m), in particular, m < 10 corresponds to structurally inhomogeneous materials; m ≥ 10, on the contrary, is for structurally homogeneous materials [14]. The technique of technological routes planning for parts manufacturing by the dynamic changes of the values of the homogeneity coefficient for their material in accordance with the principle of technological inheritability of products properties was developed in the work [3, 14].

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The estimated refinement εest. is calculated by [14]: εest. = mpart /mbl. ,

(11)

where mpart , mbl. are the WHC for the part (detail) and blank respectively. Refinement for the i-th technological step using the calculated scattering characteristics of the material hardness is determined by [14]: εi = mi /mi−1 ,

(12)

where mi , mi-1 are WHC at the current and previous technological steps respectively.

3 Aim and Object of Researches The aim of the research is to improve the technique of rational technological routes planning using machining during part’s manufacturing. The object of researches is the Development and Creation Stage in Life Cycle of a Part from the blank to the final detail.

4 Research Methodology 4.1 Development of Material Homogeneity Criterion for Parts Manufacturing Technical requirements for mechanical engineering details, as a rule, don’t regulate the entire set of basic material parameters for their functional surfaces but are often limited to the values of roughness and microhardness characteristics. The optimal structure of technological operations isn’t always taken into account during the technological processes planning for parts manufacturing and assembly of machines. Material properties are insufficiently analysed during the machining of machine parts, although at the operation stage they’ll change significantly under the influence of loads, high temperatures, the influence of aggressive media, etc. The condition of the functional surfaces of machine parts during their manufacturing or operation for a specific material is often analysed based on the results of changes in the WHC(m) [3, 14, 17, 24, 25]. Degradation of the material of the surface layer for mechanical engineering parts will differ for different materials with different physical and mechanical properties. Therefore, it is necessary to use other indicators, establishing their relationship with the WHC(m) for clarifying of the condition for the surface layer of mechanical engineering parts. The material homogeneity criterion (MHC) is proposed for the analysis of processes and phenomena related to the degradation of the material of machine parts in their Life Cycles. It is described and characterized by the homogeneity of the material of the part as a parameter for evaluating and analysing the technological inheritability of the parameters for the functional surfaces of the parts during their manufacturing and further operation. MHC is described by the main indicators: the Weibull homogeneity coefficient (m), the coefficient of variation ν, the material constant Am , technological damageability D and the intensity of its growth jD . In a specific case, MHC indicators describe the degree of material degradation:

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– for technological step during a certain technological operation using technological inheritability of properties MHC ∈ [m = f (H1 , H2 ......); ν = f (H1 , H2 ......); A = f(m); D = f(m); jD = f(m); ε= mi /mi−1 ],

(13)

– during the process of technological inheritability of part quality parameters from the blank to the final detail

(14)

– for the structurally heterogeneous state of the material of the surface layers for the mechanical engineering detail m < 10; ν → 1(100 %); Am < 0.878; D → 1, jD → ∞,

(15)

– for the structurally homogeneous state of the material of the surface layers for the mechanical engineering detail. m ≥ 10; ν → 0; Am ≥ 0.878; D → 0; jD → 0,

(16)

where t 0k is the machining time during the performing of the k-th technological step (method of machining); T 0 is the total machining time for machining of a certain surface of a mechanical engineering part. The coefficient of variation ν is calculated by [3, 23]:   n   1 2  · (17) Hi − H /H , ν= n−1 i=1

where H is the average value of the material hardness of the parts. The constant of the material Am is determined by [14]:

1 m+2 m , Am = 4m + 4

(18)

where m is the homogeneity coefficient in the Weibull distribution. The technological damageability D is calculated by [3]: D = (mmatr. − mi )/mmatr. ,

(19)

The intensity of growth of technological damageability jD is determined by [3]: jD = (mmatr. − mi )/mi ,

(20)

where mmatr. , mi are the Weibull homogeneity coefficients (m) determined by the dispersion of the macro-hardness of the base material and the i-th section of the detail respectively.

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4.2 Development of Technique of Technological Route Planning for Parts Manufacturing Using the MHC Indicators Structurally sensitive characteristics (m) is widely changed: m ∈ [0; ∞]. If m = 0, then the degree of the material degradation of mechanical engineering details will achieve the highest value. Large values of the coefficient (m) correspond to a low level of dispersion of hardness characteristics and, consequently, a better organization of the structure, a low level of damage, lower values. On the contrary, less values of the coefficient (m) correspond to a high level of dispersion of hardness characteristics and, consequently, a worse organization of the structure, and higher level of damage. A significant range of changes for coefficient (m) is inconvenient for comparative analysis of degradation processes of different materials. For example, m = 50 may be satisfactory for some materials, but m = 100 may be unsatisfactory for others. The coefficient of variation ν is widely changed: ν ∈ [0; 1] or ν ∈ [0; 100%]. If ν = 100% (ν = 1), then the degree of the material degradation of mechanical engineering details will achieve the highest value. The coefficient of variation ν is more convenient to use than the homogeneity coefficient (m) for comparative assessment of the condition of the surface layer of the detail for different materials or different sections. Therefore, the method of technological routes planning of the functional surfaces for the parts manufacturing can be improved by calculating refinements based on the ratios of the coefficients of variation. The estimated refinement εest. is calculated by: εest. = νbl. /νpart ,

(21)

where ν bl. , ν part are coefficient of variation for the blank and part (detail) respectively. Refinement for the i-th technological step using the calculated scattering characteristics of the material hardness is determined by: εi = νi−1 /νi ,

(22)

where ν i-1 , ν i are coefficient of variation at the previous and current technological steps respectively. 4.2.1 Experimental Research Methodology The optimal technological routes planning for functional surfaces during their manufacturing using experimental investigations is performed for the drum’s shaft of the belt conveyor (see Fig. 1) [14]. Material of the detail is steel 40X DSTU 7806 (European analogies are 37Cr4, 37Cr4KD, 41Cr4, 41Cr4KD, 41CrS4). The bank type is round. Overall dimensions of the initial blank are ∅ 160 × 2105 mm, weight of blank is 332.24 kg, weight of the detail is 243 kg and material using coefficient – 0.73 [14]. The machining accuracy of the shaft necks is a criterion for analysing the estimated refinements using the principle of object-oriented technologies [14] (see Fig. 1) in accordance with the analysis of service functions of that detail.

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Fig. 1. Drum’s shaft of the belt conveyor [14]

Determining the methods of shaft surfaces by machining using the criterion of accuracy and technological routes planning of their cutting was realized by means of (2)–(5). Homogeneity of the machined material during the experimental investigations was analysed using the current values of coefficient of variation νby means of (17). Hardness was measured by means of a portable hardness tester TD-42 (“Ultracon”) in accordance with the large sizes and weight of the workpiece. The standard Brinell method of hardness measurement was used during the experimental investigations [14]. The hardness of the shaft’s workpiece was measured in axial sections under the location of its functional surfaces – necks, keeping the dimensions, ∅ 90h7, ∅ 125h7 (from the left), ∅ 148h9 (from the left), ∅ 148h9 (from the right), ∅ 125h7 (from the right) and the free surface in the size ∅ 156h14 (see Fig. 1). 30–35 hardness measurements are performed for each neck of the workpiece during two series of experimental investigations [14]. The main feature of the discrete and analytical method of designing the structure of technological routes for machining certain surfaces during the process of definition of estimated refinement is to calculate the ratio of table values of tolerance fields. In contrast, experimental-analytical method allows determining the estimated refinement due to the real material parameters for a given processing method at a specific technological step. Therefore, estimated refinements according to the discrete-analytical method are overestimated compared to the experimental-analytical method (see Fig. 2). The accepted number of surface treatment methods, calculated according to the traditional technique (criterion – machining accuracy) and developed techniques (criterion – Weibull homogeneity coefficient; criterion – coefficient of variation), are identical based on research results. However, the calculated values of the methods number of surface machining using the traditional technique are greater than calculated according to MHC criteria, by 11.7–24.6%. That ratio can lead to an increase in the number of machining when a technologist chooses a less accurate blank. On the other extreme, the change of estimated refinements is smoother for the developed method of technological route planning than for the traditional one. The change law of estimated refinements from rough turning methods to finish grinding in the technological chain “blank-finish detail” is similar to exponential. Markov chains describe

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Fig. 2. Change of intermediate refinements after each technological steps using criterions of accuracy and material homogeneity (coefficient of variation) a) and criterions of accuracy and material homogeneity (WHC) b) for machining routes of a shaft surfaces in accordance with the technological inheritability (t1 (n1 ), t2 (n2 ),…, tk (nk ) – time spans of 1, 2, k technological steps; (IT ), (ν), (m) – change of intermediate refinements using the machining accuracy, coefficient of variation and the homogeneity coefficient of the material)

the exponential laws of physical parameters and they can use to analyse and estimate the physical process and phenomena in further investigations.

5 Conclusion The main conclusions have been drawn based on the research results. 1. The structure of technological routes for machining the surfaces of machine parts is determined by the tabular method, the discrete and analytical method, and the experimentally-calculation method, depending on the principle of the implemented technologies, the regulated technological tasks, and the technological capabilities of the current production. 2. The previously developed technique of technological routes planning for machining the surfaces of machine parts by analysing the dynamics changes of the Weibull homogeneity coefficients allows taking into account current changes in the surface layer of the material for a certain technological step using the necessary cutting method. However, the wide range of changes in the coefficient (m) makes it difficult to compare the obtained research results for a wide range of mechanical engineering details with different physical and mechanical parameters of their materials. 3. The coefficient of variation ν due to the narrower range of its change ν ∈ [0; 1] (ν ∈ [1; 100%]) is more flexible and informative criteria than the homogeneity

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coefficient (m) for comparative assessment of the condition of the surface layer of the detail for different materials or different sections. The values of coefficient of variation ν decrease from 10.10–18.80% (for the starting workpiece) to 0.55– 0.57% (after rough grinding) and 0.33–0.34 (after finish grinding) during the steel shaft manufacturing. Large values of coefficients of variation and their significant dispersion for the material of blank are characterized by the various defects in its surface layer: pores, microcracks, etc., which indicates a high level of degradation of the shaft material. The cutting of the defective layer of shaft’s material during rough and finishing turning is accompanied by a decrease in the coefficients of variation during the machining of all shaft necks, which determines the increase in the homogeneity of the material of functional surfaces and the reduction of its susceptibility to damageability. The highest degree of homogeneity of the material of the shaft surfaces is ensured at the technological steps of rough and finish grinding. 4. Further research will concern the expansion of the nomenclature for machine parts and their materials and the introduction of the developed technique into the practice of mechanical engineering industry.

References 1. Davim, J.P.: Surface Integrity in Machining. Springer, London (2010). https://doi.org/10. 1007/978-1-84882-874-2 2. Bertsche, B.: Reliability in Automotive and Mechanical Engineering. Springer, Germany (2008). https://doi.org/10.1007/978-3-540-34282-3 3. Kusyi, Ya.M., Stupnytskyy, V.V., Kuk, A.M., Topilnytskyy, V.G.: Development of the fundamental diagram of the formation and transformation of the products properties during their manufacturing. J. Phys. Conf. Ser. 1781(1), 012027 (2021). https://doi.org/10.1088/17426596/1781/1/012027 4. Kachan, O., Pavlenko, D., Ulanov, S.: Relaxation of the technological residual stresses during the thermal exposure in titanium samples. In: Altenbach, H., et al. (eds.) CAMPE 2021. LNME, pp. 247–255. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-18487-1_25 5. Ropyak, L.Ya., Vytvytskyi, V.S., Velychkovych, A.S., Pryhorovska, T.O., Shovkoplias, M.V.: Study on grinding mode effect on external conical thread quality. IOP Conf. Ser. Mater. Sci. Eng. 1018(1), 012014 (2021). https://doi.org/10.1088/1757-899X/1018/1/012014 6. Berladir, K., Hovorun, T., Botko, F., Gusak, O., Denysenko, Y.: Effect of Ti-Zr ligature on microstructure and mechanical properties of automotive silumin. In: Tonkonogyi, V., Ivanov, V., Trojanowska, J., Oborskyi, G., Pavlenko, I. (eds.) Advanced Manufacturing Processes IV. InterPartner 2022. LNME, pp. 253–263. Springer, Cham (2023). https://doi.org/10.1007/9783-031-16651-8_24 7. Kumar, K., Zindani, D., Davim, J.P: Sustainable Manufacturing and Design. Woodhead Publishing, Cambridge, United Kingdom (2021) 8. Kołowrocki, K., Soszy´nska-Budny, J.: Reliability and Safety of Complex Technical Systems and Processes: Modeling—Identification—Prediction— Optimization. Springer, London (2011) https://doi.org/10.1007/978-0-85729-694-8 9. Bazaluk, O., Dubei, O., Ropyak, L., Shovkoplias, M., Pryhorovska, T., Lozynskyi, V.: Strategy of compatible use of jet and plunger pump with chrome parts in oil well. Energies 15(1), 83 (2022). https://doi.org/10.3390/en15010083

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10. Bembenek, M., et al.: Microstructure and wear characterization of the Fe-Mo-B-C—based hardfacing alloys, deposited by flux-cored arc welding. Materials 15(14), 5074 (2022). https:// doi.org/10.3390/ma15145074 11. Shatskyi, I.P., Perepichka, V.V., Ropyak, L.Y.: On the influence of facing on strength of solids with surface defects. Metallofizika i Noveishie Tekhnologii 42(1), 69–76 (2020). https://doi. org/10.15407/mfint.42.01.0069 12. Stefana, E., Marciano, F., Cocca, P., Alberti, M.: Confined space risk management in steel industry: towards the adoption of industry 4.0 technologies. In: Proceedings of the Summer School Francesco Turco, Italy, Brescia, pp. 94–100 (2018) 13. Cocca, P., Marciano, F., Rossi, D., Alberti, M.: Business software offer for industry 4.0: the SAP case. IFAC-PapersOnLine 51(11), 1200–1205 (2018). https://doi.org/10.1016/j.ifacol. 2018.08.427 14. Kusyi, Y., Onysko, O., Kuk, A., Solohub, B., Kopei, V.: Development of the technique for designing rational routes of the functional surfaces processing of products. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) NT 2022. LNNS, vol. 472, pp. 135–143. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_16 15. Stupnytskyy, V.: Features of functionally-oriented engineering technologies in concurrent environment. Int. J. Eng. Res. Technol. 2(9), 1181–1186 (2013) 16. Grzesik, W.: Prediction of the functional performance of machined components based on surface topography: state of the art. J. Mater. Eng. Perform. 25(10), 4460–4468 (2016). https:// doi.org/10.1007/s11665-016-2293-z 17. Kusyj, J.M., Kuzin, O.A., Kuzin, N.O.: The dependence of intergrain damageability of casting on the technological treatment route. East. Eur. J. Enterp. Technol. 1/5(79), 39–47 (2016). (in Ukrainian). https://doi.org/10.15587/1729-4061.2016.59845 18. Attanasio, A., Ceretti, E., Outeiro, J., Poulachon, G.: Numerical simulation of tool wear in drilling Inconel 718 under flood and cryogenic cooling conditions. Wear 458–459, 203403 (2020). https://doi.org/10.1016/j.wear.2020.203403 19. Colpani, A.,Fiorentino, A.,Ceretti, E., Attanasio, A.: Tool wear analysis in micromilling of titanium alloy. Precis. Eng. 57, 83–94 (2019). https://doi.org/10.1016/j.precisioneng.2019. 03.011 20. Ropyak, L.Y., Velychkovych, A.S., Vytvytskyi, V.S., Shovkoplias, M.V.: Analytical study of “crosshead - Slide rail” wear effect on pump rod stress state. J. Phys Conf. Ser. 1741(1), 012039 (2021). https://doi.org/10.1088/1742-6596/1741/1/012039 21. Bembenek, M., et al.: Multiclass level-set segmentation of rust and coating damages in images of metal structures. Sensors 22(19), 7600 (2022). https://doi.org/10.3390/s22197600 22. Shatskyi, I.P., Makoviichuk, M.V., Shcherbii, A.B.: Equilibrium of cracked shell with flexible coating. In: Shell Structures: Theory and Applications, Proceedings of the 11th International Conference on Shell Structures: Theory and Applications, SSTA 2017, Poland, Gda´nsk, vol. 4, pp. 165–168 (2018). https://doi.org/10.1201/9781315166605-34 23. Shats’kyi, ІP., Makoviichuk, МV., Shcherbii, АB.: Influence of a flexible coating on the strength of a shallow cylindrical shell with longitudinal crack. J. Math. Sci. 238(2), 165–173 (2019). https://doi.org/10.1007/s10958-019-04226-9 24. Lebedev, A.A., Makovetskii, I.V., Muzyka, N.R., Volchek, N.L., Shvets V.P.: Assessment of damage level in materials by the scatter of elastic characteristics and static strength. Strength Mater. 38(2), 109–116 (2006) 25. Lebedev, A.A., Muzyka, N.R., Volchek, N.L.: Determination of damage accumulated in structural materials by the parameters of scatter of their hardness characteristics. Strength Mater. 34(4), 5–11 (2002)

3D Printed Souvenir with Mechanical Iris Žiga Alma(B) , Kaˇcmarˇcik Josip, and Behadarevi´c Ismir Faculty of Mechanical Engineering, University of Zenica, St. Fakultetska 1, 72000 Zenica, Bosnia and Herzegovina [email protected]

Abstract. The paper presents the design and 3D printing of the souvenir for the Archaeological park “Ravne 2” in Visoko. The souvenir has the shape of a hexagon box, since most of the buildings in the park have a hexagonal base. On the top of the box is a mechanical iris lid consisting of six equilateral triangles that move and make on opening by turning the hexagon base. An analytical and numerical method for determining the bending stress of columns in a rotating base has been given, since they are the most loaded part of the assembly. The method of 3D printing of the box has been described and practical advices have been given for the design of the mechanical models made by 3D printing. Keywords: Souvenir · Hexagon box · Mechanical iris · 3D printing

1 Introduction The word ‘souvenir’ originated from French, in which it literally means ‘memory’. This indicates that the souvenirs’ primary function is to serve as a reminder or link between the destinations and tourist’s special moments or experiences from the time spent there [1, 2]. In 1986, Beverly [1] sorted souvenirs into five categories: the pictorial image (postcards or magnet), piece-of-the-rock (the object collected from nature), symbolic shorthand (the item with landmark signs or patterns), markers (the product with the mark of which it came from) and a local product (indigenous product of destination). The paper presents design, analysis and 3D printing process of the souvenir shaped as a hexagon box with mechanical iris as a box lid. The souvenir was designed for the Archaeological Park “Ravne 2” as symbolic shorthand. Many buildings in the Park were built with a hexagonal base: meditation platforms, concert platform, multimedia hall, fountains. The mechanical iris was added to give box an intricate design.The hexagon itself has very power meaning as it is found throughout nature and is integrated in a lot of sacred geometry shapes [3].

2 Design of Hexagon Box with Mechanical Iris Figure 1 shows a hand-drawn sketch of a box. The approximate dimensions of the box are φ 120 x 50 mm. The wall thickness is 4 mm. The lid consists of 6 equilateral triangles © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 233–240, 2023. https://doi.org/10.1007/978-3-031-31066-9_24

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that take on the role of the iris petals. As it can be seen in the picture, the idea is to move the triangles and open the lid by turning the bottom, i.e. the base of the box in relation to the housing. On this model the base is movable relative to the fixed housing, however this only applies to the model, in reality both parts are movable, depending on which part is held in the hand and which rotates.

Fig. 1. Freehand sketch of a hexagonal box with a mechanical iris

In order to enable the box to be opened in this way, cylindrical columns are placed on the moving base (Fig. 2). In the triangles, which form the lid, grooves in which the columns slide are cut. By turning the base, the columns move the triangles. The length of the grooves on the triangles defines the starting and ending positions of the openings of the lid. To insure the stability of the triangles, below them, in line with the upper surface of the housing, it is necessary to install another ring on the columns. This ring serves as an additional support to prevent instability and tilting. The problem that now arises is that none of these parts are attached to each other, as this would prevent sliding and rotation, which is essential for opening or closing the box. The columns move inside the grooves of the triangles, the triangles slide on the housing and the housing slides on the base. Since there is no connection between these parts of the box, the box could fall apart when handled. This problem was solved by introducing an additional part called a pin. A pin is a small flat piece that is glued to the top of each column. This restraint the lid movement in a vertical direction, which effectively seals the box. Once all the parts in SolidWorks have been modeled, a hexagonal box assembly needs to be made. The assembly of the box is very simple, which was one of the primary goals. All ready-to-assemble parts are shown in Fig. 2.

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Fig. 2. All parts of the box

Complete assembly is on Fig. 3 that shows how to open the box by rotating the base of the box relative to the housing.

Fig. 3. Opening the box

3 Stress Analysis in Column Base 3.1 Analytical Calculation The features of the box that are exposed to the greatest bending and shear stresses are the base of the columns. In the end position, when the box is fully opened, due to the contact of the column tops and the triangle grooves, the contact force causes bending of the columns. The question is how much maximum moment an adult could create when opening a box and whether that moment is enough to break a column. Based on the conducted

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Gender

Average torque [Nmm]

Male (12)

9670

Female (10)

5910

Average

7960

Fig. 4. Freely movable jar [4]

anthropometric tests, the most appropriate test is the maximum torque, which females and males can produce when opening the jar. In the study [4] 22 adults participated. The opening torque in Nm was measured on a jar lid with diameter of 66 mm using both hands on a free jar as in Fig. 4. Table 1 shows the test results. Table 2. 3D printing parameters in UltimakerCura Quality

Layer Height

0.15 mm

Bottom Layer Height

0.2 mm

Line Width

0.35 mm

Shell

Wall Thickness

1 mm

Infill

Infill Density

20%

Material

Printing Temperature

210 C

Speed

Print Speed

60 mm/s

Support

Enable Support

Without

Build Plate Adhesion

Build Plate Adhesion Type

Brim

Brim Margin

7 mm

The moment selected for the calculation is the average value of the moment that a female person can produce when opening a jar, because the souvenir needs to be handled carefully. In the following, the force F acting on the end of the column due to the contact with the triangular cover is calculated. The following information is required: L = 52 mm – length on column between base and contact area center, T = 5910 Nmm – the maximum torque that a female person can achieve when unscrewing the jar lid, T 1 = T 6 = 985 Nmm – moment acting on one column, R = 47 mm – radius of central column circle,

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d = 7 mm – column diameter, F = T 1 / R = 20.957 N- force on column due to contact with the groove. Bending stress in the base of the column [5]: σ =

32 · F · L = 32.36 MPa d 3π

(1)

To calculate the deflection, the value of the modulus of elasticity is required. The material of the box ispolylactic acid (PLA). The modulus of elasticity of PLA varies depending on the parameters of 3D printing (filling, printing temperature, etc.), but the value that is most often adopted, and which is most often found in the literature is 3.125 GPa [6, 7]. The expression for calculating the deflection of a console with concentrated force at the end is [8]: y=

F · L3 = 2.67 mm 3Em · Ix

(2)

3.2 Numerical Calculation In order to perform stress analysis in the SolidWorks Simulation module, it is necessary to first define the material. The SolidWorks database does not contain PLA data, so it is necessary to manually define the material. The yield stress for PLA is in the range of 37–70 MPa [6, 7]. A lower value was adopted. Figure 5 shows the PLA data entered into the SolidWorks database. It is not necessary to use the whole model for the analysis. The shape of the hexagon gives the box six axes of symmetry, so that only one-sixth of the model can be observed. Thus, a section of the base with column was used for the analysis as in Fig. 6. The base was fixed and a force was applied to the end of the column in the area of contact with the triangle.

Fig. 5. PLA material in SolidWorks

The equivalent, Von Mises, stress at the bottom of the column which is compound from bending and shearing stresses is 39.5 MPa and it is higher than the yield stress of

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Fig. 6. Analysis of stress and deflection

the PLA material. This leads to the conclusion that an adult could break the columns by applying maximum torque when opening the box. However, a hexagon box is a mechanical souvenir, and proper use and careful opening should not create stresses that would lead to breakage.

4 Hexagon Box Printing In order to print parts of the box, using a 3D printer, it is first necessary to save all 3D models created in one of the CAD software, such as SolidWorks, as STL files. Then these STL files need to be loaded into one of the G-code generation software, in this case the UltimakerCura software. For the 3D printing of the parts, Ultimaker S3 and Ultimaker S5 3D printers are used. After loading the STL file, it is necessary to set the 3D printing parameters [9].These parameters directly affect the G-code, and dictate how the part is printed. First it is necessary to properly position the model on the base. Model positioning and orientation are very important factors in 3D printing. Orientation directly affects the quality (precision) of the print, the time required to print the part, the strength of the part, as well as the surface roughness. When the model is positioned correctly, the 3D printing parameters are defined. The print parameters for generating G-code are in Table 2. By defining the required parameters, a G-code is generated, and the model is ready for 3D printing. For example, the time required to print the “base with columns” part was 5 h and 57 min and it required 66 g of PLA material. The box was printed twice. The first sample (Fig. 7) was a test one, due to doubts about the size of the clearance that is needed between certain parts for the box. The first sample was half successful. The box performed its intended function without major problems, without too much friction between moving parts and without braking of any kind. The biggest problem was the excessive clearance between the triangles and pins,

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and between the triangles themselves, which resulted in a rather loose assembly of lid that could move up to a few millimeters in both horizontal and vertical directions, in both open and closed positions. It has been observed that a 3D printer almost always produce larger dimensions than the designed one in the CAD model. On average, it adds between 0.3 to 0.5 mm, so that in the case if a lose fit is wanted, it is concluded that the clearance of 1 mm in a CAD model should be sufficient.

Fig. 7. Test sample of hexagonal box

5 Conclusion The hexagon box is a mechanical souvenir made of 215 g of relatively fragile material, and as such should be handled carefully. Analytical and numerical analysis of stresses in the base columns was performed. The columns are elements of the box that are exposed to the highest stresses and the goal was to find out if an adult could do damage to the columns. The average adult female can achieve a torque of 5910 Nmm when opening the jar, and the analysis showed that this torque was enough to potentially break the column. The recommendation for the following mechanical souvenirs is that the pins and columns should be made of stronger material (metal or wood) due to the bending, torsional and shear loads to which they are exposed. The box was printed twice. The first sample was a more experimental, trial specimen, to see if a box like this could work at all. The first sample was a partial success. The opening and closing was possible without any problems, however excessive clearances between individual parts of the box resulted in a rather loose assembly and wobbly box. The second, final sample was much more successful. Initial errors have been corrected, such as too much clearance between the pins and the triangles, and too much clearance between the triangles themselves. The tilting and movement of the lid triangles was greatly reduced, resulting in a much firmer box assembly. Of course, the second sample of the box was not perfect either and there is still a lot of room for improvement. In reality, the situation is always a little different from the situation assumed by the

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software, especially when it comes to 3D printing technology, which has many different settings on which the final results depend, and it takes a lot of work and experience to achieve the desired results.

References 1. Beverly, G.: The souvenir: messenger of the extraordinary. J. Popular Cult. 20(3), 135 (1986) 2. Collins-Kreiner, N., Zins, Y.: Tourists and souvenirs: changes through time, space and meaning. J. Herit. Tour. 6(1), 17–27 (2011) 3. Baugh, S.L.: Hexagon Encyclopedia Britannica (2022). https://www.britannica.com/science/ hexagon. Accessed 8 Dec 2022 4. Gordon, C.C.: Adultdata: The Handbook of Adult Anthropometric and Strength Measurements. Data for Design Safety by Laura Peebles and Beverley Norris 1998, Department of Trade and Industry (URN 98/736) (1999) 5. Žiga, A., Kaˇcmarˇcik, J.: Otpornost Materijala. Univerzitet u Zenici, Mašinski fakultet (2020) 6. Farah, S., Anderson, D.G., Langer, R.: Physical and mechanical properties of PLA, and their functions in widespread applications—A comprehensive review. Adv. Drug Deliv. Rev. 107, 367–392 (2016) 7. Ferreira, R.T.L., Amatte, I.C., Dutra, T.A., Bürge, D.: Experimental characterization and micrography of 3D printed PLA and PLA reinforced with short carbon fibers. Compos. Part B: Eng. 124, 88–100 (2017) 8. Hibbeler, R.C.: Mechanics of Materials. Pearson Educación, London (2005) 9. Industry, P.: The free beginner’s guide to 3D printing (2014). https://3dprintingindustry.com/ wp-content/uploads/2014/07/3D-Printing-Guide.pdf. Accessed 11 June 2022

Multi-response Optimization of FDM Process Parameters Using Taguchi Based Grey Relational Analysis Method Kenan Muhamedagic, Ahmet Cekic, Derzija Begic-Hajdarevic(B) , and Amina Ramljak Faculty of Mechanical Engineering, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina [email protected]

Abstract. Fused deposition modelling (FDM) is the most commonly used of additive technology process for producing polymer products from simple to complex shapes. This study focuses on the FDM process parameters optimization to obtain the optimal combination parameters that achieves the maximal flexural strength and the maximal compressive strength. The experiment was conducted by FDM process for printing Polylactic Acid (PLA) parts. Data from Taguchi experimental design were analysed with Grey Relational Analysis. Layer thickness, printing temperature and raster angle are the parameters used for experimentation. It was found that a layer thickness of 0,1 mm, a raster angle of 90°and a printing temperature of 220 °C present the optimal combination of parameters by using multi-response optimization method.ANOVA was used to determine the most significant parameters at 95% confidence level. Keywords: FDM process · Polylactic Acid (PLA) · GRA · ANOVA · Flexural strength · Compressive strength

1 Introduction Additive technologies represent a group of processes used to make products of various degrees geometric complexity, by adding material “layer by layer”.In addition, the manufacturing process itself remains the same regardless of the level of complexity of the part. A 3D CAD model is used as input data, based on which a G-code is generated by slicer software, which is sent to the 3D printing device. Until now, a large number of different additive manufacturing processes have been developed, which basically differ according to the material type and the way the layers are made, that is, the physics of the process. Some of the most commonly used procedures are: stereolithography (SLA), fused deposition modelling (FDM), Ink jet modelling, selective laser sintering (SLS), etc. The FDM process isadditive technology, which is used for modelling, prototyping, but also for the production of fully functional products for engineering applications. The base material for FDM process was a thermoplastic filament. Some of © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 241–248, 2023. https://doi.org/10.1007/978-3-031-31066-9_25

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most commonly used material are: PolylActic-Acid (PLA), PolyEthylene-Terephthalate (PET), AcrylonitrileButadiene-Styrene (ABS), propylene (PP), PolyAmide (PA), and ThermoPlastic-Polyurethane (TPU) [1, 2]. For improving the FDM process performance, many authors have been engaged in the optimization of FDM process parameters with the aim of finding optimal input parametersto achieve better mechanical properties and quality of the FDM parts. Zaman et al. [3] were analysed how layer height, infill style, infill density, and contour width effects on compressive strength. In this investigation, Taguchi method based on L8 orthogonal array was used in order to create appropriate experimental design. Test samples were printed from PETG and PLA and ANOVA analysis with signal-to-noise ratio (S/N ratio) were showed that the compressive strength of test samples printed from PETG material was better than compressive strength of PLA material. Wang et al. [4] examined the effect of deposition pattern, support structure, layer height and build location on the dimensional deviations of ABS printed parts. Experimental matrix was designed according the Taguchi method. ANOVA analysis was shown that deposition style in the Z-direction has the most influential effect to dimensional deviations. Multi-criteria optimization methods can be successfully used for various engineering problems in production engineering [5], including the field of additive technologies [6, 7]. Many recent investigations were using GRA in order to improve different responses. In paper [8] was successfully applied GRA and RSM methodfor multi-criteria optimizationin order to improve FDM process cost effectiveness. For input parameters were selected part orientation, deposition style and wall thickness. Print time, model material and support material consumption were considered as output factors. Some of the researchers used multi-criteria optimization of FDM process parameters to reduce dimensional deviations and improve mechanical strength.Shakeria et al. [9] investigates the effect of four FDM process parameters: layer height, printing temperature, workspace temperature and printing speed on shape accuracy, compressive strength, elastic modulus, and deformation by GRA. Optimal parameters were determined according to the Grey Relational Grade (GRG). Verification test was shown that the GRG value had improved by 14% for experimental test conducted at optimal parameters. For many engineering applications, it is necessary to find optimal process parameters to improve several different mechanical properties simultaneously. For example, in paper [10], impact strength, flexural strength and tensile strength were selected as responses.The effect oflayer thickness, air gap, raster width, raster orientation and build orientation on analysed responses were determined by the use of Taguchi method and ANOVA. Combination of optimal process parameter were determined by the use of Grey Relational Analysis in order to optimize selected responses. In another study [11], with aim to find the optimal parameters for improving flexural strength, tensile strength and wear resistance, was investigated effect of layer height, printing speed, printing temperature and infill density, on the selected three mechanical properties. The optimal combination of parameters was determined using Grey Relational Analysis, which is obtained for layer height of 0.3 mm, printing temperature of 220°C, printing speed of 50 mm/s and infill density at 90%.

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The aim of this paper was to determine the effect and optimization of process parameters (layer thickness, printing temperature and raster angle) to improve flexural and compressive strength of FDM printed PLA parts Using Taguchi based Grey Relational Analysis method.

2 Material and Methods The test specimens were printed on a 3D printer device “UltimakerS5”. Polylactic acid (PLA) was used as the print material in this investigation. The specimens tested for flexural strength are designed in according to standard ISO 178, as presented in Fig. 1 (left), and the specimens tested for compressive strength are designed in according to standard ISO 604, as presented in Fig. 1 (right).

Fig. 1. Dimensions of specimen according to ISO 178 (left) and ISO 604 (right)

Three input parameters were selected such as the layer thickness, printing temperature and raster angle, varying at three levels. Input parameters and itslevels are presented in Table 1. Table 1. Input parameters and its levels Parameter

Unit

Symbol

Level 1

Level 2

Level 3

Thickness of Layer

mm

A

0,10

0,20

0,30

Printing temperature

°C

B

180

200

220

Raster angle

°

C

0

45

90

Other process parameter such printing speed of 60 mm/s and 100% infill, were kept constant during the experiment. Taguchi experimental design with an L9 orthogonal array was conducted to determine the optimal parameters for FDM process performance. In Table 2 are presented experimental data for 9 trials with three input parameters and two output parameters (responses). Flexural strength and compressive strength of printed specimens are considered as output parameters (process performance). A universal machine “Shimadzu AGS-X” of 10 kN was used for measuring flexure strength and compressive strength.

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K. Muhamedagic et al. Table 2. Experimental data

No

A (mm)

B (°C)

C (°)

Flexural strength, σF (MPa)

Compressive strength, σP (MPa)

1

2

3

Avg.

1

2

3

Avg.

1

0.1

180

0

38.7

38.9

38.0

38.55

45.8

44.6

45.1

45.16

2

0.1

200

45

80.8

82.0

81.7

81.56

47.8

46.7

45.7

46.78

3

0.1

220

90

92.6

92.0

92.0

92.24

49.2

46.9

48.4

48.14

4

0.2

180

45

35.9

37.1

36.5

36.53

39.6

38.8

39.9

39.45

5

0.2

200

90

79.2

80.1

80.1

79.77

45.6

45.8

44.6

45.34

6

0.2

220

0

71.6

72.5

72.5

72.24

44.3

45.0

43.8

44.37

7

0.3

180

90

29.9

30.0

29.0

29.65

38.9

40.2

40.3

39.81

8

0.3

200

0

50.6

52.2

53.4

52.10

41.8

41.4

41.7

41.63

9

0.3

220

45

70.9

72.7

73.5

72.38

40.6

41.8

41.5

41.30

3 Results and Discussion 3.1 Grey Relational Analysis GRA is a suitable multi-response optimization method for obtaining optimal process parameters. Optimization of multi-response performances can be transformedinto singleresponse performance optimization based on calculation of GRG (Grey Relational Grade. Normalisation of process responses isfirst step in this method. In this study “Larger is better” criterion is used for normalization of flexural strength and compressive strength, and it is given by Eq. (1): xi (k) =

yi (k) − minyi (k) maxyi (k) − minyi (k)

(1)

where, yi (k) is i-th experimental data for k-th process response, maximum value of yi (k) is maxyi (k), minimum value of yi (k) is minyi (k) and normalised value of yi (k) is xi (k). Difference between the highest normalised values for each response is defined with deviation sequence 0i (k). It is determined using Eq. (2): 0i (k) = |x0 (k) − xi (k)|

(2)

where, x0 (k) is highest normalised value of output.Deviation sequences and normalised values of process response is listed in Table 3. Grey relational coefficient (GRC)εi (k) is determined using Eq. (3): εi (k) = (min + ε · max )/(0i (k) + ε·max )

(3)

where, min minimum value and max maximum value of deviation sequence, and ε is grey relational constant and it was taken 0.5.

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Table 3. Normalised values and deviation sequences Normalised Values, xi (k)

Deviation Sequences, 0i (k)

σF

σP

σF

σP

1

0.142

0.657

0.858

0.343

2

0.829

0.843

0.171

0.157

3

1.000

1.000

0.000

0.000

4

0.110

0.000

0.890

1.000

5

0.801

0.678

0.199

0.322

6

0.680

0.566

0.320

0.434

7

0.000

0.041

1.000

0.959

8

0.359

0.251

0.641

0.749

9

0.683

0.213

0.317

0.787

No.

GRC used to estimate Grey Relational Grade. It is determined using Eq. (4): 1 εi (k) n n

αi =

(4)

k=1

where, n is response number. Values of GRC and GRG are depicted in table 4. Table 4. GRG with GRC No.

GRC

GRG

Rank

0.593

0.481

6

0.746

0.762

0.754

2

3

1.000

1.000

1.000

1

4

0.360

0.333

0.347

8

5

0.715

0.608

0.662

3

6

0.610

0.535

0.573

4

7

0.333

0.343

0.338

9

8

0.438

0.400

0.419

7

9

0.612

0.388

0.500

5

σF

σP

1

0.368

2

The response for mean GRG is given Table 5 and the bold value indicates level at optimal process parameters.

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From Table 5 it is clear that layer thickness has the most significant impact on process performance, followed by temperature of printing and then raster angle. So, the optimal parameters with respect to flexural strength and compressive strength are 0.10 mm layer thickness, 220°C printing temperature and 90° raster angle. Table 5. The mean GRG Parameter

max − min

Rank

0.4191

0.3257

1

0.6115

0.6910

0.3026

2

0.5334

0.6666

0.1757

3

GRG Level 1

Level 2

Level 3

Layer thickness

0.7448

0.5270

Printing temperature

0.3884

Raster angle

0.4909

Total mean GRG is 0,5636

3.2 ANOVA ANOVA was used to determine how much input parameters effect the multi-response performance significantly by using GRG value. In Table 6 is presented the ANOVA results. Based on percentage contribution (PC) and p-value, the thickness of layer is the most significant parameter, followed by the temperature of printing and raster angle. Table 6. ANOVA results for GRG Source

DF

SS

MS

F-value

p-value

PC, %

Layer thickness

2

0,165112

0,082556

57.29

0,017

45.12

Printing temperature

2

0.147587

0.073793

51.21

0.019

40.33

Raster angle

2

0.050396

0.025198

17.49

0.054

13.77

Error

2

0.002882

0.001441

Total

8

0.365976

0.79 100

4 Conclusion This study investigation the impact of input parameters on flexural strength and compressive strength of FDM manufactured PLA parts. Thickness of layer, raster angle and temperature of printing are used as input parameters in this investigation. The multiresponse optimization GRA were performed for obtaining an optimal combination of parameters that ensures maximal flexural strength and maximal compressive strength.

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The following was concluded: – Analysed input parameters have a significant effect on mechanical behaviour of PLA samples tested. – Thickness of layer has a primary impact on flexural strength and compressive strength, while raster angle has the least impact on process performance. – The optimal parameters are layer thickness of 0,10 mm, an angle of raster 90° and a printing temperature 220 °C. With these parameters, flexural strength of 92.24 MPa and the compressive strength of 48.14 MPa were obtained. – GRA method is a suitable tool for FDM process parameters optimization.

References 1. Kristiawan, R.B., Imaduddin, F., Ariawan, D., Ubaidillah, A.Z.: A review on the fused deposition modeling (FDM) 3D printing: filament processing, materials, and printing parameters. Open Eng. 11(1), 639–649 (2021).https://doi.org/10.1515/eng-2021-0063 2. Awasthi, P., Banerjee, S.S.: Fused deposition modeling of thermoplastic elastomeric materials: challenges and opportunities. Addit. Manuf. 46, 102177 (2021). https://doi.org/10.1016/j. addma.2021.102177 3. Zaman, U., Boesch, E., Siadat, A., Rivette, M., Baqai, A.A.: Impact of fused deposition modeling (FDM) process parameters on strength of built parts using Taguchi’s design of experiments. Int. J. Adv. Manuf. Technol. 101(5–8), 1215–1226 (2018). https://doi.org/10. 1007/s00170-018-3014-6 4. Chung Wang, C., Lin, T., Hu, S.: Optimizing the rapid prototyping process by integrating the Taguchi method with the Grey relational analysis. Rapid Prototyping J. 13(5), 304–315 (2007). https://doi.org/10.1108/13552540710824814 5. Muhamedagic, K., Begic-Hajdarevic, D., Cekic, A., Mehmedovic, M.: Multi-response optimization of plasma cutting parameters using grey relational analysis. In: Katalinic, B., ed. DAAAM Proceedings, DAAAM International Vienna, vol. 1., pp. 1074–1082 (2017). https:// doi.org/10.2507/28th.daaam.proceedings.149 6. Raju, R., Varma, M.M.M., Baghel, P.K.: Optimization of process parameters for 3D printing process using Taguchi based grey approach. Mater. Today: Proc. 68, 1515–1520 (2022). https://doi.org/10.1016/j.matpr.2022.07.163 7. Patil, P., Singh, D., Raykar, S.J., Bhamu, J.: Multi-objective optimization of process parameters of Fused Deposition Modeling (FDM) for printing Polylactic Acid (PLA) polymer components. Mater. Today: Proc. 45, 4880–4885 (2021). https://doi.org/10.1016/j.matpr.2021. 01.353 8. Rathee, S., Srivastava, M.: Layout optimization for FDM process by multi-objective optimization using RSM and GRA. In: Dave, H.K., Davim, J.P. (eds.) Fused Deposition Modeling Based 3D Printing. MFMT, pp. 505–515. Springer, Cham (2021). https://doi.org/10.1007/ 978-3-030-68024-4_26 9. Shakeria, Z., Benfriha, K., Zirak, N., Shirinbayan, M.: Optimization of FFF processing parameters to improve geometrical accuracy and mechanical behavior of polyamide 6 using grey relational analysis (GRA). In: Review (2021). https://doi.org/10.21203/rs.3.rs-1118150/v1 10. Liu, X., Zhang, M., Li, S., Si, L., Peng, J., Hu, Y.: Mechanical property parametric appraisal of fused deposition modeling parts based on the gray Taguchi method. Int. J. Adv. Manuf. Technol. 89(5–8), 2387–2397 (2016). https://doi.org/10.1007/s00170-016-9263-3

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11. U.S.I.C.T.: Guru Gobind Singh Indraprastha University, Delhi-110078, India, Singh M, Bharti PS, U.S.I.C.T., Guru Gobind Singh Indraprastha University, Delhi-110078, India. Grey relational analysis-based optimization of process parameters for efficient performance of fused deposition modelling based 3D printer. JER is an international, peer-reviewed journal that publishes full-length original research papers, reviews, case studies in all areas of Engineering (2022). https://doi.org/10.36909/jer.ICMET.17159

Development and Design of Air Purifier Device Prototype Vedad Saletovi´c, Adis J. Muminovi´c(B) , Isad Šari´c, and Nedim Pervan Department of Mechanical Design, Faculty of Mechanical Engineering, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina [email protected]

Abstract. Air pollution is one of the main environmental problems today. It is a problem which cannot be solved in many cities around the world. Sarajevo, as main capital of Bosnia and Herzegovina, is one of those cities. Few times during every year, Sarajevo is the most polluted city in the world, especially during winter season. Taking in consideration that air pollution cannot be solved on global level for one town or country, engineers are started to work on the devices that can improve air quality in small closed spaces like offices, schools or homes. This paper is focused on the design and development of an air purification device intended for indoor use, full development process is presented, from initial design to prototype manufacturing using additive manufacturing (3D printing). Keywords: Air pollution · air purification · design · development · device

1 Introduction Air quality is one of the biggest environmental problems today [1]. There are numerous studies about air quality monitoring [2, 3] and different filtrations technologies. New filtration technologies are developed constantly [4, 5]. Taking in consideration that air pollution cannot be solved on a global level, or even in one city, like Sarajevo in Bosnia and Hercegovina, there is growing research in the area of development of devices for air purification inside closed spaces like schools, offices and homes [6]. Today market is filled with air purification devices. These devices gain popularity in recent years because peoples become more informed about health problems related to low air quality. Through this paper full design and development process [7] of an air purification device intended for indoor use is presented, from initial design to prototype manufacturing using additive manufacturing [8]. During process of development and design of a new product there is always a goal to develop a product which properties will be better in comparison to the other products available on the market [9]. Market success is dependent on various factors (design and development time, price, shape, customer needs, etc.). Focus of product developed in this research is on its unique design and functionality. All parts of a device are designed for manufacturing using additive manufacturing (3D printing). This reduced manufacturing time to just few days. Goal of this design is to offer it to everyone who have some types of desktop 3D printers so everyone can © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 249–259, 2023. https://doi.org/10.1007/978-3-031-31066-9_26

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manufacture the device for them self. All parts except HEPA (high-efficiency particulate air) filter and electronics can be manufactured using 3D printing.

2 Definition of Device Functions and Properties After market research list of customer requirements and wishes are formulated in a form of Table 1. Table 1. Customer requirements and wishes No.

Requirements and wishes: Name and description

1.1

Main technical function:

1.1.1

Air purification

1.2

Additional technical functions

Requirement

Wish

✓ ✓

1.2.1

✓

1.2.2

Air purification of particles up to the 0.3 microns

1.2.3

Smell neutralization

✓

1.2.4

Gases neutralization

✓

1.2.5

Air purification in a space of 360 degrees

✓

1.2.6

Safety

✓

1.2.7

Ventilator speed regulation

✓

1.2.8

Power supply of 220V

✓

1.3

Design

1.3.1

Modern

✓

1.3.2

Innovative

✓

1.3.3

Universal

✓

1.3.4

Small dimensions

1.4

Ergonomic

1.4.1

Light

1.4.2

Simple positioning

✓

1.4.3

User friendly usage

✓

1.4.4

Simple filter replacement

✓

1.5

Additional properties

1.5.1

Lighting

1.5.2

Air quality sensor

✓ ✓

✓ ✓ (continued)

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Table 1. (continued) No.

Requirements and wishes: Name and description

Requirement

Wish

1.5.3

Remote control

✓

1.5.4

IoT properties

✓

1.5.5

Automatic on and off

✓

1.5.6

Filter status sensor

✓

2.1 Main Function Main function of a device is shown at Fig. 1. Electrical power is used for mechanical work of a ventilator which moves the air and creates negative pressure inside the filter.

Polluted air Air purification

Clean Air

Electrical power Fig. 1. Main function: Air purification

Air pollution particles remain trapped inside the filter and rest of the air goes out. Main function is called Air Purification. Inputs are polluted air and electrical energy. Output is clean air. Main function must be additionally divided to its partially and elementary functions. 2.2 Partial Functions Main function is divided into three partial functions shown at Fig. 2. All partial functions must be completed for proper function of a device.

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Air purification

Clean air

Electrical power

Clean air Electronics

Ventilator

Filter

Poluted air

Fig. 2. Partial functions

2.3 Elementary Functions Partial functions are divided into elementary functions. Elementary functions are starting point for all other functions. All partial function can be fulfilled using one or more elementary functions. The best solution is to use one machine or electronic element for one elementary function. In this case partial functions Ventilator and Filter have only one elementary function with the same name. They can be carried out using only one machine or electronic element. Ventilator and filter are chosen as standard elements. Partial function Electronics must be divided into two elementary functions (Fig. 3). Switch for device on and off is implemented. In addition, electrical power regulator is

Fig. 3. Elementary function “Electronics”

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used for the control of power which goes to the ventilator and on that way speed of the ventilator is controlled.

3 Concept Designs Looking to the similar devices on the market it can be noticed that all devices which uses cylindrical filter have similar design. Usually design is completely adjusted to the shape of the filter so usually device is cylindrical or four-sided prism. To develop new and innovative design, inspiration was found in the more complex geometrical shapes and fractals. In the first step concepts designs are developed. In the second step using the principle of design evolution initial concept design is evolved until final design is developed. Figure 4 shows initial concept design. Green part is the filter which is selected according to the requirements from Table 1. Design of the device must be adjusted to the shape of the filter. With the goal to make different design in comparison to the rest of the products available on the market three-sided prism was selected.

Fig. 4. Initial concept design

With the closes inspection of this design it can be noticed that this design has large part of empty space inside the device. To eliminate empty space design is changed from three-sided prism to six-sided prism (Fig. 5). This design is good but it is similar to the rest of the devices available on the market. In the third step, design from Fig. 5 is additionally upgraded to an eight-sized prism and twisted along the z axis (Fig. 6).

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Fig. 5. Six-sided prism design

Fig. 6. Final design an eight-sided prism design

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4 Detail Design For final design from Fig. 6 detail design is developed for every part. Device assembly is divided into 4 important sub-assemblies (Fig. 7): 1- housing, 2 – cap, 3 – electronics, 4 – fanhousing. Device have 47 parts in total from which 17 parts are completely unique. Housing is divided into 4 different parts to enable additive manufacturing using Ultimaker 3 additive manufacturing device. Also, design of housing is additionally upgraded using larger side openings for air intake and larger line openings at the top of the device. Larger openings enable better air flow and saves used material for manufacturing. Design of all parts of the device is adjusted to additive manufacturing principles as much as possible. One of the goals of this research was to upload all CAD models of the parts to be publically available on the internet, so everyone can download and manufacture device housing for themselves. Buying electronics, filter and fan everyone can manufacture whole device at home using any desktop additive manufacturing machine (3D printer).

Fig. 7. Sub-assemblies of a device

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Filter change can be done from the bottom of the device by simple cap removal. Device is designed to be easy to use and maintain. Future versions of the device can include air quality sensor and display for better monitoring of the efficacy of the device.

5 Prototype Manufacturing For device manufacturing two manufacturing machines was used, Ultimaker S5 and Ultimaker 3 3D printers (Fig. 8). All parts are manufactured using PLA (Polylactic acid) material. It is a great material for prototyping of functional parts.

Fig. 8. Machines used for additive manufacturing (3D printers)

Figure 9 shows examples of two manufactured parts. First one is housing for electronics and second one is housing for fan.

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Fig. 9. Examples of manufactured parts

After manufacturing of all parts device is assembled and tested (Fig. 10). All designed functionalities of the device were working properly. Device is easy to use, it can regulate fan speed and filter change is easy to do.

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Fig. 10. Manufactured fully functional prototype of the device

6 Conclusion Through this paper, complete process of product design, development and manufacturing, according to customer needs, is presented. Customer requirements, needs and whishes are collected, device functions were formulated, concept designs are developed, final design was chosen, detail design is developed, CAD models were created and prototype of the device was manufactured. It is important to notice that manufacturing of the prototype is very important in the process of product development and design. CAD models can be used for visualization and concept designs, but that is not enough for detail design of the device. Real problems with the design can be detected only after device prototype manufacturing. In future research this device can be upgraded in many ways. Sensors for air quality monitoring and device efficacy can be added to the design.

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References 1. Tang, R., et al.: Air quality and health co-benefits of China’s carbon dioxide emissions peaking before 2030. Nat. Commun. 13(1), 1–9 (2022) 2. Chaudhary, V., et al.: Emergence of MXene–polymer hybrid nanocomposites as highperformance next-generation chemiresistors for efficient air quality monitoring. Adv. Func. Mater. 32(33), 2112913 (2022) 3. Sá, J.P., Alvim-Ferraz, M.C.M., Martins, F.G., Sousa, S.I.: Application of the low-cost sensing technology for indoor air quality monitoring: a review. Environ. Technol. Innov. 102551 (2022) 4. Zhou, Y., Liu, Y., Zhang, M., Feng, Z., Yu, D.G., Wang, K.: Electrospun nanofiber membranes for air filtration: a review. Nanomaterials 12(7), 1077 (2022) 5. Munir, M.M., Adrian, M., Burhanuddin, M., Iskandar, F.: Fabrication and structure optimization of expanded polystyrene (EPS) waste fiber for high-performance air filtration. Powder Technol. 402, 117357 (2022) 6. Uhde, E., Salthammer, T., Wientzek, S., Springorum, A., Schulz, J.: Effectiveness of airpurifying devices and measures to reduce the exposure to bioaerosols in school classrooms. Indoor Air 32(8), e13087 (2022) 7. Špago, M., Muminovi´c, A.J., Pervan, N., Trobradovi´c, M., Hadžiabdi´c, V., Deli´c, M.: Development and Design of a Machine Using Standard Aluminium Profiles (2022) 8. Muminovi´c, A.J., Pandži´c, A., Pervan, N., Deli´c, M.: Razvojidizajnproizvoda u sklopuIndustrije 4.0: od brzeizradeprototipova do aditivneproizvodnje 9. Smajic, J., Muminovic, A.J., Saric, I., Muminovic, A.: Development and design of a machine for hybrid manufacturing. In: Karabegovi´c, I. (ed.) NT 2021. LNNS, vol. 233, pp. 121–134. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_15

The Influence of Technological Parameters on the Geometric Product Specification of the Parts Manufactured by the Fused Deposition Modeling Vladimir Blanuša1(B) , Dejan Movrin2 , Branko Štrbac2 , Miodrag Hadžistevi´c2 , and Miloš Ranisavljev2 1 The Higher Education Technical School of Professional Education, 21000 Novi Sad, Serbia

[email protected] 2 Faculty of Technical Sciences, 21000 Novi Sad, Serbia

Abstract. The production of functional parts by additive manufacturing is becoming an increasingly common practice in today’s manufacturing environment. The possibility of realizing simple and complex external and internal geometry of workpieces without the use of special tools and fixtures has made additive manufacturing a competitive technology on the market. Currently, there are a large number of methods that fall into the domain of additive manufacturing, and one of the most popular is Fused Deposition Modeling, or FDM. Functionality, dimensional and geometric accuracy, and surface roughness are the key quality characteristics of every manufactured product. With the workpiece obtained by the FDM method, these characteristics directly depend on the choice of technological parameters. In this paper, the effects of the filling percentage, quality, and layer thickness on the mentioned quality output characteristics were analyzed. On the workpieces, 6 dimensional and 6 geometric quality characteristics were measured, with repetitions, with subsequent measurement of surface roughness. Based on the results, obtained by analysis of variance (ANOVA), it can be concluded that the selected factors and their levels have statistical significance on the quality output characteristics. By analyzing the diagram of the main effects, a proposal of optimal levels for each of the three factors included in the study was given. Keywords: Fused Deposition Modeling · Technological parameters · Optimization

1 Introduction Additive Technologies are methods for deposing materials to form a workpiece based on a digital 3D model, usually, layer by layer. These technologies were initially used only for rapid prototyping, and with the development of technology and materials, additive manufacturing technologies have evolved to a degree that enables the production of final, functional products or final tools. With the help of Computer-Aided Models or CAD © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 260–268, 2023. https://doi.org/10.1007/978-3-031-31066-9_27

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models, engineers and designers are enabled to better comprehend the project solution without using expensive production equipment [1]. Also, with these technologies, it is possible to create very complicated workpieces, that are expensive to produce with other, more conventional methods like machining, grinding, casting, or deforming. One of the most popular 3D printing technologies is Fused Deposition Modeling (FDM). The process of obtaining workpieces using the FDM method is reduced to the deposition of melted material (most often polymer) layer by layer, to generate a complete workpiece [2]. The structure of the FDM 3D printer consists of the support structure of the printer, the extruder, the heated nozzle through which the molten material (filament) comes out, the work table, mechanical gears, and control. The operating principle of an FDM 3D printer can be explained in several steps: with the help of an extruder, the filament (material in the form of a wire) is forcibly moved towards the heated nozzle of the printer; the nozzle deposits the molten material according to the control program in the form of G-code; Motion of the executive organ of the printer is done by stepper motors; layers of material are stacked on top of each other until a complete model is obtained. Due to the specificity of the production process using this method, the low strength and stiffness of the polymer, and the mechanical characteristics of the resulting workpiece are inferior compared to traditional techniques of forming parts (injection molding, extrusion, etc.) [3]. In addition to mechanical characteristics, geometric product specifications such as dimensional accuracy, shape and form errors, and surface roughness represent an important aspect of the quality of workpieces obtained by the FDM method. The geometric accuracy of workpieces is defined as the closeness of agreement between the dimensions of the real workpiece and its specification. Conformity with the specification is verified against the corresponding standards [4]. The geometric accuracy of parts obtained by the FDM method, using PLA material, is affected by several parameters, namely: orientation of the print, thickness of the print layer, speed of movement of the print head, speed of material flow through the nozzle, the thickness of the model walls, etc. [5]. Research in the literature has shown that the thickness of the print layer, i.e. the resolution, has a significant influence on the geometric accuracy of the manufactured parts, which is confirmed in [6], on the example of printing composite materials. The roughness of the workpieces is an important feature that defines the functionality, therefore it is vital to reduce the roughness of the resulting components.

2 ZORTRAX M200 Plus – 3D Printer The 3D model was printed on a Zortrax M200 PLUS 3D printer. The working volume of the printer is 200 × 200 × 180 mm. The design of this printer is “XY Core”, which means that it has a relatively rigid supporting structure. The assembly of parts allows the nozzle to move in the XY plane while the work table moves vertically in the direction of the Z axis. The printer has a closed support structure that allows it to print materials that require a heated atmosphere in the print zone, not just a heated work table. The diameter of the nozzle used for printing is 0.4 mm and the diameter of the filament is 1.75 mm.

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Preparation for printing, as well as the setting of all necessary parameters, is done using the “Z-SUITE” software package. The software package is developed for “Zortrax” printers and can process “.stl”, “.obj” or “.dxf” files created in specialized or universal modeling software packages. The first necessary step within the program package, is to choose the appropriate type of printer, and after that, the finished geometry is downloaded in the form of a 3D model, and then its positioning is performed on the table (platform) for printing and scale adjustment. After that, the analysis of the wall thickness of the model is performed in the software package. The most important is the next stage of setting up the preparation for printing because it is in this stage that all technological parameters of 3D printing are set within the “Print settings” window. Some of the parameters that can be adjusted are material type, nozzle diameter, print layer thickness, print quality (low, medium, or high), print type, print density, etc.

3 Definition of Technological Parameters The influence of technological parameters on the accuracy and surface quality of parts obtained by 3D printing was performed for the specific model shown in Fig. 1.

Fig. 1. Geometrical product specification for the workpiece used in the study

The workpieces obtained by the FTD technology have an engineering application and this represents a very significant characteristic of these types of printers in exploitation. For the parts to have an engineering application, it is necessary to provide the appropriate technical parameters with which the parts will be printed with certain geometric accuracy and surface quality. 3D printing strategies and technological parameters have a significant impact on the geometric accuracy, manufacturability, and surface quality of 3D printed parts. The software package for preparing 3D printing can define 3 qualities of the printed surface, namely:

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• Draft, • Normal, • High. These three qualities directly depend on the printing speed (productivity), whereby with the setting on the Draft, the highest printing speed (shortest printing time) is obtained or the highest productivity but also a worse surface quality. With the settings on High. The highest surface quality is obtained but a longer printing time is required. In addition to these three qualities of the surface, the thickness of the printing layer is a critical parameter of the quality of the print. In the software system itself, it is possible to define the following dimensions of the thickness of the print layer: • • • • •

0,09 mm, 0,14 mm, 0,19 mm, 0,29 mm, 0,39 mm,

With the application of a smaller value of layer thickness, a higher quality of the printed surface is obtained, while with a larger layer thickness, a lower quality of the printed surface is obtained. Workpieces obtained by the FDM printing method, which were printed with different technological parameters, are shown in Fig. 2.

Fig. 2. Workpieces obtained by the FDM printing method

One of the technological parameters that have a significant impact on the accuracy and quality of printing is certainly printing speed. The results of the influence of the printing speed on the productivity and surface quality of the parts are shown in Table 1. In addition to the previous ones, very important technological parameters on the geometric accuracy and surface roughness of parts obtained by 3D printing are the layer thickness and the print density. Of course, with a greater layer thickness, the productivity of the printer itself is higher, but the surface quality and geometric accuracy are significantly diminished. Table 2 shows the influence of the layer thickness and the print density on the surface quality of the manufactured parts (Table 3 and Table 4).

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Table 1. Influence of printing time on print quality and productivity for a layer thickness of 0.09 mm Quality

Density of the workpiece in %

Layer thickness in mm

Printing time in min

Mass in g

Draft

50

0,09

84

34

Normal

50

0,09

176

35

High

50

0,09

211

35

Table 2. Influence of print speed and density on print quality and productivity for a layer thickness of 0.39 mm Quality

Density of the workpiece in %

Layer thickness in mm

Printing time in min

Mass in g

Draft

10

0,39

61

28

Normal

10

0,39

86

29

Draft

50

0,39

68

34

Normal

50

0,39

95

35

Draft

100

0,39

106

40

Normal

100

0,39

147

40

Table 3. Analysis of Variance for “Roundness of the cylinder with the diameter 8” Analysis of Variance - ANOVA Source:

DF

Adj SS

Adj MS

Infill [%]

2

0.018338

0.009169

Quality

2

0.006627

Layer thickness

1

0.080372

Error

3

0.000758

0.000253

Total

8

0.133944

F-Value

P- Value

36.28

0.008

0.003313

13.11

0.033

0.080372

318.03

0.000

Table 4. Analysis of Variance for “Diameter 26” Analysis of Variance - ANOVA Source:

DF

Adj SS

Adj MS

Infill [%]

2

0.003058

0.001529

F-statistika

Quality

2

0.000636

0.000318

0.65

0.583

Layer thickness

1

0.044184

0.044184

90.18

0.002

Error

3

0.001470

0.000490

Total

8

0.067445

3.12

P-vrednost 0.185

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4 Results and Discussion The surfaces of the workpieces obtained by the FDM method are in most cases, imperfect. That depends on previously defined technological parameters. Surface irregularities of functionally applicable parts can affect wear, stress concentrations, or failure of the part itself. The roughness of the surface is characterized by micro geometric irregularities and is displayed in the form of an effective profile. The size of the roughness itself will be defined depending on the roughness parameters, namely: the largest height of bumps Rmax , the mean arithmetic deviation Ra and the mean height of bumps Rz . Figure 4 shows the roughness diagram for the case of a print layer thickness of 0.39 mm and a print density of 50% (Fig. 3)

Roughness in μm

Total height of the assessed profile Rmax

Arithmetical mean deviation of the assessed profile - Ra

Maximum height of the assessed profile - Rz

146

28.420

127

.

Fig. 3. The layout of the roughness diagram for the case of a print layer thickness of 0.39 mm and a print density of 50%

Figure 5 shows the roughness diagram for the case of a print layer thickness of 0.09 mm and a print density of 50%.

Roughness in μm

Total height of the assessed profile Rmax

Arithmetical mean deviation of the assessed profile - Ra

Maximum height of the assessed profile - Rz

49.1

6.924

39.7

The roughness parameters show that the maximum height of unevenness Rmax is about three times smaller when the thickness of the print layer is reduced from 0.39 mm to 0.09 mm, while the mean arithmetic deviation is four times smaller for the thickness of the print layer 0.09 mm and that the mean the height of unevenness decreased by 3.2 times for the thickness of the print layer of 0.09 mm.

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Fig. 4. The layout of the roughness diagram for the case of a print layer thickness of 0.09 mm and a print density of 50%

The analysis of dimensional and geometric quality characteristics was performed on a Carl Zeiss Contura G2 coordinate measuring machine, with a rotating RDS head and a passive Vast XXT sensor. The maximum permissible error when measuring the distance between two points in space is defined as MPE E = (1.9 + L/330), where L is expressed in mm, and the value of MPE E is obtained in micrometers. The diameter of the measuring probe used to measure all considered characteristics on the workpieces was 3 mm. The measurement was performed with three repetitions and the mean values of the results were analyzed. The statistical analysis of the obtained results was performed in the Minitab 17 software package. To determine the statistical significance of the observed factors, i.e. percentage of filling, quality, and layer thickness, an analysis of variance (ANOVA) was performed for each of the 12 observed quality characteristics. Before analyzing variance, the Anderson-Darling normality test was conducted and it was determined that for all characteristics, the data corresponds to the data taken from a normal distribution with a significance threshold of α = 0.05. For five characteristics, statistical significance was determined by “fitting” a general linear model. These are the Cylindricity and Diameter of the cylinder 26 and the Roundness of all three Cylinders 8. Due to limited space, the ANOVA table and main-effects plot will be shown only for two significant characteristics of the workpiece. Based on the analysis of variance, it can be determined that for the roundness of the observed cylinder, all three parameters included in the study have a statistically significant influence, because the p-value is less than the significance threshold α = 0.05. For the diameter 26, the only significant factor, based on the p-value, is the layer thickness. The adequacy of the model (R-sq) for both characteristics is adequate, namely, for Roundness 8 and Diameter 26, it is 99.43% and 97.82%, respectively. In Fig. 5, diagrams of the main influences are given. From Fig 5, it can be concluded that the layer thickness factor has the greatest influence, followed by the factor related to Quality (Draft, Normal, High), and the infill factor is the least influential. Based on the analysis of the numerical and graphical results of the study, the optimal levels for each of the observed factors can be reached. Namely, for Roundness, we would choose the following factor levels: Infill –50%, Quality - High, and Layer Thickness –0.09. Analogously, for a Diameter whose nominal measurement is 26 mm, we would choose the following factor levels: Infill - 50%, Quality - High, and Layer Thickness - 0.09. Thus, in this case, the same factor levels were found to be optimal for two different quality characteristics.

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5 Conclusion The choice of technological parameters during the production of functional parts using the FDM printing method has a decisive influence on the output quality characteristics. Finding the optimal set of technological parameters, even today, is a current issue, especially due to the availability of new types of materials (composite materials), the improvement of existing technical solutions (printing methods and their components), and the development of new ones. The analysis of technological parameters was related to the selection of the optimal levels of the three observed factors, percentage of filling, quality, and layer thickness, by “fitting” the general linear model within the analysis of variance ( ANOVA). The optimization of the parameters was carried out concerning the macro and micro geometric specifications of the product. On certain quality characteristics, the analysis showed statistical significance for all three observed factors. Employing the main effects plot, the optimal levels were determined for the observed factor. When manufacturing workpieces, the “Quality” factor could be considered a “black box” because the “Z-Suite” specialized software does not allow insight into data such as print speed, filament flow speed, etc. The direction of future research would be to use different software packages to create the G-code for the same workpiece. One of the software should be open-source, such as “Ultimaker Cura”, so that the “hidden options” can be controlled.

Fig. 5. Main-effects plot for the quality output characteristics of the workpiece

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References 1. Nagendra, J., Srinath, M.K., Sujeeth, S., Naresh, K.S., Ganesha Prasad, M.S.: Optimization of process parameters and evaluation of surface roughness for 3D printed nylon-aramid composite. Mater. Today Proc. 44, 674–682 (2021) 2. Chen, K., Yu, L., Cui, Y., Jia, M., Pan, K.: Optimization of printing parameters of 3D-printed continuous glass fiber reinforced polylactic acid composites. Thin- Walled Struct. 164, 107717 (2021) 3. Ranisavljev, M., Blanuša, V., Movrin, D., Štrbac, B., Matin, I., Hadžistevi´c, M.: Analysis of geometric product specifications obtained by different 3D printing strategies. J. Mechatron. Autom. Indentification Technol. 7, 13–17 (2022) 4. Radlovaˇcki, V., Hadžistevi´c, M., Štrbac, B., Deli´c, M., Kamberovi´c, B.: Evaluating minimum zone flatness error using new method—Bundle of plains through one point. Precis. Eng. 43, 554–562 (2016) 5. Hanon, M.M., Zsidai, L., Ma, Q.: Accuracy investigation of 3D printed PLA with various process parameters and different colors. Mater. Today Proc. 42, 3089–3096 (2021) 6. Ayrilmis, N., Kariz, M., Kwon, J.H., Kitek Kuzman, M.: Effect of printing layer thickness on water absorption and mechanical properties of 3D-printed wood/PLA composite materials. Int. J. Adv. Manufact. Technol. 102(5–8), 2195–2200 (2019). https://doi.org/10.1007/s00170019-03299-9

Dimensional and Positional Control of Industrial Workpiece Using CMM and Optical 3D Scanner Kenan Varda1,2(B) , Almira Softi´c2 , Nermina Zaimovi´c-Uzunovi´c3 , and Sabina Serdarevi´c-Kadi´c3 1 Automation and Metrology Department, University of Zenica, 72000 Zenica,

Bosnia and Herzegovina [email protected] 2 Faculty of Mechanical Engineering, University of Zenica, 72000 Zenica, Bosnia and Herzegovina 3 Faculty of Mechanical Engineering, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina

Abstract. In the process of dimensional and positional control of workpieces of large series, it is necessary to establish fast and reliable product quality control. Using modern and automated complex measuring systems, it is possible to create such systems. In the request of the economy, it is important to find a balance between saving time, money and the quality of the control process. This paper presents an example of dimensional and positional control of a machine workpiece, using a coordinate measuring machine Carl Zeiss Contura G2 and an optical 3D scanner RangeVision PRO. In the first phase, the calibration of the measuring machine was done by an accredited laboratory for length, in accordance with standard 10360, paragraph 2. Using the manual mode of operation, the VAST XT probe detected and roughly determined the surfaces of interest on the work piece. Automatic strategies for CNC measurement were created, creating parameters so that the maximum number of points is obtained in the optimal operating mode. The obtained measurement results on the CMM were compared with the results obtained by 3D scanning. Bearing in mind certain disadvantages of optical complex measuring systems, in this particular case the color of the piece made the scanning process difficult, so it was necessary to apply a layer of powder of small granulation in order to obtain optimal results. Detecting all aspects that participates in the measurement uncertainty in this scanning process, a 3D model is created and virtually measured in the GOM Inspect software. The compared results are shown. Keywords: CMM · 3D scanning · metrology · measurement · GOM · Rangevision · control

1 Introduction In the quality control of machine parts and metal pieces, where there are no strict requirements for the quality of the surface finish and where there are no strict permitted deviations from the nominal dimensions and positions, it is increasingly decided to use a © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 269–275, 2023. https://doi.org/10.1007/978-3-031-31066-9_28

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control system that includes optical and laser measuring devices. For one such metal piece, a dimension and position control strategy was created using a calibrated Coordinate measuring machine at an accredited length laboratory, as well as a dimension and position control strategy on a scanned 3D model using an optical measuring device. Bearing in mind that no information was available on the allowed deviations and tolerances of the workpiece, this work serves as a basis for creating a quick strategy for controlling the dimensions and positions of the piece using an optical scanner that shows the differences of the results obtained using a calibrated CMM device and an optical 3D scanner. With both approaches, it is not necessary to create a virtual 3D CAD model, as it is possible to measure with probes on a CMM and scan on a 3D scanner in manual mode and obtain results. It is important to emphasize that both approaches have their advantages and disadvantages. Using the Coordinate measuring machine, the procedure for controlling dimensions and positions is undoubtedly more accurate and precise, bearing in mind that this procedure and measuring device is still irreplaceable in metrology for pieces of simple and complex geometry. On the other hand, this procedure is time-consuming and the CMM is a device that is very expensive, and it is important to make an assessment and balance whether there is a need to use a CMM for pieces with less demanding parameters in product quality control. On the other hand, the 3D optical scanner is a device that is easy to use and the scanning process is very fast. It is the operator’s assessment how long the process should be in order to obtain a sufficient amount of data for a quality product quality control report. The disadvantage of such a device is that the scanning process is affected by two key parameters, namely the color and material of the piece. Dark pieces and materials that have a high reflection are very difficult to scan and it is necessary to apply a small layer of fine-grained powder in order to reduce the influence of these two parameters, but this procedure introduces additional error and affects the measurement uncertainty budget.

2 3D CAD Model Creating and Nominal Drawing Dimensions Based on the nominal dimensions and positions of the workpiece and the technical drawing, a 3D CAD model of the piece was created, which was used in the process of virtual control and comparison of the scanned and 3D CAD models. Based on the requirements for quality control of the workpiece, a list of parameters of interest was created, whose dimensions and positions were examined using two different methods (Fig. 1). Taking into account the advantages and disadvantages of both procedures, the most optimal number of characteristic parameters for control and measurement was determined. 10 characteristic surfaces and 2 diameters were selected. In the measurement and control procedure, parameters of flatness and parallelism deviations of surfaces, as well as deviations of length measurements, radius and angles were controlled (Fig. 2).

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Fig. 1. Technical drawing and 3D CAD model of workpiece

Fig. 2. Parameters of interest

The parameters are marked with the letter “P” and a numerical value, so that it is easier to establish a relationship between the desired parameters in the control report.

3 3D Scanning Procedure and Virtual Metrology In the 3D scanning process, a RangeVision PRO optical scanner was used, which is equipped with three sets of lenses for three different size ranges of the workpieces to be scanned. As part of this measuring system, there is also a rotary table that is predefined by software, so that the workpieces that are positioned on the table of the 3D scanner automatically receive data about their position in space in relation to the 3D scanner. Scanning using a rotary table greatly facilitates the post-processing procedure, where it is necessary to combine a group of scans and a 3D model suitable for the virtual metrology procedure. With the workpiece that was scanned for the purpose of writing this paper, it was necessary to remove the negative phenomenon of high light reflection from the surface of the workpiece, as well as the dark color of the workpiece. A matte spray of white color and fine granulation was used, in order to apply a layer of white paint that would enable better quality images obtained by 3D scanning (Fig. 3).

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Fig. 3. 3D scanned model

On the created 3D scanned model, dimensions and positions were checked using virtual metrology techniques. In the GOM Inspect software, which is the gold standard in the process of virtual control and measurement, the deviation from flatness and parallelism, as well as the deviation of dimensions, diameters and angles, were examined. It is important to emphasize that in the process of controlling both dimensions and positions, new, ideal surfaces were created in the GOM Inspect software that approximate the cloud of points obtained by the 3D scanning process. All surfaces were obtained using the Gaussian method. Using the “Fitting element” tool, which uses this approximation method, surfaces and elements of interest are created (Fig. 4).

Fig. 4. Virtual measurement procedure

4 CMM Measuring Procedure In the process of measuring a workpiece on a CMM, the first step is to create a device for measuring the piece and provide positioning so that the workpiece elements of interest can be easily and undisturbedly measured. For the positioning workpiece, electromagnets where used. Bearing in mind that CMM measurement is a tactile method, it is important

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to choose the appropriate stylus for measurement. The CMM Carl Zeiss Contura G2 that was used to measure the workpiece uses a VAST XT stylus and a vertical stylus with a probe radius of 1.5 mm was selected.Using the selected stylus, the positions of the elements of interest are determined in space. After they were roughly defined, automatic measurement strategies were created (Fig. 5).

Fig. 5. Automatic strategies creation in software Calypso

Each of the surfaces, as well as the cylinders whose diameters were controlled, were measured using the automatic “Grid” and “Helix” strategies. The measurement was performed at a speed of 15 mm per second, and approximately 500 points in space were collected on each of the desired elements. After the measurement is carried out, reports were created using software Calypso.

5 Results After both procedures of measurement and control of the workpiece were carried out, reports were created for virtual and tactile measurement. In both cases, flatness for 9 surfaces, parallelism between 5 pairs of surfaces, distance between 5 pairs of surfaces, diameter for 2 cylinders and angle between 2 pairs of surfaces were controlled. Results are presented in Table 1. Table 1. Results 3D scanner RangeVision PRO

CMM Carl Zeiss Contura G2

Parameter

Nominal value

Result

Result

Flatness P1

0 mm

0,22 mm

0,03875 mm

Flatness P2

0 mm

0,19 mm

0,02686 mm

Flatness P3

0 mm

0,32 mm

0,05097 mm

Flatness P4

0 mm

0,13 mm

0,04716 mm

Flatness P5

0 mm

0,21 mm

0,08597 mm (continued)

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CMM Carl Zeiss Contura G2

Flatness P6

0 mm

0,15 mm

0,04733 mm

Flatness P7

0 mm

0,23 mm

0,02805 mm

Flatness P8

0 mm

0,29 mm

0,03799 mm

Flatness P9

0 mm

0,21 mm

0,04941 mm

Length P1, P5

125 mm

125,07 mm

124,82308 mm

Length P3, P7

40 mm

40,19 mm

40,29054 mm

Length P3, P9

12,5 mm

12,89 mm

12,70163 mm

Length P8, P9

15 mm

14,56 mm

15,30390 mm

Length P7, P8

12,5 mm

12,79 mm

12,49278 mm

Parallelism P2, P5

0 mm

0,24 mm

0,09409 mm

Parallelism P3, P7

0 mm

0,31 mm

0,07506 mm

Parallelism P8, P9

0 mm

0,23 mm

0,06983 mm

Parallelism P3, P9

0 mm

0,35 mm

0,17959 mm

Parallelism P7, P8

0 mm

0,21 mm

0,12760 mm

Diameter R1

15 mm

14,83 mm

15,06357 mm

Diameter R2

15 mm

14,94 mm

15,20271 mm

Angle P3,P4

150 deg

149,74 deg

149,75817 deg

Angle P6,P7

150 deg

149,79 deg

149,76666 deg

6 Conclusion By processing the measurement results, it can be concluded that the largest number of deviations in dimensions and positions ranges from −0.2 mm to + 0.2 mm, which is a very good control result for workpieces with less strict tolerances. It is important to emphasize that the control of dimensions and positions was carried out on the workpiece with the largest length dimension of 125 mm, so 3D scanning was performed on the first set of lenses for pieces up to a maximum of 150 mm in the largest dimension. Also, it can be concluded that the smallest deviation obtained by scanning and tactile measurement is obtained for deviation from parallelism for surfaces P7 and P8 and it is 0,0824 mm. The largest deviation of the two measured values was obtained for the length deviation for surfaces P8 and P9 and it is 0,7439 mm. It is important to emphasize that when controlling the deviation from the angles, approximate results were obtained and the minimum deviation is 0.01 deg. These results will serve as a basis for further research that will include a larger number of samples and reproducibility of measurements.

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References 1. Zaimovi´c-Uzunovi´c, N.: Ispitivanjegeometrijskihkarakteristikaproizvoda, Institut za privredniinženjering-IPI, Zenica (2019) 2. Jenoptik.: Geometrical tolerancing in practice, Industrial Metrology Germany(2015) 3. Gajski, A.: Izrada plana dimenzionalnekontrolekonzole, Sveuˇcilište u Karlovcu, Karlovac (2017) 4. Eto, Confalone, G., Ellis, B., Belding, J.: 3D Scanning: Metrology for Advanced Manufacturing. Wiley (2023) 5. Mucko, T.: Primjenastatistiˇckihtolerancijanastrojarskimpozicijama, SveuˇcilišteSjever, Varaždin (2015) 6. Sladek, J.A.: Coordinate Metrology Accuracy of Systems and Measurements, Springer (2016)

3D Printed Toys for Children with Disabilities – Study Case in Montenegro Mihailo Jovanovic1 , Milena Djukanovic2(B) , Anita Maric3 , and Andrea Medin4 1 Faculty of Management Herceg Novi, Adriatik University, Herceg Novi, Montenegro 2 Faculty of Electrical Engineering, University of Montenegro, 81000 Podgorica, Montenegro

[email protected]

3 Government of Montenegro, Bureau for Education Services, 81000 Podgorica, Montenegro 4 Faculty of Mechanical Engineering, University of Montenegro, 81000 Podgorica, Montenegro

Abstract. Around 15% of the population has some kind of disability, of which 240 million are children. They are a part of every community, and the way society approaches and embraces them defines children’s ability to participate and develop. Toys have a huge impact on children’s cognitive development, senses, and creativity, as well as teaching them about themselves and their surroundings. Actually, kids build skills naturally through play. 3D printing as a fast-growing technology has also found its use in education, and it is especially beneficial for printing toys for children with disabilities because the materials used are recyclable and eco-friendly and can be created in accordance with their needs. Keywords: 3D printing · children · education · toys · software · PLA filaments · Montenegro

1 Introduction When we talk about 3D printing, we think it is a relatively new technology, but it was first mentioned as an idea in 1945 and put to practical use in 1971. Since then, 3D technology has developed and been inserted into every aspect of our lives; it is used by common people as well as companies, and it is used in many branches, including construction, manufacturing, design, engineering, medicine, education, etc. The idea was first mentioned in a story; the concept of making objects from uploaded drawings where the material comes out of the drawing arm and then becomes hard was considered just science fiction but soon proved to be very real and practical [1]. In the 60s Teletype Corporation started using a method of pulling a drop of material from the nozzle using electronics [2]. A device that was used had the capacity for printing up to 120 characters/s. They started using melted wax by following the example of Johannes Gottwald, who made objects from liquefied metal that harden into a shape, predetermined by a device [2]. In the years that followed 3D printing had some trouble getting the attention it deserved. First, in 1980 research was published describing the 3D printing method that used special plastic instead of metal. Two years later and in 1984 few patterns were filed regarding 3D printing and the CAM process, but like its predecessors’ work and the research was © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 276–282, 2023. https://doi.org/10.1007/978-3-031-31066-9_29

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casted-off because of a lack of appeal and interest. After a rough start, the years that came were full of progress andthe first 3D printer was built. The first stereolithographic device (SLA) was manufactured in 1987 and used for making complex parts [3]. At that time materials science was not developed as it is now, machines were expensive, and they were placed only in manufacturing plants. As the industries developed 3D printing was integrated pretty much into each one of them, such as in bioengineering, a urinary bladder, a miniature kidney and blood vessels [4]. From there, 3D printing was used more and more in every aspect of our lives, and as its use increased, it could easily replace traditional CNC manufacturing. Its advantages include faster and less expensive model production, as well as the fact that the materials used in 3D printing are diverse, safer, and more environmentally friendly. We cannot fail to mention its use during the COVID pandemic, printing medical equipment [5, 6]. After that, 3D printing can be used for more enjoyable purposes such as education and entertainment. And in the years ahead, 3D printing has a bright future. Construction plays a significant role in a constantly evolving world, and as we strive to reduce pollution and gas emissions, new technologies enter the picture. As we have seen in the past years, during the pandemic 3D printing was very useful, even crucial in medicine, because of the shortage of commercial goods and medical appliances. Especially in medicine, 3D printing has yet to show its full potential. Regarding the combination of medicine and education 3D printing can be used to print educational equipment such as toys for children [7]. Because when dealing with someone in need, we must submit tools that are appropriate for the problem at hand. In that sense, 3D printing is suitable because we can print whatever we imagine and need. 3D printing is used in education to stimulate students’ imagination and construction creativity; they can bring any idea to life by creating a 3D model of anything they learn about, such as geography, language, art, biology, and so on [8]. The toys that we printed were made to represent the cultural heritage of Montenegro.

2 Toys as Means of Teaching in Inclusive Education Inclusion reflects the system of values of society and portrays the way it enforces and manifests its principles, criteria, points of view, attitudes toward life, reality, and human rights. The philosophy of inclusion is based on the belief that all people have the same rights and opportunities, regardless of individual differences. In an inclusive society, every person is respected and recognized as a human being. Inclusion, primarily, conveys ensuring equal opportunities for everyone as well as maximum flexibility in fulfilling specific educational and wider social rights and needs (Fig. 1). Kindergarten teachers, schoolteachers, kindergartens, and schools adjust working strategies so that they meet children’s needs. Inclusive education is based on altering the curriculum, content, approach, and teaching practices. It is carried out in a flexible way in accordance with the structure and strategies of the education system. With inclusive education, equal chances are fulfilled, enabling choice in accordance with individual rights, and the teaching process is conducted without discrimination. Instead of focusing on a child’s shortcomings or damages, the emphasis is on what he can and is capable of doing his strengths and potentials. There are several categories of disabilities [9]:

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Fig. 1. Inclusion ensures equal opportunities for everyone

a. Children with disabilities in physical development - Space becomes more accessible and manageable through inclusive education, which improves self-image. The emphasis is on capability rather than the external interface. The alternative expression and material adjustments are highlighted. As a field in which teachers’ need for support was perceived, there were class organization, adjustment, and accessibility issues at work. b. Children with intellectual disabilities- Through inclusive education, they acquire the basis for an independent social life since they are acquiring the knowledge and skills necessary for everyday life. The child’s learning curve is continuously monitored. Fields of interest are expanding and becoming lasting and deeper. They learn directly from the surroundings and from their experience. c. Children with auditory disabilities- Through peer interaction articulation is made more clear. As a means of primary technical adaptation, the following are offered: usage of computers; enabling the child to sit in the first row or central position (1–1.5 m from the speaker) in order to see the lecturer’s lips move. d. Children with autism- Dwelling in structured environments that provide inclusive education enables the autistic child to: improve his or her understanding of reality, both for himself and others; be calm (organized surroundings reduce anxiety); learn better (visual signs help focus on important information); acquire self-sufficiency; and manage his or her behavior. Peer communication models help to improve social contact and communication. One of the ways of respecting the principle of accessibility and equal opportunities for everyone in accessing information, education, socializing, labor, and free time is the application of assistive technologies. Assistive technologies facilitate and promote regular educational, everyday, and professional functioning. Assistive technology is a collective term that includes assistive, adaptive, and rehabilitating means. It relates to any

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product, a piece of equipment, or a system, no matter whether it is used in its original form, modified, or adjusted, that is used to increase, sustain, or improve functional abilities with disabilities. It is a set of instruments, means, and devices that children with disabilities use to do tasks that they could not otherwise accomplish. Instruments can range from simple peg grip holders to expensive equipment such as computers and can be industrial or homemade [10]. Assistive technology is available for persons with physical disabilities, visual impairment (blindness and partial visual loss), auditory impairment (voice, speech, and language), and difficulties in communication and studying. Broadly considered, those can be: communicational, software, educational, ergonomic, auditory, orthopedic, reading aids, everyday life (dressing, diet, bathing…), surroundings control, transport (wheelchairs, electronic, ambulant aids…), physical activities, sitting and standing, consultative services, and consulting about choice.

3 Process of 3D Modeling of Toys Modeling and designing were first done on paper with 2D sketching and further with 3D modeling of the components. Software for 3D modeling gives us a better insight intothe dimension, position of the components, their relation and so on. With this software we can also analyze the mechanical and electrical parameters of the model. The most used software are CAD programs, SolidWorks, Onshape, Blender, MeshLab, Creo and many more [11]. For 3D modeling of toys for children with disabilities, Solid Works has been used. Other programs work on the same idea using a different interface and adding special tool kits. Some programs such as SolidWorks have integrated parts, that eased constructors’ jobs. There are gears, nuts, small parts made by ISO, DIM and other standards. Since the toys will be used in Montenegro’s elementary schools, approved by the Government of Montenegro, Bureau for Education Services, the idea was to implement stories from Monetengro and its cultural heritage (Fig. 2). Two toys represent puzzles with cyrilic and

Fig. 2. Layout of toys’ 3D models

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latin letters in different colors. Another toy is a puzzle representation of the Montenegrin map. And another one represents plants that grow in Montenegro with names associated with them.

4 3D Printing Process and Materials As we face some of the 21st century’s problems, new materials are being discovered and developed to help solve them, such as waste problems, pollution, and negative impacts on people and nature. Every manufacturing process uses a different type of material, and in 3D printing, plastic is still the most commonly used material, but as this method of production is more widely used, the variety of materials grows. Materials that are usually used are metal and carbon fiber, but PLA materials have proven themselves more eco-friendly and as good as regular materials. Just to give you an idea of how big the market is for 3D printing with plastic, it is estimated to reach 2.83 billion dollars by the year 2027. Two types of plastic are used in this process: acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA). ABS is cheaper to use and good when flexibility and strength are needed, for example in some car parts. On the other hand, PLA is biodegradable plastic, which makes it attractive for use. It can be made from cornstarch and plastic; its low melting temperature is one of its benefits, making it easy to use anywhere. Because of its traits, it is very easy to work with this material: flexibility with temperature, no odor while printing, etc. This material is good for beginners and people who have just been introduced to 3D printing. When wanting to produce a part with details, PLA is best to use because it reproduces details best and is good to use when aesthetics is required. PLA materials can be different colors as the materials easily change pigments. The strength of PLA materials is sufficient for light models. As said before, PLA is suitable for use because it exists in symbiosis with the environment. PLA is a biodegradable material; not at room temperature, but under certain conditions, if necessary, PLA parts can decompose [12]. For 3D printed toys that we designed, PLA materials were used in different and vibrant colors (Fig. 3). There are many different types of 3D printers, especially in modern times, but the leading roles go to stereolithography (SLA), selective laser sintering (SLS), and fused deposition modeling (FDM)-based printers. SLA was first used in the 1980s and is the type of technology used for 3D printing. It uses a laser to turn liquid into hardened plastic. This type of production is beneficial for concept modeling and short-run production. Its benefits are high accuracy, and its final product has fine features. SLS uses lasers with high power to turn powder into a hard surface. This type has advantages when it comes to complex geometries. Leading roles go to stereolithography (SLA), selective laser sintering (SLS), and fused deposition modeling (FDM)-based printers. SLA was first used in the 1980s and is the type of technology used for 3D printing. It uses a laser to turn liquid into hardened plastic. This type of production is beneficial for concept modeling and short-run production. Its benefits are high accuracy, and its final product has fine features. SLS uses lasers with high power to turn powder into a hard surface. This type has advantages when it comes to complex geometries. FDM, also known as FFF (fused filament fabrication), is the most common type. It turns plastic, such as PLA,

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Fig. 3. 3D printed toys for children with disablities

layer by layer into the object we desire. This technique is used for basic concept models and simple prototyping [13]. For printing toys, we used Craftbot XL, which showed advanced functions and made the whole process much easier. The printer is easy to use and gives high-quality products, such as toys that were printed.

5 Conclusion The main goal of inclusive education is the inclusion of children with disabilities. This process involves special teaching methods as well as inclusive technologies and means that address the different needs of children. One of the challenges is creating educational toys fit for children with disabilities. In this paper we have shown the process of creating 3D printed toys using recyclable and biodegradable filaments in different colors. These toys are based cultural heritage of Montenegro helping this way elementary school children with disabilities learn more about history, nature, and many other authentic values of their homeland in a creative and interesting way.

References 1. Design, Education Department at the Museum of Arts and3D printing timeline. https://mad museum.org/sites/default/files/static/ed/3D%20Printed%20Timeline%20Resource.pdf 2. History of 3D Printing. https://redshift.autodesk.com/articles/history-of-3d-printing 3. History of 3D Printing: from 1980 - until today. https://hellenic-cam.gr/en/history/

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4. 10 Exciting Applications Of 3D Printing That Could Revolutionize Industry And Society. https://www.forbes.com/sites/forbestechcouncil/2021/10/04/10-exciting-applications-of-3dprinting-that-could-revolutionize-industry-and-society/ 5. Ðukanovi´c, M., Mavri´c, A., Jovanovi´c, J., Roganovi´c, M., Boškovi´c, V.: Design of 3D printing thermo-sensored medical gear in detecting COVID-19 symptoms. MDPI Appl. Sci. 10, 10–11 (2020)https://doi.org/10.3390/app11010419 6. Djukanovic, M., Jovanovic, M., Pejovic, N., Lutovac, D.: 3D printing solutions in the fight against covid-19 pandemic. In: Karabegovi´c, I. (ed.) NT 2021. LNNS, vol. 233, pp. 310–322. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_35 7. Prakash, M., Buchi Bhanu, S.l.: 3D printing and its applications. Int. J. Sci. Res. (2016) 8. Making toys with 3D printers. https://www.make.toys/ 9. Mili´c, T., Mari´c, A.: Pruruˇcnik za rad s djecom s autizmom. Podgorica : Zavod za udžbenike i nastavna sredstva (2015). ISBN: 978–86–303–1882–5 10. Lazor, M., Isakov, M., Ivkovi´c, N.: Asistivna tehnologija u školi. Novi Sad : Škola za osnovno i srednje obrazovanje Milan Petrovi´c (2012). ISBN 978–86–85873–16–4 11. What is solidworks? https://www.technia.com/blog/what-is-solidworks/ 12. Guide to 3D Printing Materials: Types, Applications, and Properties. https://formlabs.com/ blog/3d-printing-materials/ 13. Guide to 3D printing. https://formlabs.com/3d-printers/

Calibration of Test and Measuring Equipment in Pandemic Conditions Belma Faki´c1

, Samir Lemeš2(B) , Branka Muminovi´c1 , Omer Beganovi´c1 , Mustafa Hadžali´c1 , and Kenan Varda3

1 University of Zenica, Institute “Kemal Kapetanovi´c”, 72000 Zenica, Bosnia and Herzegovina

[email protected]

2 Polytechnic Faculty, University of Zenica, 72000 Zenica, Bosnia and Herzegovina 3 Mechanical Engineering Faculty, University of Zenica, 72000 Zenica, Bosnia and Herzegovina

Abstract. In order to meet the requirements of product standards, accreditation and certification bodies, normal operation during production requires regular calibration of test and measuring equipment, providing the validity of testing and measurement results. If regular, standard-prescribed calibration is not performed, the results of tests and measurements become questionable. This paper analyses how the COVID-19 pandemic influenced regular calibrations of testing and measuring equipment by accredited laboratories. The companies from Bosnia and Herzegovina participated in a survey to estimate the existing capacity of the national quality infrastructure under extraordinary conditions. Keywords: Calibration · Measuring equipment · Pandemic conditions · Accredited laboratories · Maintenance

1 Introduction This research represents the results of a survey of the needs of business entities in Bosnia and Herzegovina for the calibration of test and measuring equipment by accredited laboratories. An analysis of the existing capacity of the quality infrastructure in Bosnia and Herzegovina and the capacity of companies to meet European Union (EU) requirements in terms of standards, accreditation and certification of their products, as well as their communication with institutions facilitating export to foreign markets, was carried out. Some business entities reported that they encounter difficulties during the process of establishing a quality management system as well as during its implementation.

2 Relevant Studies There were no studies, as of our knowledge, performed to estimate how the pandemic conditions influenced the specific process of measuring equipment calibration. The process requires travel and transportation, which were largely restricted during the pandemic, especially internationally. In small economies, such as Bosnia and Herzegovina, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 283–290, 2023. https://doi.org/10.1007/978-3-031-31066-9_30

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the quality infrastructure is very limited and relies largely on internationally accredited laboratories from other countries. It was really a challenge to maintain the calibration certificates under these restrictions. However, some studies were performed to estimate how these restrictions influenced the medical laboratories, as their operations were mostly excluded from restrictions to provide testing services for patients. The challenges of pandemic conditions in clinical diagnostic laboratories in an institute in United Kingdom were discussed by Russell et al. [1]. They intevrened in building a diagnostic pipeline, adapting the booking system, and staff planning approach. The restricted availability of onsite QMS (Quality Management System) mentors in the accreditation of clinical laboratories in Zambia during the pandemic was discussed in [2]. Authors recommended remote, offsite mentorship, strengthening training and certification of engineers, increasing stock of reagents and consumables, and performing interlaboratory comparisons on national level, as a response to emergency situations. Jackson and Genzen reviewed the operations of large medical refence laboratories within an university in United States under pandemic restrictions [3]. They changed some operating principles, increased use of IT tools, and adjusted budgeting practices. They identified laboratory employees as the most important resource responsible for uninterrupted operation. Rahman et al. explored the challenges to which the laboratories in wastewater treatment plants were exposed worldwide during pandemics [4]. They concluded that one fourth of surveyed laboratories had disruptions due to lack of spare parts for maintenance. One third reported degraded quality of data collected by the instruments, as equipment was not maintained and cleaned suffciently. They also identified instrument maintenance as the main issue with process control under these conditions. Prasetya et al. discussed in [5] the importance of standardization in Indonesia under pandemic conditions. They described how Indinesian metrological infrastructure announced a digital tool for remote calibration and digital proficiency testing, but there is no information available whether this system gave the proper results. Some authors described how digital technology could be utilized to overcome these restrictions. Marescotti et al. in [6] presented how a Japanese company developed a cloud-based platform for laboratory automation and management. However, this solution had no influence on calibration services. Santana et al. proposed a methodology for the remote calibration of meteorological sensors [7]. Their methodology uses Internet connectivity tools of current technologies in order to innovate and facilitate remote verification and calibration activities in real-time. Geronymo also presented a solution for hybrid-remote calibrations with remote control of calibration systems [8] for electrical measurement standards such as resistors, capacitors, inductors, capacitors, and AC-DC transfer standards for voltage and current. Garg et al. carried out a SWOT analysis on the digital transformation of metrological services in India [9]. They described how digital metrological infrastructure enables remote calibration, which can be used in extraordinary circumstances such as pandemic.

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Mirtsch et al. in [10] explored how COVID-19 pandemic strongly influenced conformity assessment bodies in Germany and how they responded to challenges imposed by these conditions. They identified the calibration services as the most severely affected activity in conformity assessment and quality assurance. On the other hand, the medical and healthcare laboratories have not been affected by these conditions as their services were maintained properly and managed to continue their operation without disruption other than overload. The most important tools that enabled proper response of certification bodies were sufficient IT resources.

3 Methods and Materials 3.1 Data Collection The collection of data on companies and institutions in Bosnia and Herzegovina that had problems due to the impossibility of calibrating test and measuring equipment during the pandemic, as well as the consequences that had an impact on their daily work, was carried out through an online survey and visits to companies and institutions in Bosnia and Herzegovina. The research instrument is the established contact with companies that need calibration services from accredited laboratories outside the country. 3.2 Research Methods The research methods applied within the project are the methods of induction and analysis. The application of the inductive method of reasoning is reflected in the analysis of collected data regarding the number of companies in Bosnia and Herzegovina that need calibration services from accredited laboratories outside the country, where, based on the collected facts, a conclusion is reached about the need to establish laboratory calibration activities, e.g. 3D measuring machines and their accreditation, as well as the necessary resources for establishment and accreditation. The reliability of the inductive conclusion directly depends on the number of investigated companies and institutions that need calibration, the representativeness of the analyzed data and the degree of reliability of the meaning of the facts. The analysis method is a scientific research procedure where the special needs of companies for the calibration of test and measuring equipment lead to the need to establish a calibration laboratory for at least one type of measuring equipment.

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4 Results 4.1 Online Survey Results The research started with an online survey, sent to more than 300 companies. The survey consisted of the following questions: 1. 2. 3. 4. 5. 6. 7.

The name of the respondent company Do you have measuring and testing equipment that requires calibration? Description of the equipment that requires calibration How calibration is carried out (multiple answers allowed)? Did you have any problems when performing calibrations during the pandemic? Description of the problems during calibration Which of the following problems did you have during the pandemic (multiple answers allowed)? 8. Briefly describe how did you overcome those problems 9. Whose help and support did you have when solving the mentioned problems (multiple answers allowed)? 10. Would you like to participate in further research through field visits? There were 45 respondents who filled in the survey. Figures 1, 2, 3, 4 and 5 show the online survey results. The list of prospective companies was obtained from the national Chamber of Commerce. The majority of responses came from metal processing and civil engineering companies, as we expected (Fig. 1). The ratio between the sectors actually reflects the structure of the economy in Bosnia and Herzegovina.

Fig. 1. Type of business

Five percent of interviewed companies are not even aware that calibration is required and obligatory, and 4% of companies do not use equipment requiring regular calibration by accredited laboratories (Fig. 2). The probable cause for lack of awareness could be that the responses were given by economists or lawyers, and not by engineers.

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Fig. 2. Do you have measuring and testing equipment that requires calibration?

Most companies use calibration services in the country, if they are available, and some of them use foreign calibration services (Fig. 3). Due to relatively small market in Bosnia and Herzegovina, it is understandable that not all measuring equipment can be calibrated within the country.

Fig. 3. How calibration is performed (multiple answers allowed)?

Despite pandemic conditions, more than one third of respondents reported no problems in calibration (Fig. 4). This could be explained with calibration intervals for specific measuring equipment being longer than pandemic conditions lasted. The most important difficulties were reported as increased costs or delays in services due to inability to perform calibration in a timely manner. Lack of institutional support is apparent (Fig. 5), as 89% of respondents reported no support to overcome these issues. Support from the government was directed more towards human resources, neglecting the equipment and quality infrastructure. Surprisingly, equipment manufacturers and suppliers offered almost no support for their customers, leaving laboratories to manage their problems on their own or, in some cases, by the company management.

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Fig. 4. Problems encountered during the pandemic

The companies used different methods to overcome the problems: – performed the essential calibration by themselves with the online supportof a service technician – delayed the calibration until the service was available – acquired an internal transfer standard – had to face working in the conditions of uncalibrated measuring equipment and with a reserve of the obtained results – sent requests to several addresses and found alternative suppliers

Fig. 5. Who supported you to overcome the problems (multiple answers allowed)?

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4.2 Field Visits The project team visited 18 companies who expressed their interest in extending and discussing the survey responses in an onsite visit. Most companies (14) were from the metal processing sector. The calibration services they use include humidity, temperature, length, hardness, flow, electrical conductivity, force, mass, heat conductivity, light intensity, and roughness.

5 Discussion Analysis of the collected data indicates the following: – Companies and institutions in Bosnia and Herzegovina mainly have equipment that can be calibrated in accredited laboratories from the country – The most represented measures of length, temperature, pressure, humidity, force, moment, hardness, electrical conductivity and mass – For the calibration of specific measuring quantities - ultrasound, roughness and illumination - companies hire laboratories outside Bosnia and Herzegovina – Equipment manufacturers most often carry out calibration of 3D coordinate measuring machines. The initial purchase of the semachines usually includes the maintenance agreement, which links the calibration with accompanying the software update. The maintenance agreement is the manufacturer’s requirement.

6 Conclusion Based on the conducted survey, one can conclude that there is no real need for the establishment of new accredited calibration laboratories in order to meet the requirements of product and service standards in terms of achieving satisfactory quality control and fulfilling the requirements of accreditation and certification bodies. The initial hypothesis that at least ten companies in Bosnia and Herzegovina could not calibrate their measuring and testing equipment due to restrictions imposed by the pandemic conditions was not confirmed in the observed sample. Most of the surveyed and visited companies stated that they had no problems during the pandemic, as most equipment is calibrated in domestic laboratories. The pandemic restrictions reflected only international services for the equipment that cannot be calibrated in the country. It is worth noting that some companies reported that equipment manufacturers or resellers insist that they also perform the calibration along with regular maintenance and software upgrades.

References 1. Russell, E., et al.: Adapting to the Coronavirus pandemic: building and incorporating a diagnostic pipeline in a shared resource laboratory. Cytometry A 99(1), 90–99 (2021). https://doi. org/10.1002/cyto.a.24248

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2. Daka, V., et al.: Challenges that may impact achieving and maintaining accreditation in clinical laboratories in Zambia during the COVID-19 pandemic. Pan Afr. Med. J. 38(290) (2021). https://doi.org/10.11604/pamj.2021.38.290.27836 3. Jackson, B.R., Genzen, J.R.: The lab must go on: clinical laboratory management in a world turned upside down. Am. J. Clin. Pathol. 155(1), 4–11 (2021). https://doi.org/10.1093/ajcp/ aqaa187 4. Rahman, A., et al.: Digital solutions for continued operation of WRRFs during pandemics and other interruptions. Water Environ. Res. 93(11), 2527–2536 (2021). https://doi.org/10. 1002/wer.1615 5. Prasetya, B., et al.: Innovation opportunity and challenge of standardization in response to COVID-19 pandemic and the socio-economic impact: a case study in Indonesia. Standards 2(1), 66–82 (2022). https://doi.org/10.3390/standards2010006 6. Marescotti, D., et al.: AI-driven laboratory workflows enable operation in the age of social distancing. SLAS Technol. 27(3), 195–203 (2022). ISSN 2472-6303 7. Santana, M.A., et al.: Remote and on-site calibration of meteorological sensors: a distributed common approach in Latin America. 11 Congresso Brasileiro de Metrologia. Rio de Janeiro 18–21.10.2021(2021) 8. Geronymo, G.M.: Digitalization of an Electrical Metrology Laboratory: Hybrid-remote calibrations. 11 Congresso Brasileiro de Metrologia. Rio de Janeiro 18–21.10.2021 (2021) 9. Garg, N., Rab, S., Varshney, A., Jaiswal, S.K., Yadav, S.: Significance and implications of digital transformation in metrology in India. Measurement Sens. 18, 100248 (2021). https:// doi.org/10.1016/j.measen.2021.100248 10. Mirtsch, M., Koch, C., Ashari, P.A., Blind, K., Castka, P.: Quality assurance in supply chains during the COVID-19 pandemic: empirical evidence on organisational resilience of conformity assessment bodies. Total Qual. Manag. Bus. Excell. (2022). https://doi.org/10.1080/147 83363.2022.2078189

Numerical Simulation of Viscoelastic Fluid Flow in a Channel Almin Halaˇc(B) and Ejub Džaferovi´c Faculty of Mechanical Engineering, University of Sarajevo, Vilsonovo šetalište 9, 71000 Sarajevo, Bosnia and Herzegovina [email protected]

Abstract. This paper describes a method and results of the numerical simulation of viscoelastic fluid flow in a two-dimensional channel. The governing equations are solved by a finite volume method, and a segregated solution procedure based on the SIMPLE algorithm is used. The rheological behaviour of the viscoelastic fluid is described by the upper-convected Maxwell model (UCM). After calculating the cell-centre stresses from the constitutive equations, the cell-face stresses must be calculated. However, linear interpolation can lead to decoupling between velocity and stress, resulting in an oscillating (checkerboard) velocity field, even for the correct stress values. To overcome this problem, a method for the calculation of the cell-face stresses based on the Rhie and Chow interpolation is developed. The developed method is tested on the flow in a two-dimensional channel. Although the discussion is limited to the channel flow, observations and conclusions presented in the paper should also be relevant for viscoelastic fluid flows in general. Keywords: viscoelastic flow · stress-velocity coupling · numerical simulation · channel flow · upper-convected Maxwell model

1 Introduction Many fluids encountered in industrial applications are non-Newtonian fluids that do not obey Stokes’ law of viscosity. Some of these fluids are viscoelastic fluids. Viscoelastic fluids show behaviour which is between the viscous fluids and the ideal elastic materials [1]. Under constant stress, the viscous fluid deforms at a continuous rate. When stress is removed, the fluid will remain deformed. Unlike viscous fluid, ideal elastic material deforms when stress is applied and returns to its original state after removing the stress. When stress is applied to the viscoelastic fluid, it will deform. After removing the stress, the fluid will attempt to return to its initial state and, to some degree, will succeed, which is a behaviour similar to the ideal elastic material. Consequently, the stress response depends on the current deformation and deformation history. In engineering practice, many fluids exhibit a combination of viscoelastic and time-dependent behaviour. Typical examples of fluids with viscoelastic behaviour are natural fluids, such as biological fluids and industrial fluids, such as paints, polymers, lubricants, foams, gels, soap solutions etc. The applications of viscoelastic fluids are vast and still expanding. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 291–297, 2023. https://doi.org/10.1007/978-3-031-31066-9_31

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Experimental investigations of viscoelastic fluids are usually expensive, difficult and time intensive. Therefore, numerical simulations are essential in understanding viscoelastic fluids and their behaviour in engineering practice. During the last decades, there has been considerable development in the simulation of viscoelastic fluid flows. Even though many numerical solvers have been developed, viscoelastic fluid simulations still remain a challenging task. The numerical simulations of viscoelastic fluids can be difficult for several reasons. An additional constitutive equation has to be solved, which is a highly nonlinear equation. The solution for the viscoelastic fluids requires additional six equations for stress to be solved. Even simple approximations of these equations give a large number of terms [2]. When dealing with viscoelastic fluids, no single constitutive model can describe the rheological behaviour of all viscoelastic fluids. The choice of a constitutive model for a viscoelastic fluid remains an open question. The constitutive models for viscoelastic fluids are adjusted to data from the experiment, which are obtained on the simple viscometric flows. Assuming an adequate constitutive equation is chosen, the choice of numerical implementation must be made, including the implementation of stabilization techniques. Different approaches include stabilization techniques such as booth-side diffusion, solvent-polymer stress, elastic-viscous stress, the original formulation, and others. Most of the previous studies were based on a finite element or finite difference method due to the great experience of these methods in solving problems related to the behaviour of solid bodies. One of the first numerical simulations based on the finite volume method (FVM) was reported in the work of Hu and Joseph [3]. They investigated viscoelastic flow over a cylinder using the UCM model. The first simulations based on the FVM were done on the staggered orthogonal meshes, which enable a simple coupling between the dependent variables [4]. Even relatively simple viscoelastic flows (for example, twodimensional flow in a channel), which is done on collocated meshes, can produce the checkerboard pattern of velocity and stress if the linear interpolation of the cell-face stress is used. Thus, the method for stress-velocity coupling is needed. Authors Olivera et al. [5] made a significant contribution by developing a method for simulation on the non-orthogonal collocated meshes and by developing the coupling algorithm for the velocity and stresses based on the Rhie and Chow interpolation [6], which was later improved in the work of [7] and [8]. Favero et al. [9] used OpenFOAM, where second-order linear interpolation of the cell-face stresses was done, which can lead to decoupling between velocity and stresses. Another method for stress-velocity coupling is developed by Habla [10], where the portion of the constitutive relation which causes deformation is treated implicitly, which can enhance the stability. In the recent study, authors Fernandes et al. [11] used an improved both sides diffusion approach which assures the coupling between velocity and stress where the right side diffusion term in the momentum equation is solved by the linear interpolation of the cell-centre gradient, which is calculated by using Gauss theorem. Besides the “classical implementation” of the governing equations with velocity, pressure and stresses, some other formulations were developed, such as stream function formulation [12], where the velocity-stress decoupling problem was avoided.

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2 Mathematical Method and Numerical Methodology The flow of viscoelastic fluid can be described by the equations of mass and momentum conservation:   ∂ ρdV + ρv · d s = 0, (1) ∂t V ∂ ∂t

S



 ρvdV + V



ρv ⊗ v · d s = S

 σ · ds +

S

ρfb dV ,

(2)

V

where t is the time, ρ is the density, v is the velocity vector, σ is the Cauchy stress tensor and fb is the body force. The stress tensor σ is calculated as: σ = T − pI,

(3)

where p is the pressure, I is the unit tensor, and T is the stress modeled by the upperconvected Maxwell model UCM model [13]: ∇

˙ T + λ1 T = 2μ D,

(4)

˙ is the is the rate of deformation where λ1 is the relaxation time, μ is the viscosity and D tens or calculated as:   ˙ = 1 ∇v + (∇v)T . (5) D 2 ∇

T is the upper-convected time derivate calculated as: ∇

T=

  ∂T + ∇ · (v ⊗ T) − T · ∇v + (∇v)T · T . ∂t

(6)

The numerical procedure for the viscoelastic fluid flows is different from the usual procedure for Newtonian fluids since the stresses cannot be directly evaluated from the deformation rate. The absence of linear diffusion in the momentum equation can make the solution procedure difficult or even impossible. Therefore, an extra diffusive term is added to the booth side and discretized as follows:  sf · sf μ∇v · d s = μf (vNi − vPi ) , (7) df · sf S

where μf is the viscosity on the cell-face, vNi and vPi are velocities in the cell-centers of the neighboring cells, sf is the surface vector and df is the distance vector between neighboring cell-centers. The momentum equation can be rewritten as:       ∂ ρvdV + ρv ⊗ v · d s + μ∇v · d s = μ∇v · d s+ σ · d s + ρfb dV . ∂t V V S

S

S

S

(8)

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To overcome the decoupling problem between the velocity and stress, a coupling method is proposed and employed for the simulation of the viscoelastic fluid flows. After calculating the cell-centre stresses from the constitutive equations, the cell-face stresses must be calculated. The calculation can be done by linear interpolation. However, linear interpolation can lead to decoupling between velocity and stress, resulting in an oscillating (checkerboard) velocity field, even for the correct stress values. To overcome this problem, a method for the cell-face stress values is proposed according to the Rhie and Chow interpolation [6]. The simple and efficient way to calculate the cell-face stresses Tf is:  ∇vf · if · df vNi − vPi sf + μf sf · sf , (9) Tf · sf · if = Tf · if − μf df · sf df · sf where if is the unit vector, ∇vf is the gradient on the cell-face calculated by the linear interpolation from the cell-centers. The cell-center velocity gradients are calculated by the Gauss theorem. Tf is the cell-face stress calculated by linear interpolation from the cell-centers. The part Tf · sf · if is added to the momentum equation and solved as the source term. The momentum equation can be solved separately from the constitutive equation. The proposed solution is similar to the solutions given in [7] and [8] but simpler since only the part of the constitutive equation with a velocity gradient from the deformation rate is used for the coupling. The methodology should be applicable to any constitutive relation since the constitutive equation is treated separately, while an extra diffusive term is added to the momentum equation. The FVM proposed by [14] is adopted as the framework for the analysis of the viscoelastic flows. The governing equations are discretized and solved using the finite volume method and a SIMPLE-like solution algorithm, as described in [14]. The upwind differencing scheme is used to calculate convected cell-face value, while the surface and volume integrals are calculated by the midpoint rule. Transient term is calculated by the Euler implicit scheme.

3 Results and Conclusions The proposed method is tested on the two-dimensional fluid flow in a channel, which is one of the standard benchmark cases for the simulation of the viscoelastic fluid flows. The channel height and length are L = 1 m and 10L, respectively. Viscoelastic fluid enters the channel at the maximum velocity 1 m/s. The viscosity of the fluid is μ = 2 Pa‧s and the relaxation time is λ = 1. The fluid density is ρ = 1 kg/m3 . Reynolds number is Re = 0,5 and the Weissenberg number is Wi = 0,4. Three different uniform meshes are considered, M1 with 50 × 10 cells, M2 with 50 × 20 cell and M3 with 50 × 40 cells. The steady simulation is used, where a maximum number of iterations is set to 500 and the convergence tolerance is set to 0,001. The under-relaxation factors used are 0,2 for mass conservation equation and 0,7 for momentum and stress equations. At the inlet, fully developed velocity profile is imposed. The no-slip boundary condition is set on the channel walls for velocity and the zero-gradient condition for stresses. The zero-gradient condition is set at the channel exit for all variables. The numerical results are compared with the analytical solution for the UCM fluid in the channel.

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The simulations are done using two different approaches for the calculation of the cell-face stresses. One set of results is obtained by using linear interpolation, while the second set of results is obtained using the stress-velocity coupling method given by Eq. 9. The velocity profiles near the pipe outlet obtained with different solution strategies are shown in Fig. 1. The stress profiles of T xy and T xx are shown in Figs. 2 and 3. One can see that linear interpolation of stress produces an unphysical profile of the velocity and stresses. Similar results can be observed on all three meshes, which means that finer meshes cannot resolve the problem of an unphysical profile of the velocity and stresses. When the velocity-stress coupling is applied, the profiles are predicted correctly even for the coarsest mesh.

Fig. 1. Velocity profile obtained on three meshes: linear interpolation (left) and stress-velocity coupling (right)

Fig. 2. Stress profile T xy obtained on three meshes: linear interpolation (left) and stress-velocity coupling (right)

The velocity magnitude near the inlet of the channel is shown in Fig. 4, where the velocity shows a checkerboard pattern if the cell-face stresses are calculated by linear interpolation. The checker board pattern disappears when the method for stress-velocity coupling is used. The results are very similar to the result obtained in [11]. The relatively simple case of the two-dimensional channel flow demonstrates the advantage of the stress-velocity coupling method. The proposed formulation is essential

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Fig. 3. Stress profile T xx obtained on three meshes: linear interpolation (left) and stress-velocity coupling (right)

Fig. 4. Velocity magnitude near the inlet of the channel: linear interpolation (top), stress-velocity coupling (bottom)

to get stable and accurate results. Although the discussion is limited to the flow in a channel, observations and conclusions presented in the paper could also be relevant for flows of viscoelastic fluid in general.

References 1. Chhabra, R.P.: Non-Newtonian fluids: an introduction. In: Krishnan, J., Deshpande, A., Kumar, P. (eds.) Rheology of Complex Fluids, pp. 3–34. Springer, New York, NY (2010). https://doi.org/10.1007/978-1-4419-6494-6_1 2. Morozov, A.N., van Saarloos, W.: An introductory essay on subcritical instabilities and the transition to turbulence in visco-elastic parallel shear flows. Phys. Rep. 447(3–6), 112–143 (2007) 3. Hu, H.H., Joseph, D.D.: Numerical simulation of viscoelastic flow past a cylinder. J. Nonnewton. Fluid Mech. 37(2–3), 347–377 (1990)

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4. Afonso, A.M., Oliveira, M.S., Oliveira, P.J., Alves, M.A., Pinho, F.T.: The finite volume method in computational rheology. In: Finite-Volume Methods–Powerful Means of Engineering Design, pp. 141–170 (2012) 5. Oliveira, P.J., Pinho, F.T., Pinto, G.A.: Numerical simulation of non-linear elastic flows with a general collocated finite-volume method. J. Nonnewton. Fluid Mech. 79(1), 1–43 (1998) 6. Rhie, C.M., Chow, W.L.: Numerical study of the turbulent flow past an airfoil with trailing edge separation. AIAA J. 21(11), 1525–1532 (1983) 7. Oliveira, P.J., Pinho, F.T.: Numerical procedure for the computation of fluid flow with arbitrary stress-strain relationships. Numer. Heat Transfer Part B Fundam. 35(3), 295–315 (1999) 8. Matos, H.M., Alves, M.A., Oliveira, P.J.: New formulation for stress calculation: application to viscoelastic flow in a T-junction. Numer. Heat Transfer Part B Fundam. 56(5), 351–371 (2010) 9. Favero, J.L., Secchi, A.R., Cardozo, N.S.M., Jasak, H.: Viscoelastic flow analysis using the software OpenFOAM and differential constitutive equations. J. Nonnewton. Fluid Mech. 165(23–24), 1625–1636 (2010) 10. Habla, F.: Modeling and CFD simulation of viscoelastic single and multiphase flows (Doctoral dissertation, Technische Universität München) (2015) 11. Fernandes, C., Araujo, M.S.B., Ferrás, L.L., Nóbrega, J.M.: Improved both sides diffusion (iBSD): A new and straightforward stabilization approach for viscoelastic fluid flows. J. Nonnewton. Fluid Mech. 249, 63–78 (2017) 12. Comminal, R., Pimenta, F., Hattel, J.H., Alves, M.A., Spangenberg, J.: Numerical simulation of the planar extrudate swell of pseudoplastic and viscoelastic fluids with the streamfunction and the VOF methods. J. Nonnewton. Fluid Mech. 252, 1–18 (2018) 13. Oldroyd, J.G.: On the formulation of rheological equations of state. Proc. R. Soc. London. Series A Math. Phys. Sci. 200(1063), 523–541 (1950) 14. Demirdži´c, I., Muzaferija, S.: Numerical method for coupled fluid flow, heat transfer and stress analysis using unstructured moving meshes with cells of arbitrary topology. Comput. Methods Appl. Mech. Eng. 125(1–4), 235–255 (1995)

Using Fractal Dimensions in Modeling Complex Systems in Engineering Maryna Holofieieva1(B) , Volodymyr Tonkonogyi2 , Iraida Stanovska3 , Andrii Pavlyshko2 , and Sergii Klimov2 1 Department of Digital Technologies in Engineering, Odessa National Polytechnic University,

Shevchenko ave., 1, 65044 Odessa, Ukraine [email protected] 2 Department of Information Technologies in Design, Odessa National Polytechnic University, Shevchenko ave., 1, 65044 Odessa, Ukraine [email protected] 3 Department of Higher Mathematics and Systems Modeling, Odessa National Polytechnic University, Shevchenko ave., 1, 65044 Odessa, Ukraine [email protected]

Abstract. The article is devoted to the development and implementation of elements of express methods for designing heterogeneous objects. The method “of express-selection from the results of reverse calculation on the direct model RCDM” is proposed. It allows you to dramatically speed up the creation of a direct computer model of an object, testing it and making a decision on its compliance with the specified operating conditions of the object. In the case of a negative answer, the original direct model is corrected, followed by a retest. The method consists in using the fractal dimension when modeling complex systems. Heterogeneous objects consist of at least two elements, between which there is a boundary. This boundary has a fractal dimension, and deliberate distortion (crumpling) of the original object leads to a change in the fractal dimension of the boundaries. The latter makes it possible to bring the distortion of the object to the extent that the boundaries reach the surface of the object and to numerically estimate the fractal dimension of the boundaries after crushing on the model. As a result, we get a number that allows us to measure the initial fractal dimension of this boundary, and therefore, to measure its state. Keywords: r complex objects · express design · transfer models · intensive parameter · fractal dimension

1 Introduction Design - by definition - is the creation of a description of an object that does not yet exist [1]. This implies the main problem of the design process - the inability to assess the “correctness” of the selected option of the object until the design is fully completed, the object is manufactured and tested. Thus, optimization in design comes down to solving © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 298–304, 2023. https://doi.org/10.1007/978-3-031-31066-9_32

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many inverse problems: from object to project. The solution of the contradictions connected with this problem is sought, as a rule, on the way of creating models of the future object and testing the latter with the help of simulation. This problem is especially relevant when designing complex systems, which include interacting elements that jointly solve a certain common problem and have the following properties in combination: the absence of a single functioning algorithm in the form of some consistent mathematical description; “noisy” model, which complicates the design and observation, due not so much to the presence of random noise generators, but to a large number of secondary processes; non-stationarity, expressed in the drift of characteristics, changes in parameters, evolution in time; irreproducibility of experiments with it [2]. As a rule, all this makes it difficult to use in CAD systems such “standard” back calculation from the required properties of the system to the parameters of its design or manufacturing technology. In the process of such calculations, using of the so-called fractal dimension of individual elements of the designed systems can make a significant simplification of the applied models.

2 Research Methodology If we consider the concept of a fractal in relation to heterogeneous materials, then a certain universal chemically structured unit is embedded in it, which contains information about the structure and properties of the material under study [3]. Using this approach opens up new possibilities in system design. The fractal type model is based on the definition of the self-similarity of an object [4]. At the same time, the main property of fractal objects is the independence of their properties from the scale, i.e. the results of studies of parameters at one of the dimensional levels are extended to the remaining scale levels [5]. This principle of hierarchical organization is often found in nature and, of course, manifests itself in material structures, including heterogeneous materials [6]. There are various methods for determining the fractal dimension [7]. In the general case, they come down to establishing a certain characteristic parameter, the change in the value of which at different scale levels is used to judge the fractal dimension [8]. At the same time, for the effective application of such methods, it is necessary to take into account the specific properties of specific objects of study [9]. When designing a complex system, most often they resort to creating its version using a model. Next, the result of the “reverse” simulation of this option is calculated and the result of the calculation is compared with the requirement for the future object (the method of selection from the results of reverse calculation on the direct model RCDM). In this article, the application of this approach in mechanical engineering is considered using two examples. In the first one, we are talking about designing the parameters of the technology for the process of manufacturing products from syntegran. The second example considers the application of the proposed method in the foundry industry. Syntegran is a non-metallic heterogeneous material consisting of a polymer matrix based on epoxy resin, fillers in the form of crushed stone with a fraction of up to 10 mm, as well as fine mineral filler. According to the main physical and mechanical characteristics, syntegran is close to natural granite, while having a significant advantage over the

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latter - manufacturability [10]. The manufacturing technology of syntegran products is the casting of a low-flowing mixture with subsequent vibrocompaction. The time of bulk polymerization is determined by the geometric characteristics of the manufactured parts [11]. Basically, polymer concrete, which includes syntegran, is used to replace blocks of natural granite and cast iron in the manufacture of basic parts of technological equipment, plates of measuring machines, instruments and other equipment, the materials of which are subject to special requirements. This is due, first of all, to the fact that the materials under consideration have such properties as non-magnetism, corrosion resistance, low thermal conductivity, high dimensional and thermal stability, and vibration resistance. There is a possibility of directed regulation of the properties of the material under consideration (strength, stiffness, vibration damping characteristics, level of operating temperatures) by selecting the composition, changing the reinforcement schemes, the ratio of the components and the macrostructure of the material [12]. Figure 1 shows the dependence of the mechanical properties of syntegras on the content of the polymer binder δ. σcomp – compressive strength; σt – tensile strength; E – dynamic modulus of elasticity; λ – damping factor. Figure 2 shows a fragment of a frame made of syntegran with cast-iron mortgages. Along with the considered high performance characteristics of signtegrans, some of their shortcomings should be noted. The characteristics of heterogeneous materials are stochastic in nature. As a result, during the processing of their components, defects arise caused by random changes in the composition: the presence of shells, delamination of embedded parts, the mixture getting into cavities during casting, which are not intended for this by design, heterogeneity of composition and structure, and, consequently, physical and mechanical properties in the volume of the casting [14]. To analyze the properties of non-metallic heterogeneous materials, for example, in the non-destructive testing of products, a simplified structural model of such a material at the meso- and microlevels can be used (Fig. 3) [15]. In the materials under consideration, the structure is formed from elements of at least three hierarchical levels. H, A, and a are the characteristic linear dimensions of the volume of the material, heterogeneous volumes of the mesolevel and microlevel, respectively. In this case, H >> A >> a. It should be noted that the properties of the material as a whole, the ensemble, or individual elements of the mesolevel differ significantly from each other [16]. When engineering the design of a part made of syntegran or its manufacturing technology, the task is as follows. Evaluate the design so that at this early stage the question can be answered whether the object will have the desired properties after manufacture. For example, if the object is the frame of a large metalworking machine, will it ensure that the specified requirements for vibration resistance are met? As you can see, the object model should allow us to calculate the vibration resistance parameters of the future frame. To do this, the model must be able to reproduce the movement and impacts inside the frame and at the same time evaluate the vibration parameters of its surface. If the latter do not meet the requirements, then the design parameters of this object can be changed in the model, after which the vibration resistance study is repeated.

Using Fractal Dimensions in Modeling Complex Systems in Engineering

Е, GPа

σсomp σt, МPа

λ

Е

Е 40

301

0,03

20 0

σсomp

0,03

30 15 0 20

10

0,02

10 0

λ

σt 0,02

50 0

3

6

9

12

15

18

20

δ, %

σcomp – compressive strength; σt – tensile strength; Е – dynamic modulus of elasticity; λ – damping factor. Fig. 1. Dependence of the syntegran properties on the content of the binder

As for the foundry, it should also be classified as extremely complex in terms of the possibility of measuring the parameters of ongoing processes. The latter are characterized by stochasticity, nonstationarity, high intensity, and multidimensionality [17]. For example, the occurrence of air pockets in a hardening casting can be detected using infrared thermal imaging techniques due to the difference in surface temperatures in the defective and defect-free zones. In this situation, there is a need for a quick response in order to eliminate the identified artifact by external influence, for example, using vibration. However, temperature measurements using infrared thermometry, in the best case, will give some space-time display of the object - the temperature field, which is very difficult for mathematical description, and hence embedding in the control system [18, 19]. Of course, to solve design problems, these parameters must be not only metrologically understandable, but also strictly and, if possible, simply described mathematically [20, 21]. This possibility is provided by the proposed method “of express-selection from the results of reverse calculation on the direct model – RCDM”. Figure 4 shows the procedure for developing a technology for obtaining new castings using the RCDM method.

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Fig. 2. The fragment of the syntegranic frame of a metal-cutting machine with cast-iron mortgages

Fig. 3. Structural model of a non-metallic heterogeneous material

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drawing, 3d model of the part

drawing of the

Agreement, remarks

Technology

Agreement

Foundry Melting results

Mechanical processing shop

Design department

Analysi s results

CAD department

technical control department

Casting Fig. 4. Development of technology for obtaining new castings using the RCDM method

3 Conclusion In the article, an express method for designing complex heterogeneous systems is considered, which includes the construction of a complex model of the primary state of the system being designed. It is possible to transform the design of the designed system and its manufacturing technology into models, as well as evaluate the change in state after each step of the transformation and choose the best parameters after comparison with the terms of reference for the designed object. The application of the method is considered on the example of designing parts from a non-metallic heterogeneous material - syntegran, as well as in foundry production. In order to optimize the design process, it is proposed to use the so-called fractal dimension of individual elements of the designed systems, which makes it possible to significantly simplify the applied models. Further research is aimed at detailing the proposed method, as well as the study of the mathematical apparatus on which it is based.

References 1. Rosenfeld, L.G., et al.: Early diagnosis of vessel diseases of the lower extremities due to infrared thermography. Ukrainian Med. Chronicle. 2(82) III–IV, 28–30 (2011). (in Ukrainian) 2. Riley, M.A., Bonnette, S., Kuznetsov, N., Wallot, S., Gao, J.: A tutorial introduction to adaptive fractal analysis. Front. Physiol. 3(371). (2012). https://doi.org/10.3389/fphys.2012.00371 3. Bolshakov, V.I., Volchuk, V.N., Durov, Y.I.: The main stages of fractal modeling in materials science. Metal Sci. Therm. Process. Metals 2, 24–29 (2019). (in Russian) 4. Stanovskaya, I.I., Kolesnikova E.V., Guryev I.N.: Fractal dimension of project activity. In: Proceedings of the 21st Seminar Modeling in Applied Scientific Research, pp. 23–25 Odessa: ONPU (2013). (in Ukrainian) 5. Kroviakov, S., Mishutin, A., Pishev, O.: Management of the properties of shipbuilding expanded clay lightweight concrete. Int. J. Eng. Technol. 7(3.2), pp. 245–249 (2018)

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6. Daši´c, P.: Scientific and technological trends: Selected scientific-professional papers (in Serbian). Vrnjaˇcka Banja: SaTCIP Publesher Ltd., 2020. – 305 str. ISBN 978–86–6075–072–5 7. Ikhlazov, S.Z.: Vibro diagnostics by fractal analysis. Omsk Sci. Bull. 2 (110), 235–239 (2012). (in Russian) 8. Krasikova, I.E., Krasikov, I.V., Kartuzov, V.V., Muratov, V.B., Vasiliev, A.A.: Multifractal characteristics of hot-pressed composites from AlB12–AlN nanopowders. Nanosystems, nanomaterials, nanotechnologies Nanosistemi, Nanomateriali, Nanotehnologii 18(1), 89–96 (2020). (in Russian) 9. Vyrovoy, V.N., Dorofeev, V.S., Sukhanov, V.G.: Composite building materials and structures: structure, self-organization, properties. - Odessa. - 168 (2010). (in Russian) 10. Dovgan, I.V., Kersh, V.Y., Kolesnikov, A.V., Semenov, S.V.: Statistical study of the porous structure of heat-insulating composites. Bull. ODABA 60, 86–90 (2015). (in Ukrainian) 11. Dovgan, I.V., Kolesnikov, A.V., Sharygin, V.N., Dmitrenko, M.P., Kirilenko, G.A.: Structural changes in building composites from the position of fractal geometry (in Russian). Bull. Odessa State Acad. Life Archit. 62, 56–60 (2016) 12. Tonkonogyi, V.M. Holofieieva M.O., Balan V.O.: Studying of the characteristics of vibration energy dissipation in the basic parts of syntegran machines. Cutting and tools in technological systems: Intern. sci.-tech. Sat. - Kharkov: NTU “KhPI”, 85, 282–287 (2015). (in Ukrainian) 13. Brusentseva T.A., Filippov A.A., Fomin V.M.: Composite materials based on epoxy resin and nanoparticles. In: Proceedings of the Altai State University, vol. 1, no. 81, pp. 25–27 (2014). (in Russian) 14. Aliha, M.R.M., Imani, D.M., Salehi, S.M., Shojaee, M., Abedi, M.: Mixture optimization of epoxy base concrete for achieving highest fracture toughness and fracture energy values using Taguchi method. Compos. Commun. 32, 101150 (2022) 15. Bezymyanniy, Y.G., Brodnikovsky, N.G., Koziratsky, E.A., Talco, O.V.: Acoustic nondestructive testing of a multicomponent alloy based on niobium. Bull. Natl. Tech. Univ. KhPI. Ser. Electr. Trans. Technol. Zb. Sci. Prats. 19(1128), 119–126 (2015). (in Russian) 16. Bezymyanniy, Y.G., Koziratsky, E.O., Komarov, K.A., Solntsev, V.P., Talco, O.V.: Step-bystep ultrasonic control of the power of a rich-component powder material based on Ni. Bull. Ukrainian Mater. Sci. Assoc. Named After. I.M. Frantsevich. 12, 11–16 (2019). (in Ukrainian) 17. Czichos, H., Smith, L.: Springer Handbook of Metrology and Testing. Categories of Metrology, pp. 37–38 (2011) 18. da Silva, R.B. et al.: Analytical measurement: measurement uncertainty and statistics, 240 (2012) 19. Zhang, Y., Sydorenko, I., Tonkonogyi, V., Bovnegra, L., Daši´c, P.: Structural analysis of direct passive pressure reducing valves using modified kinematic graphs. In: Karabegovi´c, I. (ed.) NT 2020. LNNS, vol. 128, pp. 114–121. Springer, Cham (2020). https://doi.org/10.1007/9783-030-46817-0_13 20. Zhang, H., Yin, Y., Zhang, S.: An improvement ELM algorithm for the measurement of hot metal temperature in blast furnace. Neurocomputing 174, Part A, 232–237 (22 January 2016) 21. Xue, W.J.: Chen effect of fractal dimension of fine aggregates on the concrete chloride resistance. In: 5th International Conference on Durability of Concrete Structures Shenzhen University, Shenzhen, Guangdong Province, P. R. China (Jun 30–Jul 1, 2016)

Vibration Infrared Thermal Method of Defectoscopy of Non-metallic Heterogeneous Materials Volodymyr Tonkonogyi, Oleksandr Stanovskyi, Maryna Holofieieva(B) Oleksandr Levynskyi, and Sergii Klimov

,

Department of Information Technologies in Design, Odessa National Polytechnic University, Shevchenko ave. 1, 65044 Odessa, Ukraine [email protected]

Abstract. Effective using of non-metallic heterogeneous materials and constructions from them requires accurate determination of parameter values characterizing the internal processes that occur in them throughout the entire life cycle. Particular attention should be paid to reliable, operational measurement that could be performed outside the research laboratory. The complexity of the structure, special physical and mechanical properties, the presence of various defects, as well as complex internal processes, which neglecting leads to significant measurement errors and, accordingly, to incorrect decisions regarding their application. That is, classical measurement methods cannot be used to study heterogeneous structures. It is proposed to use the vibrational infrared thermal method of detecting defects of non-metallic heterogeneous materials, which is based on the phenomenon of thermal energy release in their locations under the influence of mechanical vibrations. This method of thermal energy generation has advantages over classical methods, primarily because it does not lead temperature changes in defect-free zones. This increases the accuracy of detecting the location of the defect. In addition, the signal-to-noise ratio increases. A general system designed for flaw detection of non-metallic heterogeneous materials with the help of infrared technology devices with vibrationally excited thermal energy is proposed. Keywords: non-metallic heterogeneous materials · internal processes · flaw detection · vibration infrared thermal method · infrared thermometry

1 Introduction In order to ensure the advance development of technology in various branches of the economy, including the military-industrial complex, intensive using of new structural materials is necessary, which can become the basis of the restoration and development of industry [1]. Various kinds of heterogeneous structures, including composite materials, which have specific physical and mechanical properties different from the total properties of the constituent components, are increasingly being used [2]. It should be noted that the characteristics of such materials have a stochastic nature. In addition, composites are © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 305–312, 2023. https://doi.org/10.1007/978-3-031-31066-9_33

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quite difficult objects for diagnosis, as they are characterized by anisotropy of properties, a wide variety of types of structures, and specific physical properties (electrical, thermal, sound insulating) [3]. The effectiveness of using the heterogeneous materials and constructions from them requires the measurement of reliable values of the parameters of the internal processes occurring in them at various stages of operation [4]. At the same time, special attention should be paid to reliable, efficient and cheap research [5].

2 Research Methodology The variety of reinforcing filler, matrices, reinforcement schemes used in the creation of heterogeneous structures (including composite materials) makes it possible to regulate the strength, stiffness, level of operating temperatures and other properties in a targeted manner by selecting the composition, changing the ratio of components and their microstructure [6]. It is possible to state the perspective of using non-metallic heterogeneous materials in various sectors of the economy [7]. However, taking into account the complexity of the structure, in the process of manufacturing parts from them, various defects may occur: cracks, delaminations, air pockets, uneven distribution of components in the volume of the material. Disadvantages include the variability of physical and mechanical properties. The question of the quality and reliability of heterogeneous materials, products and structures from them is one of the most urgent problems of modern scientific and technical development. Effective methods and means of control are of particular importance in solving such a problem [8]. It should be noted that known experimental methods, which are developed for the studying of traditional structural materials, in many cases cannot be used to measure the parameters of heterogeneous structures. This is primarily due to the fact that the latter are characterized by complex internal processes, which neglecting leads to significant measurement errors and, accordingly, to incorrect decisions regarding their application [1]. The problem of determining the characteristics of behavior of heterogeneous structures and structural elements from them depending on the characteristics of operation also remains unsolved [9]. To solve such problems, it is necessary to solve at least the following tasks: – Establish a set of parameters characterizing internal processes in heterogeneous structures; – Obtain parameters of interaction of external influences with heterogeneous structures; – Develop methods of measuring parameters of internal processes in heterogeneous structures; – Carry out practical tests and implementation of research results in relevant branches of the economy. Solving the problems described above should be based on a deep understanding of special sections of mathematics, which is the basis of the development of methods for studying the parameters of internal processes in heterogeneous objects.

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It is known that temperature fields arise in materials (including heterogeneous ones) with structural defects under the influence of vibration. This is due, first of all, to the dissipation of the energy of mechanical vibrations on defects (especially on cracks) and its transformation into thermal energy. Temperature gradients caused by the transformation of mechanical energy into thermal energy are also observed during compression, stretching, and destruction of solid bodies [10]. In the absence of structural disturbance, heat release can occur due to two mechanisms. The first is related to mechanical hysteresis that occurs during cyclic loading of materials. That is, static loads within the fluidity of the material do not cause significant temperature effects. Another mechanism of heat release is caused by plastic deformation that occurs during the initiation and propagation of cracks and other types of damage. It has a local character [11]. It should be noted that the change in temperature is proportional to the sum of deformations and does not depend on their direction. Accordingly, the analysis of thermoelasticity does not make it possible to draw a conclusion about the nature and direction of deformation [12]. Dynamic changes in temperature and mechanical loads are described by the formula [10]: βδσ σT =− = −Kδσ T0 ρCp

(1)

where σ T – cyclic temperature change; T 0 – absolute temperature of the research object; β – coefficient of linear expansion, K−1 ; δσ – changing the sum of the main mechanical loads; C p – heat capacity at constant pressure; K – coefficient of thermal elasticity; ρ – density of the material under investigation. When the thermodynamic equilibrium of the research object with the environment is disturbed, an excess temperature field appears on its surface, the parameters of which become informative regarding the presence of defects, primarily near-surface defects. It is possible to state the perspective of using the vibrational infrared thermal method of flaw detection, which is based on vibrationally excited thermal fields in heterogeneous structures [13]. Thermal control methods are based on the interaction of the thermal field of the object with the heat-sensitive element, the transformation of the parameters of the studied thermal field into an electrical signal and its transmission to the recording device [14]. Active and passive methods of thermal control can be distinguished [15]. When using the latter, the thermal field in the object of control arises during its operation (for example, in metallurgy, chemical slack, industry of building materials and mechanical engineering). That is, it does not need an external source of thermal influence. As for active thermal control, it involves heating the control object with an external energy source [16]. Figure 1 shows the scheme of active thermal control. Nowadays, the operation of the thermal load source is based on the stimulation of defects by thermomechanical methods [10]. It differs favorably from classical methods

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of thermal excitation (for example, optical, ultrahigh-frequency, convective) in that it does not lead to changing in temperature in defect-free zones. This leads to an increase in the accuracy of determining the location of the defect, and also increases the signalto-noise ratio. As for measuring the object’s surface temperature, infrared devices are most often used, primarily thermal imagers. When conducting research with the help of such devices, it is essential to identify and eliminate systematic and random errors that affect the measurement result and characterize doubts about the reliability of the results [17]. This especially applies to low-amplitude temperature signals (temperature differences in defective and defect-free zones). It should be noted that the main issue that arises when calculating temperatures based on the results of thermal imaging measurements is an error in specifying the emissivity of the surfaces of the investigated objects [18].

Front surface

Source of heat load

defect

Back surface

Object surface temperature meter

Fig. 1. Scheme of active thermal control

This physical quantity is characterized by the coefficient of emissivity of surfaces, the value of which for the surface of each specific object is individual and depends not only on the material, but also on the condition of the surface and the conditions of measurement (first of all, the angle of observation of the surface, which significantly affects the specified coefficient) [19]. This fact leads to a methodical error, which is caused by the reflection of infrared waves from the border of separation of two different media. It leads to the need to conduct thermal imaging measurements of shear angles, which in turn increases the time required to detect defects. For dielectrics, which in many cases are non-metallic heterogeneous materials, the emissivity coefficient is constant in the interval of observation angles 0… 60º. Beyond this range, the mentioned coefficient changes significantly when directed tangentially [20, 21]. Figure 2 shows the results of

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the study of the influence of the observation angle on the accuracy of measuring the surface temperature of a non-metallic heterogeneous material.

----- actual temperature value; ----- measured temperature value (viewing angle 60°); ---- measured temperature value (viewing angle 70°); ----- measured temperature value (viewing angle 80°); ----- measured temperature value (viewing angle 85°); ----measured temperature value taking into account the observation angle Fig. 2. The influence of the observation angle on the accuracy of measuring the surface temperature of a non-metallic heterogeneous material.

On the basis of the phenomena described above, a general system was proposed, which is intended for defectoscopy of non-metallic heterogeneous materials with the help of infrared technology devices with vibrationally excited thermal energy. Figure 3 shows the structural scheme of such a measuring system, consisting of the following subsystems: – – – – – –

Object of study; Generator of mechanical vibration Thermal imager; Personal Computer; Devices for measuring temperature by the contact method; A mathematical model for calculating the emissivity coefficient, which reflects information about the research object (material, surface condition, structural features)

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Digitization of analog infrared stream

Infrared stream to video stream converter Digital video stream

Object of study

IR analog stream

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Thermal imager

Devices for measuring temperature by the contact method

Visualization of information

Memorization and collection of measurement information

Results of observation

Results of measuremen t Emissivity coefficient

Error of measuremen t

PC

Data processing

Math model A priori information about the research object

material

Theoretical transformati on of information

Comparison of a priori information with experiment

Making a decision

Surface condition Design features

Fig. 3. Structural diagram of such a measuring system

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3 Conclusion The spilled method of flaw detection of non-metallic heterogeneous materials, based on vibrationally excited thermal fields in heterogeneous structures. The advantages of this method over classical defectoscopy methods are shown. The proposed system of non-contact temperature measurement using infrared devices, which implements the specified method. Such a system is designed to measure the integral parameters of non-metallic thermal processes in heterogeneous structures due to the processing of infrared flows from their surface and can be integrated as a separate link into the general automated control system. At the next stage of the research, it is planned to develop mathematical models that describe the temperature distribution on the surface of heterogeneous materials during excitation in the defective zone of thermal energy by the vibration method.

References 1. Holofieieva, M., Tonkonogyi, V., Kolesnik, M.: Control of the properties of materials with a multi-level structure(in Ukrainian). East Euro. Sci. J. 4, 61–65 (2015) 2. Mamand, H., Chen, J., Barnett, S.: Experimental and modelling investigation of mechanical behaviour of ageing concrete. Constr. Build. Mater. 155, 1138–1146 (30 Nov 2017) 3. Mamand, H., Chen, J.: Extended digital image correlation method for mapping multiscale damage in concrete. Mater. Civil Eng. 29(10), 04017179 (1 Oct 2017) 4. Daši´c, P.: Scientific and technological trends: Selected scientific-professional papers (in Serbian). Vrnjaˇcka Banja: SaTCIP Publesher Ltd., 2020. – 305 str. ISBN 978–86–6075–072–5 5. Aliha, M.R.M., Imani, D.M., Salehi, S.M., Shojaee, M., Abedi, M.: Mixture optimization of epoxy base concrete for achieving highest fracture toughness and fracture energy values using Taguchi method. Compos. Commun. 32 (June 2022) 6. Yu, G., Nameless, N.G., Brodnikovsky., E.A., Koziratsky, O.V.: Talco: Acoustic nondestructive testing of a multicomponent alloy based on niobium (in Russian). Bulletin of the National Technical University “KhPI”. Series: Electricity and transformation technology. Zb. Sci. Pratsi. 19(1128), 119–126 (2015) 7. Yu, G., Bezymyanniy, E.O., Koziratsky, K.A., Komarov, V.P., Solntsev, O.V.: Talco: stepby-step ultrasonic control of the power of a rich-component powder material based on Ni (in Ukrainian). Bull. Ukrainian Mater. Sci. Assoc. Named After. I.M. Frantsevich 12, 11–16 (2019) 8. Torquato, S.: Modeling of physical properties of composite materials. Int. J. Solids Struct. 37(1–2), 411–422 (2000) 9. López Jiménez, F.: Variations in the distribution of local strain energy within different realizations of a representative volume element. Composites Part B: Eng. 176, 107111 (1 November 2019) 10. Vavilov, V.P., Nesteruk, D.A., Khorev, V.S.: Ultrasonic infrared method for detecting impact damage and fatigue cracks in metals and composites. In the World of NK, vol. 1, no. 47, pp. 36-58. (March 2010). (in Russian) 11. Shiryaev, V.V., Khorev, V.S.: Thermal control of impact damage in CFRP using ultrasonic stimulation (in Russian). Control Diagn. 11, 11–14 (2011) 12. Vavilov, V.P., Shiryaev, V.V., Khorev, V.S.: Processing the results of active thermal control by wavelet analysis (in Russian). Defectoscopy 4, 70–79 (2011)

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13. Shepard, S.M., Ducar, R.: Quantative infrared defect detection in composite aerospace structures. In: 45th International SAMPRE Symposium, p. 10 (2000) 14. Maladague, X.: Theory and practice of infrared technology for nondestructive testing, Wiley Series in Microwave and Optical Engineering, p. 682. John Wiley & Sons. New York. U.S.A (2001) 15. Bellisola, G., Sorio, C.: Infrared spectroscopy and microscopy in cancer research and diagnosis. Am. J. Cancer Res. 2(1), 1–21 (2012) 16. Andres, E., Sanchez, R., de Bustamante, X.: Infrared thermography and ultrasound both test analyzing valves 2144 6B 425. Buenos Aires 10p. 17. Chen, H., Wang, J.: Study for image fusion based on wavelet transform. Microelectr. Comput. 5(27) 39–41 (2010) 18. Oborskyi, G.O., Levynskyi, O.S., Holofieieva, M.O.: Study of the influence of the emissivity of materials on the accuracy of the thermal imaging control method (in Ukrainian). Technol. Audit Product. Reserves 2/3(28), 4–7 (2016) 19. Wang, J., Zheng, S.: Visible and Infrared image fusion method based on wavelet transform and YUV. J. Northwestern Poly Tech. Univ. 3(33), 208–211 (2013) 20. Zhang, Y., Sydorenko, I., Tonkonogyi, V., Bovnegra, L., Daši´c, P.: Structural analysis of direct passive pressure reducing valves using modified kinematic graphs. In: Karabegovi´c, I. (ed.) NT 2020. LNNS, vol. 128, pp. 114–121. Springer, Cham (2020). https://doi.org/10.1007/9783-030-46817-0_13 21. Usamentiaga, R., Venegas, P., Guerediaga, J., Vega, L., Molleda, J., Bulnes, F.G.: Infrared thermography for temperature measurement and non-destructive testing. Sensors 14, 12305– 12348 (2014)

The Possibility of Applying ChatGPT (AI) for Calculations in Mechanical Engineering Dragi Tiro(B) University “DžemalBijedi´c” of Mostar, Sjevernilogor bb., 88 000, Mostar, Bosnia and Herzegovina [email protected]

Abstract. The research started from the assumption that using a modern artificial intelligence chatbot “ChatGPT” can significantly facilitate the job of a mechanical engineer when calculating in practice. The intention was to apply AI in many different tasks in the field of mechanical engineering, and to come to conclusions by statistical processing of the results. However, using ChatGPT in several examples of calculations we obtained incorrect results or wrong formulas and the like. Therefore, the application of ChatGPT on a large number of examples was abandoned and several of them are presented in this paper. It was concluded that for now, the use of ChatGPT in solving the problem of machine calculations is not desirable, it is even dangerous because of obtaining the wrong solutions. Keywords: AI · ChatGPT · Mechanical Engineering · Calculations

1 Introduction There are many definitions of artificial intelligence [1], and here it can be said that when a device or software solves tasks or does jobs for which a person needs intelligence, then it is the artificial intelligence (AI). Lately, many companies, especially software companies, have been striving to develop software that would help man or replace him in many jobs. This is how Google Assistant, Apple Siri, chatGPT and others are developed.OpenAI is a corporation and laboratory engaged in artificial intelligence research. They are developing a GhatGPT system.It was used by millions of people, and it is a software that communicates (for now) through chat, i.e., a chatbot. GPT stands for Generative Pre-trained Transformer. It uses powerful language to generate human-like responses. In this research, we tried to use chatGPT as an aid to solve the calculations that occur in the practice of mechanical engineers.Our intention was to try to solve more engineering problems by applying ChatGPT. Then, to compare the obtained solutions with the solutions obtained by engineers without the use of AI and using statistical tools to see how effective the application of ChatGPT is in solving engineering problems.

2 Application in Calculations of Circular Saw Machine When constructing circular saw (Fig. 1), we calculated all the machine parts and selected standard parts without the use of AI. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 313–320, 2023. https://doi.org/10.1007/978-3-031-31066-9_34

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Fig. 1. Circular saw

Then we applied chatGPT for the calculation of individual parts. 2.1 Transmission of Motion Using Belts and Pulleys In chatGPT we entered the following:The rotation transfer is carried out with a smaller pulley over the belt to a larger pulley. The diameter of the smaller pulley is D1 = 63 mm, and the diameter of the larger pulley is D2 = 190 mm. The belt speed is v = 2,373 m/s. What is the angular velocity of the smaller pulley? What is the angular speed of the larger pulley? The expected response was: R1 · ω1 = R2 · ω2 = 2, 373 m/s. ω1 =

v 2.373 v 2.373 = = = 75, 33s(−1) and ω2 = = 24, 98s(−1) R1 0, 0315 R2 0, 095

(1)

So, the task is quite easy, and we thought to get the correct answer, but we got the following answer (Fig. 2): The angular velocity of the smaller pulley (ω1) and the angular speed of the larger pulley (ω2) are related by the belt speed (v) and the pulley diameters (D1 and D2) using the following equation: ω1/ω2 = (D1/D2) * (v2/v1). Since the belt speed is given as v = 2,373 m/s and the pulley diameters are given as D1 = 63 mm and D2 = 190 mm, we can use these values to calculate the angular velocities of the pulleys:

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ω1 = (D1/D2) * (v2/v1) * ω2 ω1 = (63/190) * (2,373/2,373) * ω2 ω1 = 0.33 * ω2. ω2 = (D2/D1) * (v1/v2) * ω1 ω2 = (190/63) * (2,373/2,373) * ω1 ω2 = 3 * ω1. Therefore, the angular velocity of the smaller pulley is 0.33 times the angular speed of the larger pulley. It’s not possible to know the exact value of the angular velocity or the angular speed without knowing the RPM or the time it takes to complete one full rotation.

Fig. 2. Answers to the question for transmission of motion using belts and pulleys

ChatGPT thinks that you need to know RPM or the time of a single rotation to calculate ω1 and ω2, however this is not true. 2.2 Calculation of Electric Motor Power We asked the following question for ChatGPT:It is necessary to find the power of a electric motor. The electric motor drives the circular saw. The total main tangential force acting on the circular is Fo = 1682.97 N. The cutting speed of the circular saw is vr = 2.5 m/s. The mechanical utilization rate of the machine considers power losses in transmission. The mechanical utilization rate of the machine is eta = 0.76. What is the power of the electric motor? The expected correct answer is: PM =

1682.97N · 2.5m/s F0 · vr = = 5543, 03W η 0.76

(2)

However, we received a response from ChatGPT: The power of the electric motor can be found using the formula: Power = Fo * vr * eta where Fo is the total main tangential force acting on the circular saw, vr is the cutting speed of the circular saw, and eta is the mechanical utilization rate of the machine.

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Given that Fo = 1682.97 N, vr = 2.5 m/s, and eta = 0.76, the power of the electric motor is: 1682.97 N * 2.5 m/s * 0.76 = 3121.902 W. Since this is an incorrect answer, we wrote: The formula is not good. The formula is: Power = Fo * vr / eta. ChatGPT replies: You are correct, my apologies for the mistake. The formula for power in mechanical systems is: Power = Fo * vr / eta. Given that Fo = 1682.97 N, vr = 2.5 m/s, and eta = 0.76, the power of the electric motor is: 1682.97 N * 2.5 m/s / 0.76 = 4166.622 W. But that’s not the correct result, it should have been 5543, 03W . 2.3 Ball Bearing Selection In Fig. 1, we have two identical ball bearings on the machine. We selected the UCP 309 bearing using classic calculation according to the SKF catalog with basic dynamic load rating CD = 52.7 [kN] (Fig. 3) [3].

Fig. 3. Pillow block ball bearing units UCP 309 from SKF catalog [3]

Question: It is necessary to choose a ball bearing. The bearing is placed on the shaft with a diameter of d = 45 mm. In this place where is the bearing the total force Fa = 4174,15 N. The bearing operates at room temperature tw = 22 °C, so the operating temperature is less than 150 °C. ChatGPT: Based on the information provided, it is recommended to choose a ball bearing with a bore size of 45 mm to fit the shaft diameter, and a rating that can handle a total force of 4174.15 N. Additionally, the operating temperature should be less than 150 °C, which is suitable for a standard ball bearing. It would be helpful to consult with a bearing supplier or manufacturer to determine the specific model and type of bearing that would be best suited for your application.

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Question: The bearing supplier or manufacturer is SKF. Can you find the ball bearing? ChatGPT: SKF offers a wide range of ball bearings that can handle different types of loads and operate in various environments. To determine the specific ball bearing that would be best for your application, it would be helpful to know additional information such as the required speed and life of the bearing, and the type of load it will be supporting. Without this information, it is difficult to recommend a specific ball bearing. I recommend you to consult with SKF’s technical support or use their online product selection tool, which will help you to find the most suitable ball bearing based on your specific application requirements. Question: The speed is np = 238,74 min−1 ; the type of load is radial. The life of the bearing Tn = 10000 h. ChatGPT: Based on the additional information provided, a suitable ball bearing from SKF would be the 22310 E/VA405 spherical roller bearing. This bearing is designed for high radial loads and moderate axial loads, and can handle speeds of up to 238.74 min–1 . It has a rating life of 10,000 h and it is suitable for use in applications where the operating temperature does not exceed 150 °C. It’s important to note that this is just one option and it’s always recommended to check with the SKF’s technical support or use their online product selection tool for a more accurate and specific recommendation. So, he suggests to selectspherical roller bearing 22310 E/VA405 (Fig. 4). But the bearing he proposed has a diameter of 50 mm, a dynamic load of 228 kN, reference no. Rotates 4800 o/min, and all these sizes do not fit.

Fig. 4. Spherical roller bearing 22310 E/VA405 from SKF catalogue

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3 The Hand Lever Guillotine Shear for Sheet Metal We construct the hand lever guillotine shear (Fig. 5) without the use of AI. Now we will apply ChatGPT to calculate all the machine parts and selected standard parts. 3.1 The Force of Sheet Metal Cutting ˇ We need to calculate the cutting force of sheet metal F when cutting off material C.1331 in improved condition: σm = 650 [N/mm2 ], εot = 0,55; rake angle: ϕ =7◦ ; sheet thickness: s = 3[mm]. F = 0, 6 · σm · εot ·

s2 32 [N] = 0, 6 · 650 · 0, 55 · [N] = 15722, 66 [N] tan ϕ tan 7

(3)

The formulas used and the calculation process is carried out according to [4].

Fig. 5. Hend lever guillotine shear

Having calculated the cutting force, we now set the ChatGPT task: Cutting off sheet metal is carried out on the hend lever guillotine shear with flat inclined knives. The sheet metal to be cut has a tensile strength of 650 N/mm2 . The angle between the knives is 7 ◦ . Sheet thickness is 3 mm. What is the force of sheet metal cutting? ChatGPT replies: To calculate the cutting off force of sheet metal, it is necessary to know the coefficient of friction between sheet metal and knives, as well as the angle between the knives. In this case, concrete data are given (the tensile strength of the sheet is 650 N /mm2, the angle between the blades is 7 degrees, the thickness of the sheet is 3 mm).

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The cutting off force of sheet metal can be calculated using the following formula: F = (K * t * z * s) / cos(phi) where: F - cutting force K - friction coefficient between sheet metal and knives (concrete information not given) t - tensile strength of sheet metal (650 N/mm2) z - sheet thickness (3 mm) s - cutting speed phi - angle between knives (7 degrees). Without the friction coefficient and cutting speed, I can’t answer the question precisely. We give the information requested by ChatGPT: The friction coefficient I found, is 0.3. The cutting speed is 2 mm/s. ChatGPT replies: Thanks for the update information. With the known friction coefficient of 0.3 and the above parameters,the cutting off force of the sheet metal can be calculated using the following formula: F = (0.3*650 N/mm2*3 mm*2 mm/s)/cos(7degrees) = 5,958N. So, the cutting off force is 5,958 N. However, it is important to note that these calculated values are only approximate and may vary depending on other factors, such as cut geometry, knife quality, etc. Comment of solution provided by ChatGPT: We are not sure if the formula: F=

K ·t·z·s cos(ψ)

(4)

used by ChatGPT is correct. In [5] is the formula for calculating the cutting force: F=

0, 5 · s2 · Rm tan(ψ)

(5)

where: Rm - tensile strength of sheet metal; s - sheet thickness. However, we have not been able to find the formula provided by ChatGPT (4) in the literature. Also, if we include the values in the formula (4), we get: F = 1178.79 N, while the value obtained by ChatGPT F = 5958 N is completely false. 3.2 Calculation of the Force in the Joint of the Upper Knife F2 When the upper knife is disassembled (Fig. 6), we get a very simple single-edged lever.

Fig. 6. Drawing of the upper knife loaded with forces F and F2

From the sum of the moments of force for point A, we can calculate the force F2 : A M = 0

F · p = F2 · q => F2 =

F·p q

(6)

320

D. Tiro

F2 =

15722, 66 · 39, 5 = 2631, 54 [N]. 236

Now we are setting this problem for ChatGPT: Two forces act on a single arm lever and the lever is in equilibrium. The force F acts from below vertically on the arm 39.5 mm. Force F2 acts from above vertically on the arm 236 mm. The force F is 15722.66 N. What is the force F2? ChatGPT replies: If the lever is in equilibrium, the force F and the force F2 must be equal in power and opposite direction. This means that the force F2 = 15722.66 N. We answer: But the forces aren’t in the same point. There are different arms of forces. ChatGPT: Yes, it’s the right. The forces do not actat the same point and therefore the momentum principle is used. The principle of momentum states that the moment of force is equal to the product of force and distance from the point where the force is applied to the point where the moment is viewed. This means that F 39.5 = F2 236. F2 = (F39.5)/236 = 15722.66 39.5/236 = 4490.27 N. The force F2 is 4490.27 N. Comment: We see that the force F2 is incorrectly calculated. We gave a few more tasks to ChatGPT, but none of the tasks were done correctly.

4 Conclusion Applying ChatGPT to several examples of calculations in mechanical engineering we obtain incorrect procedures, formulas, or results. We did not get an exact solution in any of the tasks, so we gave up further research. We can conclude that at this stage of AI development, this should not be used when solving engineering practice problems. The use of ChatGPT can even be dangerous because incorrect results are obtained. It is possible that in the future this will change, and that AI will advance to the point that it can be used as a tool in the engineering business. An example of this is language translation software, which 20–30 years ago were very bad and could not be used. With continuous improvement, these software can be used today to translate text, even speech, very effectively. We hope that the development of AI will soon lead to the fact that Artificial Intelligence software can be used in solving the tasks of mechanical engineers in their practice. It may be possible to get better answers by asking questions differently to ChatGPT, but that would certainly not change these conclusions.

References 1. Polišcuk, J.E.: Ekspertni sistemi, ETF Podgorica (2004) 2. Junaid, Q.: Engineering education in the era of ChatGPT: promise and pitfalls of generative AI for education. TechRxiv. Preprint (2022) 3. https://www.skf.com/us/products/mounted-bearings/ball-bearing-units/pillow-block-ball-bea ring-units/productid-UCP%20309. 20 Jan 2023 4. Musafija, B.: Obrada metala plasticnom deformacijom, Svjetlost Sarajevo (1988) 5. Serruys, W.: Sheet Metalworking, LVD Company, ISBN 90-807224-7-2 (2006)

Performance Comparison of the Simscape Multibody Solvers for Articulated Mechanical Systems Ömer Ekim Genel1 , Rosario La Regina2 , and Carmine Maria Pappalardo3(B) 1 Department of Mechanical Engineering, Istanbul Technical University, Istanbul 34437, Turkey 2 MEID4 Academic Spin-Off of the University of Salerno, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy 3 Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy [email protected]

Abstract. SIMSCAPE MULTIBODY is considered an efficient simulation tool for the dynamic analysis of articulated mechanical systems due to the ease of modeling complex mechanical systems, the CAD import feature, and allowing for the implementation of advanced control techniques. Therefore, the objective of this study is to evaluate the performances of seven solvers implemented in SIMSCAPE MULTIBODY in terms of the error and the total elapsed simulation time. As the benchmark problem, a physical pendulum under three different load scenarios is considered, namely dynamic torque, no torque, and static torque. Computed angular position and angular velocity values at the final time step are compared with those obtained from the SIMULINK model. In addition to comparing the total elapsed simulation times in the SIMSCAPE MULTIBODY environment, the total elapsed simulation times are also compared with those obtained from SIMULINK simulations. The numerical results found in this study show a good agreement between the effectiveness of the solvers analyzed and appreciable differences in their efficiency. Keywords: Dynamical simulations · SIMSCAPE MULTIBODY · Performance evaluation · Equations of motion solvers · Articulated mechanical systems

1 Introduction Engineering systems have been evolving into more complex forms day by day, therefore it is required to analyze significant system parameters during the design process by using more detailed approaches [1, 2]. The computer modeling and simulation of dynamic systems can be considered one of the significant steps of the engineering design process [3, 4].This is because it can provide useful information on the system behavior in a short time from a virtual prototype instead of producing and analyzing an actual physical prototype [5, 6]. Depending on the complexity of the system under consideration and design time limitations, this step can be performed by developing a specified source code or by © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 321–328, 2023. https://doi.org/10.1007/978-3-031-31066-9_35

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using a premade commercial software code [7, 8]. In this sense, the SIMSCAPE product family, by The MathWorks, Inc., provides an efficient modeling technique called the physical modeling approach to model real-world physical systems such as robots, electrical power systems, fluid networks, and drivetrains [9, 10]. SIMSCAPE MULTIBODY is a specialized SIMSCAPE product belonging to the MATLAB family that is used to simulate articulated mechanical systems and its block library provides detailed modeling capability for rigid and flexible bodies, joints, gears, cables, and similar mechanical components. Especially due to the ease of model construction, making it possible to implement advanced control applications, and CAD import feature, the application area of SIMSCAPE MULTIBODY has been increasing day by day [11–13]. From the computational point of view, it can be stated that the low error and the short computation time are two primary indicators of good performance of a simulation tool. In this paper, the preliminary results of a systematic comparative analysis of the performance of the SIMSCAPE MULTIBODY solvers mentioned before are reported.

2 Benchmark Problem The physical pendulum shown in Fig. 1 is modeled as a uniform rigid link with L = 0.5 (m) half-length, H = 0.02 (m) half-width, and m = 1.5 (kg) mass. The rigid rod is connected to the ground at point O by a frictionless revolute joint, which allows the rotation of the link in XY plane [14].

Fig. 1. Physical pendulum.

It is assumed that a uniform gravitational acceleration having a magnitude equal to 9.807 (m/s2 ) acts on the body through its center of mass G along the Y-axis. By defining θ as the system degree of freedom, which represents the angular displacement of the physical pendulum from X-axis, the equation of motion of the physical pendulum can be written as:   (1) mL2 + Izz θ¨ + mgL cos θ = Te where Izz refers to the mass moment of inertia of the pendulum around its center of mass and Te is the externally applied torque. In this study, three load scenarios are considered namely, static torque, no torque, and dynamic torque [15]. The static torque scenario

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323

corresponds to the static analysis of the physical pendulum in which the required torque (T0 ) to keep the body at the initial angular position θ0 is computed as: T0 = mgL cos θ0

(2)

In this study, it is assumed that the physical pendulum starts its motion from the initial angular position θ0 = π/3 (rad) with no initial angular velocity. The no torque scenario corresponds to the case in which the physical pendulum is subjected only to the gravitational force. Finally, in the dynamic torque scenario, it is assumed that a sinusoidal excitation torque having the following time law affects the body: Te = T0 + Ta sin(2π fe t)

(3)

where Ta is the amplitude of the exctitation torque equal to 5 (Nm), fe is the excitation frequency equal to 1 (Hz), and t stands for the time variable measured in seconds [16].

3 Simulation Methods In addition to the SIMSCAPE MULTIBODY model of the physical pendulum, the SIMULINK model of the physical pendulum is also developed for verification and comparison purposes in this study. The scenario to be run in the simulations is defined through the control input of the multiport switch by using the load_flag variable defined in the MATLAB script. Since the simulations of both models are controlled using scripts, the arguments of the blocks used in the models are parameterized. In this study, ode45, ode23, ode113, ode15s, ode23s, ode23t, ode23tb solvers are considered [17]. For all solvers, the relative tolerance, the absolute tolerance, and the maximum step size are taken as 10–8 (rad), 10–10 (rad), and 10–3 (s), respectively. Consistency tolerance is 10–9 (m) in the SIMSCAPE MULTIBODY model [18]. The simulation time considered in the analysis is 10 (s). In the MATLAB script, these simulation parameters are implemented by using set_param command, and sim command is used to run the simulation. Furthermore, SIMULINK presents a very useful interface called Solver Profiler that provides detailed information on the solver behavior during simulation. In the programmatic interface, solverprofiler.profileModel command can be used for profiling, as was done in this study. To access the elapsed simulation time the TimingInfo struct in simOut.Simulation Metadata object is used. This struct presents detailed information on timing such as initialization, execution, termination, and total elapsed wall time values. In this study, total elapsed wall time information presented in TimingInfo struct is considered. Since the elapsed wall time in a simulation depends on the internal dynamics of the computer, each simulation is performed five times and averaged [19].

4 Results and Discussion The considered result set is selected as the angular position and angular velocity at the final time step for each scenario since these numerical results are subjected to the accumulation of errors during the entire time marching of the dynamical simulation [20].

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Table 1. Comparison of angular position and angular velocity values at the final time step for different solvers (Dynamic torque scenario) Method

Solver

Angular position (rad)

Angular velocity (rad/s)

SIMSCAPE MULTIBODY

ode113

382.2440769803730000

73.5022731885477000

ode15s

382.2440767400550000

73.5022730740439000

ode23

382.2440711008370000

73.5022721379572000

ode23s

382.2441255061390000

73.5022817503522000

ode23t

382.2441383939840000

73.5022601172232000

ode23tb

382.2442295882910000

73.5022753125582000

ode45

382.2440769810190000

73.5022731885391000

ode113

382.2440769803730000

73.5022731885476000

ode15s

382.2440767398870000

73.5022730740309000

ode23

382.2440711008390000

73.5022721379568000

ode23s

382.2441255061430000

73.5022817503519000

SIMULINK

ode23t

382.2441383940180000

73.5022601172171000

ode23tb

382.2442295882550000

73.5022753125565000

ode45

382.2440769810200000

73.5022731885391000

As can be seen from Table 1, angular positions and angular velocities at the final time step both computed from the SIMSCAPE MULTIBODY model and the SIMULINK model are consistent with each other for the dynamic torque scenario. Table 2 presents a comparison of angular position and angular velocity values at the final time step for the no torque scenario. As shown, results obtained from SIMSCAPE MULTIBODY and SIMULINK simulations are in good agreement. Table 2. Comparison of angular position and angular velocity values at the final time step for different solvers (No torque scenario) Method

Solver

Angular position (rad)

Angular velocity (rad/s)

SIMSCAPE MULTIBODY ode113

– 4.147032216962250000 – 0.797533230585763000

ode15s

– 4.147032297478610000 – 0.797532254789387000

ode23

– 4.147032396015190000 – 0.797530372970011000

ode23s

– 4.147034702158140000 – 0.797509349027643000

ode23t

– 4.147035896351530000 – 0.797469439680650000

ode23tb – 4.147043335045840000 – 0.797396584784833000 (continued)

Performance Comparison of the Simscape Multibody Solvers

325

Table 2. (continued) Method

Solver

Angular position (rad)

Angular velocity (rad/s)

ode45

– 4.147032216962320000 – 0.797533230584676000

SIMULINK

ode113

– 4.147032216962290000 – 0.797533230585105000

ode15s

– 4.147032297477820000 – 0.797532254802743000

ode23

– 4.147032396015240000 – 0.797530372969463000

ode23s

– 4.147034702157500000 – 0.797509349034025000

ode23t

– 4.147035896351510000 – 0.797469439680091000

ode23tb – 4.147043335046150000 – 0.797396584782620000 ode45

– 4.147032216962230000 – 0.797533230585946000

Performing a static analysis in the time-domain requires a careful determination of simulation parameters (such as step size, absolute and relative tolerances) since the accumulated numerical error during time integration can cause a drift in the output parameters. This drift behavior may be more apparent in the analysis of complex multibody systems [20]. As shown in Table 3, obtained results from the SIMSCAPE MULTIBODY model are consistent with those computed by the SIMULINK model and initial conditions for the static torque scenario. Table 3. Comparison of angular position and angular velocity values at the final time step for different solvers (Static torque scenario) Method

Solver

Angular position (rad)

Angular velocity (rad/s)

SIMSCAPE MULTIBODY ode113

1.047197551196600000 – 0.000000000000017764

ode15s

1.047197551196600000 – 0.000000000000018753

ode23

1.047197551196600000 – 0.000000000000017764

ode23s

1.047197551196600000 – 0.000000000000017764

ode23t

1.047197551196600000 – 0.000000000000018936

ode23tb 1.047197551196600000 – 0.000000000000016299 SIMULINK

ode45

1.047197551196600000 – 0.000000000000017764

ode113

1.047197551196600000 0.000000000000000000

ode15s

1.047197551196600000 0.000000000000000000

ode23

1.047197551196600000 0.000000000000000000

ode23s

1.047197551196600000 0.000000000000000000

ode23t

1.047197551196600000 0.000000000000000011

ode23tb 1.047197551196600000 0.000000000000000000 ode45

1.047197551196600000 0.000000000000000000

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In Fig. 2, in addition to the total elapsed SIMSCAPE MULTIBODY simulation time, the normalized total time, which is defined as the ratio of the total elapsed SIMSCAPE MULTIBODY simulation time to the total elapsed SIMULINK simulation time, is presented for comparison in each scenario. As can be seen, total elapsed simulation times are below 1 s in all simulations. In the dynamic torque scenario, there are 13980 Jacobian updates (one Jacobian update per step), 1 solver reset, and 1 solver exception in ode23s, which behaves as the relatively slowest solver. Moreover, the total simulation time for this solver in the SIMSCAPE MULTIBODY simulation is approximately 1.7 times slower than its SIMULINK equivalent. On the other hand, it can be stated that ode15s is the relatively fastest solver in SIMSCAPE MULTIBODY simulations for this scenario with 10016 steps, 1 solver reset, 1 Jacobian update, and 1 solver exception, even though it is approximately 2.08 times slower than its SIMULINK equivalent. In the no torque scenario, ode113 acts as the fastest solver with 10014 steps and 1 solver reset. Furthermore, based on the profiler information, ode23t has 11706 steps, 1 solver reset, and 1 Jacobian update and it performs approximately 2.3 times slower in SIMSCAPE MULTIBODY than SIMULINK simulation method. In the static torque scenario, while ode45 with 10001 steps and 1 solver reset is the slowest one, ode23 with the same number of steps, and the number of solver reset acts as the fastest one. Additionally, it can be stated that ode15s with 10001 steps, 1 solver reset and 1 Jacobian update performs approximately 2.53 times slower in SIMSCAPE MULTIBODY than its SIMULINK equivalent.

Fig. 2. Total elapsed SIMSCAPE MULTIBODY simulation times and normalized total times for different simulation scenarios.

5 Conclusions With the developments in technology, engineering systems can be developed in more detail [21, 22], and computer modeling and simulation of engineering systems play a critical role in the design process [23, 24]. SIMSCAPE MULTIBODY has been increasingly used by researchers and engineers from different disciplines due to the ease of

Performance Comparison of the Simscape Multibody Solvers

327

modeling, allowing for the implementation of advanced control techniques and its CAD import feature [25]. In a computer simulation, the performance of a solver can be quantified in terms of the error and the elapsed simulation time, and these two performance indicators can vary depending on the system under consideration [26–28]. In this study, the performances of seven solvers used in the SIMSCAPE MULTIBODY environment (ode45, ode23, ode113, ode15s, ode23s, ode23t, ode23tb) are investigated in terms of the error and the total elapsed simulation time for the physical pendulum under three different load scenarios, namely dynamic torque, no torque, and static torque. Computed results are compared with those obtained from the SIMULINK model in terms of error and it is shown that they are in good agreement with the SIMULINK results. In terms of the total elapsed simulation time, it is shown that solver performance can vary depending on the scenario and the total elapsed time in SIMSCAPE MULTIBODY simulation can be approximately two times greater than its SIMULINK equivalent at each scenario [29, 30].

References 1. Sun, X., Liu, H., Song, W., Villecco, F.: Modeling of eddy current welding of rail: threedimensional simulation. Entropy 22, art. no. 947 (2020) 2. Salvati, L., d’Amore, M., Fiorentino, A., Pellegrino, A., Sena, P., Villecco, F.: Development and testing of a methodology for the assessment of acceptability systems. Machines 8(47) (2020) 3. Formato, A., Romano, R., Villecco, F.: A novel device for the soil sterilizing in sustainable agriculture. In: Karabegovi´c, I. (ed.) NT 2021. LNNS, vol. 233, pp. 858–865. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_94 4. Liguori, A., Armentani, E., Bertocco, A., Formato, A., Pellegrino, A., Villecco, F.: Noise reduction in spur gear systems. Entropy, 22(1306) (2020) 5. De Simone, M.C., Guida, D.: Experimental investigation on structural vibrations by a new shaking table. In: Carcaterra, A., Paolone, A., Graziani, G. (eds.) AIMETA 2019. LNME, pp. 819–831. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-41057-5_66 6. Colucci, F., De Simone, M.C., Guida, D.: TLD Design and development for vibration mitigation in structures. Lect. Notes Netw. Syst. 76, 59–72 (2020) 7. Rivera, Z.B., De Simone, M.C., Guida, D.: Unmanned ground vehicle modelling in Gazebo/ROS-based environments. Machines 7(2), art. no. 42 (2019) 8. De Simone, M.C., Rivera, Z.B., Guida, D.: Obstacle avoidance system for unmanned ground vehicles by using ultrasonic sensors. Machines 6(2), art. no. 18 (2018) 9. De Simone, M.C., Veneziano, S., Guida, D.: Design of a non-back-drivable screw jack mechanism for the hitch lifting arms of electric-powered tractors. Actuators 11(12), 358 (2022) 10. De Simone, M.C., Celenta, G., Rivera, Z.B., Guida, D.: Mechanism design for a low-cost automatic breathing applications for developing countries. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V. NT 2022. Lecture Notes in Networks and Systems, vol. 472, pp. 345–352. Springer, Cham (2022). https://doi. org/10.1007/978-3-031-05230-9_40 11. Guida, R., De Simone, M.C., Daši´c, P., Guida, D.: Modeling techniques for kinematic analysis of a six-axis robotic arm. IOP Conf. Ser. Mater. Sci. Eng. 568 (1), art. no. 012115 (2019) 12. Siwek, M., Baranowski, L., Panasiuk, J., Kaczmarek, W.: Modeling and simulation of movement of dispersed group of mobile robots using Simscape multibody software. AIP Conf. Proc. 2078, 020045 (2019)

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13. Mohan, M.S., Anbumalar, V., Kumar, P.S.S.R.: Investigation on joint dynamic property of Nanoclay based redundant SCARA robot. Period. di Minral. 91, 117–135 (2022) 14. De Simone, M.C., Guida, D.: Modal coupling in presence of dry friction. Machines 6 (1), art. no. 8 (2018) 15. De Simone, M.C., Ventura, G., Lorusso, A., Guida, D.: Attitude controller design for microsatellites. Lect. Notes Netw. Syst. 233, 21–31 (2021) 16. De Simone, M.C., Laiola, V., Rivera, Z.B., Guida, D.: Dynamic analysis of a hybrid heavyvehicle. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V. NT 2022. Lecture Notes in Networks and Systems, vol. 472, pp. 236–243. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_27 17. Pappalardo, C.M., Vece, A., Galdi, D., Guida, D.: Developing a reciprocating mechanism for the emergency implementation of a mechanical pulmonary ventilator using an integrated CAD-MBD procedure. FME Trans. 50(2), 238–247 (2022) 18. Pappalardo, C.M., La Regina, R., Guida, D.: Multibody modeling and nonlinear control of a pantograph scissor lift mechanism. J. Appl. Comput. Mech. 9, 129–167 (2023) 19. Li, T., Kou, Z., Wu, J., Yahya, W., Villecco, F.: Multipoint optimal minimum entropy deconvolution adjusted for automatic fault diagnosis of hoist bearing. Shock Vibr. 2021, art. no. 6614633 (2021) 20. Pappalardo, C.M., Guida, D.: A comparative study of the principal methods for the analytical formulation and the numerical solution of the equations of motion of rigid multibody systems. Arch. Appl. Mech. 88(12), 2153–2177 (2018). https://doi.org/10.1007/s00419-018-1441-3 21. Naviglio, D., et al.: Study of the grape cryo-maceration process at different temperatures. Foods 2018(7), 107 (2018) 22. Villecco, F., Aquino, R.P., Calabrò, V., Corrente, M.I., Grasso, A., Naddeo, V.: Fuzzy-assisted ultrafiltration of wastewater from milk industries. In: Naddeo, V., Balakrishnan, M., Choo, KH. (eds.) Frontiers in Water-Energy-Nexus—Nature-Based Solutions, Advanced Technologies and Best Practices for Environmental Sustainability. Advances in Science, Technology and Innovation, pp. 239–242. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-130688_59 23. Liguori, A., Formato, A., Pellegrino, A., Villecco, F.: Study of tank containers for foodstuffs. Machines 9, art. no. 44 (2021) 24. Formato, A., Ianniello, D., Romano, R., Pellegrino, A., Villecco, F.: Design and development of a new press for grape marc. Machines 7(3), 51 (2019) 25. Formato, A., Ianniello, D., Pellegrino, A., Villecco, F.: Vibration-based experimental identification of the elastic moduli using plate specimens of the olive tree. Machines 7(2), art. no. 46 (2019) 26. Muscat, M., Cammarata, A., Maddio, P.D., Sinatra, R.: Design and development of a towfish to monitor marine pollution. Euro-Mediterr. J. Environ. Integr. 3(1), art. no. 11 (2018) 27. Cammarata, A., Lacagnina, M., Sinatra, R.: Closed-form solutions for the inverse kinematics of the Agile Eye with constraint errors on the revolute joint axes. In: IEEE International Conference on Intelligent Robots and Systems, art. no. 7759073, 317–322, November 2016 28. Huang, Z., Xi, F., Huang, T., Dai, J.S., Sinatra, R.: Lower-mobility parallel robots: theory and applications. Adv. Mech. Eng. art. no. 927930 (2010) 29. Neziri´c, E., Isi´c, S., Karabegovi´c, I.: Vibration quantity share of multiple faults with similar frequency spectrum characteristics in rotational machinery. Periodica Polytechnica Mech. Eng. 66(3), 213–218 (2022) 30. Tomovi´c, R., Dizdar, S., Isi´c, S., Tuka, S., Karabegovi´c, I.: FEM analysis of inspection manhole on large steel tanks. Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng. 235(4), 1235–1247 (2021)

Virtual Prototyping of a Dynamic Vibration Absorber for the Vibration Control of a Frame Structure Giuseppe Isola1 , Rosario La Regina1 , Carmine Maria Pappalardo2(B) , and Valentino Paolo Berardi2 1 MEID4 Academic Spin-Off of the University of Salerno, Via Giovanni Paolo II,132,

84084 Fisciano, Italy 2 Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy [email protected]

Abstract. The control of structural vibrations in the mechanical, aerospace, and civil fields is becoming increasingly important in recent years. A fundamental problem in the design of civil and industrial structures is the high vibratory level that characterizes them due to environmental factors, such as high windiness or high sensitivity to seismic phenomena of the areas in which the structures are located. Particular attention is paid to non-dissipative systems, known as dynamic absorbers, used to modify the behavior of buildings in seismic territories or in areas with high winds. The purpose of these devices is to absorb a portion of the incoming mechanical energy in order to decrease the demand for energy that the structure must dissipate, thereby reducing its damage. The aim of this paper is, therefore, to analyze different types and design methodologies of dynamic absorbers and any fields of their application in order to highlight their contribution to dynamic dampening of mechanical vibrations. Keywords: mechanical vibrations · structural control · dynamic vibration absorbers

1 Introduction This paper aims to design a tuned mass damper capable of dampening the vibrations of a structure subjected to external stresses. The term “vibration control” refers to the set of techniques and devices that make it possible to mitigate quickly, reliably, and accurately the vibrations of machines and structures caused by their operation or external stresses [1]. The vibration of a structure could be caused by natural powers such as wind or earthquakes, or by a seemingly harmless vibration source that causes ruinous reverberations in the structure. These concepts are linked to all modern anti-seismic regulations, according to which most buildings are still designed to be subjected to high damage, during an exceptional event (for example seismic), but avoid collapse, preserving human lives. Innovative methods of structural control and structural retrofitting have become, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 329–337, 2023. https://doi.org/10.1007/978-3-031-31066-9_36

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in recent years, extremely topical because they allow for designing structures able to withstand large dynamic actions [2–6]. For this reason, studying effective and reliable structural protection systems is necessary. To upgrade the useful execution of the structure against seismic and wind powers, an appropriate configuration is performed using different vibration control equipment. One of the innovative methods of vibration control is based on the use of Passive Control Systems (PCSs). PCSs use systems that develop the control force as a response of appropriate devices, which can no longer be modified after installation, to the motion of the structure, without requiring external energy sources [7–9]. Dynamic vibration absorbers (DVAs), also called Vibration Neutralizers (VNs) or Tuned Mass Dampers (TMDs), are mechanical appendages comprising inertia, stiffness, and damping elements which, once connected to a given structure or machine, named herein the primary system, are capable of absorbing the vibratory energy at the connection point. As a result, the primary system can be protected from excessively high vibration levels. In practical applications, DVAs can be found in various configurations, intended for the attenuation of either rectilinear or angular motion. The simplest setup is that formed by a single mass attached to the primary system through a linear spring. This configuration is named the ‘undamped dynamic vibration absorber’. As will be shown later, in designing an undamped DVA to attenuate harmonic vibrations, the values of its physical parameters (stiffness and inertia) must be chosen according to the value of the excitation frequency and it is then said that the DVA is tuned. The undamped DVA may become ineffective when the excitation frequency deviates, even slightly, from the nominal tuning frequency. To provide a mechanism for energy dissipation and to enlarge the effective bandwidth of the absorber, damping can be introduced into the DVA. In most applications, a viscous damping model is used, although viscoelastic and Coulomb-type dampers can be found in certain cases. The family of TMDs is divided into four categories: conventional TMDs, pendulum TMDs (PTMDs), bi-directional TMDs (BTMDs), and Tuned Liquid Column Dampers (TLCDs). One of the first applications of TMD was the 244 m sixty-story John Hancock building in Boston in 1977 to reduce response to wind vibrations [10]. Since then, TMDS have been deployed in over 50 structures in several countries including the U.S., Japan, China, and Korea [11, 12].

2 Structural System Description In this section, the focus is on the main components of the structure considered as the case study of this work, which are essential for its proper functioning. The structural system considered as the case study is shown in Fig. 1. In particular, the CAD model of the frame structure considered as the case study of the present analysis is shown in Fig. 1(a), while its mechanical schematization is represented in Fig. 2(b). The parts considered are the main mass, the auxiliary damper-spring-mass system, and elements that realize the connection to the frame. The main mass consists of an infinitely rigid steel plate, having geometric dimensions 400 (mm) x 220 (mm) x 15 (mm), and a mass of 10.4 (kg), resting on a base consisting of four horizontal Bosch profiles and four thin vertical steel bars. The horizontal Bosch profiles are connected to the four vertical bars through corner steel elements. Bosch profiles are characterized by particularly stable grooves and large core dimensions that allow for obtaining connections with the high permissible load even forhigh dynamic and static loads. Therefore,

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Fig. 1. Case study.

the plate support is made up of Bosch profiles 45 (mm) x 45 (mm), groove = 10 (mm), A (profile surface) = 7.5 (cm2 ), and J (moment of inertia) = 13.8 (cm4 ). Moreover, the vertical steel bars have a rectangular cross-section of 1 (mm) x 35 (mm) and L (length) = 0.283 (m). The damper-spring-mass system connected to the main system is represented by an antenna-like system consisting of a thin vertical rod with a circular section with a spherical mass at the top. The auxiliary system works as Dynamic Vibration Absorber (DVA), so it is a mechanical appendage comprising inertia, stiffness, and damping elements which, once connected to the primary system, is capable of absorbing the vibratory energy at the connection points. As a result, the primary system can be protected from excessively high vibration levels. In practice, this DVA can be included in the original system design [13, 14]. Moreover, in the auxiliary system, two viscous dampers are placed in parallel with the structure. This type of viscous damper consists of a cylinder inside which a watertight piston slides. The cylinder is rigidly connected to one end of this device while the piston is rigidly connected to the other end of the same [15]. These two viscous dampers dissipate part of the mechanical energy of the auxiliary vibrating system, transforming it into heat, allowing damping of the auxiliary system vibrations and, therefore, optimizing it. Furthermore, horizontal sinusoidal stress is applied to the main mass, that is F1 (Amplitude) = 1500 (N) [16].

3 Undamped Lumped Parameter Model Without the Dynamic Vibration Absorber The purpose of this section is to evaluate the main system dynamic response without a dynamic vibration absorber. Suppose the following simplifying assumptions. The main mass m1 of the mechanical model translates between smooth guides (not represented in the figure),and thin steel bars that support the main system can be schematized as embedded beams and, therefore, similar to elastic bonds, without mass. Furthermore, the plate is considered infinitely rigid and the effect of gravity on the structure is neglected. If the plate is infinitely rigid, it is possible to schematize the basic structure, represented by four thin steel bars and the plate, as hyperstatic systems (two shelves connected by a

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pendulum, each of which is stressed by a horizontal force). The stiffness of a structure schematized in this way is known and it is, therefore, possible to assimilate each of the two structures to an equivalent spring of known stiffness [17, 18] equal to k and given by: k=

24 EI L3

(1)

where E represents the elastic modulus of the material, I denotes the area moment of inertia, and L is the length of the beam. The springs are in parallel, so their total stiffness is equal to: k12 = k1 + k2 =

48 EI L3

(2)

By using the numeric data defined in the previous section, one obtains: k12 = 1587703.6 (N /m)

(3)

Through these simplifications, it is possible to schematize the structure as a massspring system stressed by a horizontal harmonic force of amplitude F1 . Thus, using a Lagrangian approach, one obtains: m1 x¨ 1 + k12 x1 = F1 sin(ωt)

(4)

4 Undamped Lumped Parameter Model with the Dynamic Vibration Absorber This section aims to evaluate the system dynamic response with the presence of the dynamic vibration absorber. Assuming the same simplifying assumptions as defined in the previous paragraph, the overall system can be discretized into two masses denoted with m1 and m2 , where the main mass is connected to the frame by employing a spring of equivalent stiffness denoted with k12 , and the two masses are connected by a spring of stiffness denoted with k3 , and a damper with damping coefficient denoted with c1 in parallel [19]. The absolute displacements of the masses m1 and m2 are denoted by x1 and x2 . Operationally, the parameters of the dynamic vibration absorber are designed by establishing the following relations [20, 21]: ⎧ m = r m1 ⎪ ⎨ 2  ⎪ ⎩ 2 = ω =

k3 m2

⇒

k3 = m2 22

(5)

being: r = 0.05 (−), ω = 5 (rad /s)

(6)

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where ω corresponds to the angular frequency of the horizontal harmonic force acting on the main mass. Therefore, one obtains:  m2 = 0.5 (kg) (7) k3 = 12.5 (N /m) For the optimization of the absorber, one proceeds by making sure that the operating band of the dynamic absorber is as extensive and flat as possible, obtaining a non-zero but small amplification coefficient. This corresponds qualitatively to an operation in a wide frequency range, in which the amplitude of the response is not zero but small enough to realize a dynamic absorber [22, 23]. Thus, the following parameters are set:  ξ1 = 0.1  ⇒ c1 = ξ1 cc,1 = 0.5 (N · s/m) (8) cc,1 = 2 k3 m2 Considering the same horizontal harmonic stress acting on the main mass, with the

T use of the Lagrangian coordinate vector x = x1 x2 , one can obtain the equation of motion of the main structural system with the TMD. At this stage, it is possible to derive the equation of motion with the Euler-Lagrange equation. By doing so, the system equations of motion in matrix form are given by:        F1 sin(ωt) x¨ 1 x˙ 1 x1 m1 0 c1 −c1 k12 −k3 + + = (9) −c1 c1 −k3 k3 0 m2 0 x¨ 2 x˙ 2 x2 The computer implementation using SIMULINK of the complete set of the system equations of motion is shown in the block diagram represented in Fig. 2.

Fig. 2. SIMULINK block diagram of the frame structure considered as the case study.

The resulting dynamic response of the frame structure is shown in Fig. 3. In particular, Fig. 3(a) represents the displacement of the main mass without the dynamic vibration

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absorber, while the comparison between the displacements with and without the dynamic vibration absorber is shown in Fig. 3(b). In Fig. 3(b), the blue curve represents the displacement of the main mass in the presence of the DVA, whereas the red curve shown in Fig. 3(b) represents the displacement of the absorber induced by the external excitation.

Fig. 3. Dynamic response of the frame structure.

By observing and comparing the system dynamic responses shown in Figs. 3, it is apparent that the oscillations of the vibration absorber (red curve) lead to a considerable reduction of the magnitude of the displacement of the main structure (blue curve).

5 Damped Lumped Parameter Model with the Dynamic Vibration Absorber Consider the real system and the actual arrangement of the elements within the system, schematized as masses and springs in the discretized system, to validate the structure from a practical/applicative point of view. The damping, in particular, is provided through two viscous dampers physically characterized by a piston-cylinder system where the damping effect is given by the presence of a viscous fluid [24]. The ends of the two dampers are connected respectively to the second mass of the auxiliary system and the midpoint of the largest side of the rectangular plate and dampers are inclined at the same angle concerning the horizontal plane. Therefore, the geometric arrangement of the dampers allows for reproducing the configuration of an isosceles triangle. The numerical information necessary to define the geometry of the auxiliary damper-springmass system was defined through considerations on the selection of the material of the circular section bar supporting the second mass and through a process of optimization of the stiffness and damping parameters that characterize the system [25, 26]. Specifically for the realization of the circular section bar, Molybdenum was selected as material with an elastic modulus E = 18.2 (Mpa), a bar length L = 221.4 (mm), and a diameter d = 15 (mm). Based on geometric considerations, it was, therefore, possible to define the angle α = 63.6 (deg) and its complementary β = 116.4 (deg), which identify the direction of the two dampers concerning the horizontal plane. Once the geometry of the system has

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been defined, it is possible to obtain the optimized numerical value of the damping that the two dampers must have in the continuous case denoted with c and given by: c=

c1 2 cos (α) + cos2 (β)

=

c1 = 1.26 (N · m · s/rad ), γ = cos2 (α) + cos2 (β) γ (10)

Considering the same horizontal harmonic stress acting on the main mass, with the use of the Lagrangian coordinate vector defined as below, one can obtain the following equation of motion of the system with the TMD:        F1 sin(ωt) x¨ 1 x1 m1 0 γ c −γ c x˙ 1 k12 −k3 + + = (11) −k3 k3 0 m2 γc γc 0 x¨ 2 x˙ 2 x2 One can readily prove that the use of a properly defined damping factor leads to a significant improvement in the performance of the dynamic vibration absorber [27, 28].

6 Conclusion and Future Work This paper deals with the development of a virtual prototype of a dynamic vibration absorber, which is applied to a simple structural system considered as the case study for testing the performance of the system designed in this investigation. The authors already covered several areas of interest related to this work, observing the vibrational response of frame structures with multiple degrees of freedom and carrying out a systematic computational and experimental analysis in order to find system identification numerical procedures applicable to the experimental modal analysis problem associated with mechanical systems based on input-output measurements. The starting point of this work aims to optimize the results obtained by designing and introducing a dynamic vibration absorber. Moreover, this paper proposes a damping mode obtained through the use of two viscous dampers able to optimize the operation of the dynamic vibration absorber. The theoretical introduction to the construction of dynamic vibration absorbers can be defined as the first step for future virtual prototyping. Future research work will be devoted to further refining the simulation by studying the structure in its critical condition and analyzing the different damping modes with particular attention paid to dry friction damping.

References 1. De Simone, M.C., Veneziano, S., Guida, D.: Design of a non-back-drivable screw jack mechanism for the hitch lifting arms of electric-powered tractors. Actuators 11(12), 358 (2022) 2. De Simone, M.C., Celenta, G., Rivera, Z.B., Guida, D.: Mechanism design for a low-cost automatic breathing applications for developing countries. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V. NT 2022. Lecture Notes in Networks and Systems, vol. 472, pp. 345–352. Springer, Cham (2022). https://doi. org/10.1007/978-3-031-05230-9_40

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Conditions for Amorphization of Ce-Ag Alloys During Quenching from a Liquid State Tetiana V. Kalinina1(B) , Oleksandr B. Lysenko1(B) , Vladeta Jevremovi´c2(B) , Anton V. Khliebnikov1(B) , and Tetiana N. Dorozhka1(B) 1 Dniprovsk State Technical University (DSTU), Dneprostroevska Street, 2,

Dnipropetrovsk Oblast, Kamianske 51918, Ukraine {kalinina_tv,ablysenko}@ukr.net, [email protected], [email protected] 2 Academy of Professional Studies Šumadija – Department in Trstenik, Str. Radoja Krsti´ca 19, 37240 Trstenik, Serbia [email protected]

Abstract. The results of X-ray studies of the structure of Ce100-x Agx alloys (x = 5–40 at %), obtained by quenching from a liquid state (QLS) with cooling rates υ ≈ (104 − 106 ) K/s are presented. It is shown that as the process of QLS is accelerated, the structure of alloys with silver content x = 10–35 changes from a mixture of equilibrium eutectic phases (γ-Ce + CeAg) at υ < υc to amorphous at υ ≥ υc . A metastable nanocrystalline (~40 nm) phase with a body-centered cubic (BCC) lattice crystallizes polymorphically at intermediate values of υc ≤ υ ≤ υc . The peculiarities of the formation of the structure of the studied alloys depending on the cooling rate are explained in terms of the concept of TTT (temperaturetime-transformation) diagrams. Keywords: Ce-Ag alloys · quenching from a liquid state (QLS) · cooling rate · X-ray diffraction analysis · Metallic glass

1 Introduction The equilibrium course of crystallization processes is disturbed, and metastable crystalline and amorphous phases are fixed in the structure of materials as a result of rapid cooling of melts (quenching from a liquid state - QLS) [1, 2]. From the kinetic point of view, fast hardened amorphous alloys (metallic glasses are MG) are a product of the suppression of crystallization on a scale that makes it impossible to experimentally reveal the volume that has had time to crystallize. Hence it follows while studying of the problem of amorphization of materials special attention should be paid to the study of the nature and regularities of crystallization of phases formed at subcritical cooling rates of melts [3], as well as to the search for factors hindering crystallization processes under the conditions of QLS [4]. On the basis of this approach, useful information can be obtained by analyzing the influence of technological variables such as the chemical composition and the cooling rate of the melt on the structure of rapidly quenched materials. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 338–347, 2023. https://doi.org/10.1007/978-3-031-31066-9_37

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The aim of this work was to study the features of structure formation during quenching from the melt of vitrifying Ce100-x Agx alloys (x = 5–40 at %). It is shown that metastable nanocrystalline and amorphous phases are fixed in a wide concentration range of the studied alloys (x = 10–35). The actual data concerning the conditions for obtaining and details of the atomic structure of metastable phases are presented. An explanation of the interconnections between the dynamic mode of the QLS and the structure of rapidly hardened alloys is proposed.

2 Materials and Methods of Research The main criterion for choosing the alloys under study was their tendency to noncrystalline solidification under the conditions of the QLS. In this case, it was assumed that the components of the Ce-Ag system are characterized by an almost complete absence of reciprocal solubility in the solid state and interact with the formation of intermediary phases with the constant composition, i.e. chemical compounds, having different stoichiometry. Chemical compounds take part in eutectic convertings in a series of which the lowest temperature is the transformation with the participation of the γ-modification of cerium and the CeAg compound at the end stages of hardening of alloys. This transformation is characterized by the maximum value of the concentration interval between the eutectic phases x e = 50 at % Ag for Ce-Ag system, as well as a large slope (≈20K/at % Ag) of the liquidus lines near the eutectic point. As it is known, the attendance of “deep” eutectics in the phase diagrams is one of the signs of the glass-forming ability of alloys [5] which increases with increasing value of x e . An additional argument in favor of the choice of alloys of Ce-Ag system was the significant relative differences (0,20) in the atomic radii of the components. The given value agrees with the size factor of many other vitrifying compositions [6]. Ce100-x Agx alloys were smelted from cerium with a total impurity content of not more than 1 at % and clear silver in a vacuum electro furnace at a residual pressure of 6,65·10–3 Pa. Spinning of the melt was carried out by injecting a small (~100 mg) portion of the liquid alloy onto the inner surface of a rotating (up to ~6000 rpm) bronze cylinder. Foils of arbitrary shape, which were suitable for researching the structure and properties, with a thickness of 20 to 100 μm were obtained depending on the pressure of the injection gas (Ar) and the speed of rotation of the quenching block. The use of an inert gas as a transport environment, as well as the swiftness of the melt hardening process, made it possible to obtain films with clean, bright surfaces without visible signs of interaction with the elements of the air atmosphere. The rate of cooling of the melt υ in the used QLS method was determined from the thickness l of the foils using equations obtained by the authors of the paper [7] by agreement the results of the numerical solution of the thermal problem with a wide set of corresponding experimental evaluations of the value of υ: ⎧ ⎨ 8, 1 − 1, 7 lg l, for l > 100 μm lg υ = 10, 5 − 2, 9 lg l, for 20 ≤ l ≤ μm (1) ⎩ 8, 4 − 1, 3 lg l, for l < 20 μm

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The structure of rapidly hardened Ce100-x Agx alloys was studied by X-ray analysis. X-ray diffraction patterns were obtained with the help a DRON-3 diffractometer in monochromatic CuKα – radiation in the range of reflection angles 2θ from 15 to 100°. The structural type of the metastable crystalline phase of the cubic system was determined from a set of values of quadratic forms [8]. The phase composition of the initial castings, as well as the annealed FLC products, was determined by comparing the experimental values of the interplanar spaces and relative intensities of the diffraction peaks with the ASTM reference data [9] for the intermetallic compounds present in the phase diagram of Ce-Ag system. The effective sizes L of coherent scattering regions (CSR) for metastable crystalline and amorphous phases were estimated from the integral width β of the first diffraction maximum using Selyakov-Scherrer formula [8]: L = λ/(β · cos θ ),

(2)

where λ is an X-ray wavelength. The method of moments [10], which takes into account the contributions to the integral width of the analyzed diffraction maximum of the instrumental error, as well as the fraction of physical broadening associated with microdeformations of the crystal lattice, was used in order to determine more correct values of the size factor for the metastable BCC phase. For rapidly hardened amorphous alloys, along with the effective sizes of CSR, one more parameter of the fine structure of MG was calculated, that is the value of the smallest interatomic distance. Ehrenfest equations [11] was used for this purpose: d0 = 0, 615 · λ/ sin θ1 .

(3)

3 Research Results The effect of the chemical composition and rate of rapid quenching on the structure of Ce100-x Agx alloys, which in terms of content are located in the vicinity of the lowtemperature eutectic (x e = 18%; T e = 783 K), was studied to achieve the goal of the work. The components of this eutectic are the γ-modification of cerium and the equiatomic chemical compound CeAg according to the phase diagram of Ce-Ag system [12]. Equilibrium eutectic phases are revealed in X-ray diffraction patterns of cast alloys and QLS samples with thickness of l ≥ 150 μm, the cooling rate υ of which did not exceed ~2,5·104 K/s (Fig. 1a).

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As the quenching from the liquid state accelerates, intensity maxima which cannot be attributed to any of the equilibrium phases of Ce-Ag system appear on the diffraction patterns of rapidly hardened films.

Fig. 1. X-ray diffraction patterns of rapidly quenched Ce82 Ag18 alloy foils obtained with different cooling rates, K/s: 2·104 (a); 7·104 (b); 105 (c); 5·105 (d). ▲ – γ-Ce;  - CeAg; ● – metastable BCC phase

It is established that unidentifiable diffraction maxima disappear upon subsequent heating of the foils to 673 K. The presented actual data testify to the formation of a metastable crystalline phase in the structure of the alloys under study. It is established that this phase has a body-centered cubic (BCC) lattice. Its relative amount increases with an increase in the cooling rate, as a result of which, upon reaching a certain critical value υ c , the BBC phase is fixed in the structure of rapidly quenched foils in its pure form (Fig. 1b). The possibility of obtaining a single-phase structure indicates that the metastable BCC phase is formed without changing the initial composition of the alloy. According to the values of the lattice period of the BCC phase, its specific atomic volume VaBCC , which was compared with the linear concentration dependence V a (x) built from the crystallographic parameters of the components and equilibrium intermediate phases of Ce-Ag system, was calculated in order to quantitatively confirm the latter conclusion.

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Fig. 2. Concentration dependences of the specific atomic volumes of the equilibrium phases of Ce-Ag system (straight line) and the metastable BCC phase (points)

As can be seen from Fig. 2, there is a satisfactory agreement between the experimental (points) and calculated (straight line) data in the entire concentration range of detection of the metastable BCC phase (x = 10–35). Hence it follows that the metastable BCC phase has a wide region of homogeneity and crystallizes polymorphically at quenching from the liquid state while maintaining the concentration of alloys. In view of the foregoing, we can conclude that the critical parameter υ c has the meaning at the cooling rate at which the processes of diffusion separation of components, which are necessary for the formation of a mixture of eutectic phases, are suppressed. Under these conditions, the crystallization of alloys is carried out in a kinetically more favorable way, that is, it is accompanied by the formation of a metastable BBC phase of the initial composition. X-ray estimates of the effective grain sizes of the BBC phase obtained from the integral width of the diffraction maximum (110) using comparison (2) for rapidly quenched alloys of Ce82 Ag18 foil with a thickness of l≈60 μm, approximately is 25 nm. The refined values determined by the method of moments [10] are higher (L BCC ≈40nm). Nevertheless, these values are significantly inferior to the grain size typical for microscale structures of rapidly quenched materials [13]. The last result leads to the conclusion that the metastable BCC phase fixed in QLS foils has a nanocrystalline structure. The formation of a nanocrystal structure requires a high nucleation rate and an extremely high low growth rate reached with deep supercooling of the melt. Such conditions are very rare in experiments on the quenching from a liquid state. Therefore, there are only a few reports, for example, [14], about the formation of nanosized structures in the process of rapid cooling of the melt. Firstly partial (Fig. 1c), and then (at υ ≥ υc ) complete (Fig. 1d) suppression of crystallization of the BCC phase is observed with a further increase in the rate of fast quenching in relation to the value υ c . An experimentally fixed sign of these processes is the appearance in the X-ray scattering patterns of diffuse intensity maxima characteristic of amorphous materials. As can be seen from Fig. 1d, the X-ray diffraction pattern of the rapidly quenched amorphous Ce82 Ag18 alloy contains only three strongly smeared

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maxima located in the range of the values of sin θ/λ from 1 to 5 nm−1 . The diffraction pattern shown in Fig. 1d correlates with the X-ray diffraction patterns of metallic glasses of other types according to a number of characteristic features (the mutual arrangement of the first two maxima, the presence of a “shoulder” on the descending branch of the second maximum, and the degree of diffuseness). Using the Selyakov-Scherrer (2) and Ehrenfest (3) equations, the dimensions of the coherent scattering regions L and the values of the shortest interatomic distances d 0 for Ce82 Ag18 amorphous alloy were estimated from the integral width β and the angular coordinate of the first diffuse halo θ1 . According to the results of five independent calculations performed by processing various diffraction patterns, the following values of the analyzed parameters were obtained: L = 1,82 ± 0,03 nm; d 0 = 0,347 ± 0,001 nm. Analyzing the presented calculated data, it should be noted that the effective BCC sizes are consistent with the maximum estimates of the value of L published in the literature for metallic glasses of different types. As for the parameter d 0 its value practically coincides with a similar characteristic obtained by linear interpolation of the atomic diameters of the components taking into account their relative amount in the alloy under study. This means that the formation of an amorphous structure during quenching from a liquid state of Ce100-x Agx alloys is not accompanied by a significant change in the distances between the nearest atoms in comparison with close-packed crystalline phases. Thus, according to the mentioned parameters of X-ray diffraction patterns, a structure typical of metallic glasses is formed in rapidly quenched foils of Ce82 Ag18 alloy obtained at a cooling rate υ ≥ υc . Hence, it follows that the upper threshold value of the QLS rate υc corresponds to the cooling mode in which the physical prerequisites for the realization of the process of polymorphic crystallization of the metastable BCC phase disappear and the amorphous state of the alloy is fixed. The features of structure formation under conditions of rapid quenching discussed above on the example of the Ce82 Ag18 eutectic alloy are also reproduced in alloys of pre- and hypereutectic compositions belonging to the concentration range (10–35)% Ag. The experimentally observed successive changes in the phase composition of Ce100-x Agx alloys depending on the rate of QLS can be represented as the following scheme:

Fig. 3. Change in the phase composition of Ce100-x Agx alloys (x = 10–35) with an increase in the rate of quenching from a liquid state

Commenting on Fig. 3, it should be noted that the amorphous state (the structure of metallic glass) is fixed as a result of the suppression of crystallization not only of a mixture of equilibrium eutectic phases (γ-Ce + CeAg), but also of the metastable BCC phase which is formed without changing the alloy composition in the range of cooling rates υc − υc .

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Table 1 shows the values of the critical rates of rapid quenching υc and υc for alloys with different silver content. It can be seen that the smallest values of the analyzed parameters (υc ≈5·104 K/s; υc ≈4·105 K/s) limiting the dynamic range of formation of the metastable BCC phase are inherent in alloys located in the immediate vicinity (16– 20% Ag) of the eutectic point (18% Ag). However, the values of υc and υc get closer at the boundaries of the studied concentration range (10–35)% Ag tending to a level of ~ 5·107 K/s which corresponds to the maximum cooling rates achieved using the QLS technique used in the work. Table 1. Conditions for the formation of a metastable BCC phase in rapidly quenched alloys Ce100-x Agx x

Critical rate of rapid quenching, K/s υc

υc

10–12

107

> 3·107

16–20

5·104

4·105

25–28

2·105

107

30–35

8·106

> 3·107

4 Discussion of the Results We will discuss the features of the structure formation of Ce100-x Agx alloys (x = 10–35) during quenching from a liquid state with different cooling rates using a hypothetical “temperature-time-transformation” (TTT) diagram in the final part of the work. This approach allows us to graphically illustrate the relationship between temperature, kinetic, and dynamic factors during solidification of melts under nonequilibrium conditions of rapid quenching. Figure 4 shows a TTT diagram for the alloys under study. It consists of two pairs of C-shaped curves located in the temperature range T m – T g , where T m and T g are the melting and glass transition temperatures of the alloy, respectively. Curves 1, 1’ describe the kinetics of crystallization of a liquid solution (L) with the formation of a mixture of equilibrium eutectic phases. In this case, curve 1 corresponds to the beginning, and curve 1’ corresponds to the end of the L → γ-Ce + CeAg transformation. Curves 2 and 2’, respectively, have the meaning of the beginning and end of crystallization of the metastable BCC phase. The mutual arrangement of curves 1, 1’ and 2, 2’ was set based on the results of experimental studies according to which the crystallization of the metastable BCC phase, firstly, is a kinetically more favorable process, i.e. characterized by a higher rate, and, secondly, occurs at deeper supercooling of the melt in comparison with the formation of a mixture of equilibrium eutectic phases. In view of the foregoing, C-curves 2, 2’ in Fig. 4 are shifted to the left and down in relation to curves 1, 1’.

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Fig. 4. Hypothetical TTT diagram for Ce100-x Agx alloys (x = 10–35) prone to the formation of metastable crystalline (BCC) and amorphous phases while quenching from a liquid state

It also shows the schemes of cooling curves with different rates which provide experimentally fixed structures including combinations of equilibrium and metastable crystalline phases, as well as metastable crystalline and amorphous phases. As follows from Fig. 4, the crystallization of the melt proceeds in accordance with the phase diagram of the Ce-Ag system and ends on line 1’ with the formation of a eutectic mixture of γ-Ce crystals and CeAg compound at a relatively low cooling rate υ 1 . If, however, only a certain volume fraction of the parent liquid phase crystallizes at the stage of formation of a mixture of equilibrium phases (regime υ 2 in Fig. 4), then the remaining part of the melt at lower temperatures (between lines 2 and 2’) turns into a metastable BCC phase. In this case a heterophase structure is formed the elements of which are equilibrium (γ-Ce, CeAg) and metastable (BCC) phases. An increase in the liquid solution cooling rate to values υc < υ < υc leads to the fact that the formation of a mixture of equilibrium phases, which requires a significant redistribution of components, is a less competitive process in comparison with the polymorphic crystallization of the metastable BCC phase. According to Fig. 4, the BCC phase is formed during deep supercooling of the melt that provides a combination of high nucleation rates and low crystal growth rates, which is necessary for the formation of the experimentally observed nanocrystalline structure. There are such dynamic regimes of rapid quenching are possible in the considered range of values υ at which the crystallization of the BCC phase is not completed. In this case, the non-crystallized part of the melt cools below the glass transition temperature T g and solidifies with the formation of an amorphous structure. A similar cooling regime in Fig. 4 is shown by the curve υ 3 , and the X-ray diffraction pattern corresponding to the amorphous-crystalline state is shown in Fig. 1c.

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The cooling curves do not intersect with the kinetic diagrams 1 and 2 in the case of using the extreme regimes of the QLS (υ ≥ υc ), which indicates the suppression of the crystallization of both the equilibrium and metastable phases. Under these conditions, a structure is fixed without X-ray signs of crystallinity (Fig. 1d), which is typical for metallic glasses. The results of the studies carried out indicate that the use of a TTT diagram as a tool for analyzing phase transformations under QLS conditions makes it possible to explain all the X-ray diffraction features of the structure of rapidly quenched Ce-Ag alloys with a silver content of 10 to 35 at %. In this case, not only a complete picture of the structure formation of alloys depending on the cooling rate is recreated, but it is also possible to predict the grain sizes of the metastable BCC phase.

5 Conclusions 1. X-ray studies of the structure of vitrificating Ce100-x Agx alloys (x = 5–40 at %) obtained by rapid cooling of thin layers of the melt on the inner surface of a rotating cylindrical heat sink have been performed. 2. It is shown that with an increase in the rate of quenching from a liquid state, the structure of alloys with a silver content of 10–35 at % changes from a mixture of equilibrium eutectic phases (at υ < υ c ) to amorphous (at υ ≥ υc ). The metastable nanocrystalline (~40 nm) CSR phase crystallizes polymorphically at intermediate values υc ≤ υ < υc . 3. The parameters of the fine structure of rapidly quenched amorphous Ce100-x Agx alloys were determined from the details of the X-ray diffraction pattern. A close correlation of CSR sizes with similar characteristics of metallic glasses of other types has been established. It is shown that non-crystalline solidification of melts is not accompanied by a significant change in the shortest interatomic distances in comparison with close-packed crystalline phases. 4. Features of the structure formation of Ce100-x Agx alloys (x = 10–35) depending on the rate of quenching from a liquid state, as well as all the nuances of the structure of rapidly quenched foils revealed by X-ray diffraction are explained using a hypothetical TTT diagram.

References 1. Warlimont, H.: Amorphous metals driving materials and process innovations. Mater. Sci. Eng. A. 304–306, 61–67 (2001) 2. Filonov, M.R., Anikin, Yu., A., Levin, Yu., B.: Theoretical basis of the production of amorphous and nanocrystalline alloys by the superfast quenching method. MISIS, 328 p., (2006) 3. Lysenko, A.B., Zagorulko, I.V., Kalinina, T.V., Lysenko, A.A.: Formation of metastable nanocrystalline phases in alloys of light rare earth elements with silver. Nanostruct. Mater. Sci. №1, -pp. 58–68 (2015) 4. Lysenko, A.B, Kravets, O.L., Lysenko, A.A.: Kinetic criteria for the tendency of metallic melts to amorphized. Metallophys. Latest Technol. 31(10), 311–1320 (2009)

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5. Chen, H.S.: Glassy metals. Rep. Progress Phys. 43, 353–432 (1980) 6. Miracle, D.B., Sanders, W.S., Senkov, O.N.: The influence of efficient atomic packing on the constitution of metallic glasses. Philos. Mag. 83(20), 2409–2428 (2003) 7. Lysenko, A.B., Borisova, G.V., Kravets, O.L.: Calculation of the cooling rate during quenching of alloys from the liquid state. Phys. Technol. Narrow Pressures. 14(1),.44–53 (2004) 8. Gorelyk, S.S., Skakov, Yu.,A., Rastorguev, L.N.: Roentgenographic and electron optical analysis. MISIS, 368 p. (2002) 9. Diffraction Data File. ASTM. Philadelphia (1969) 10. Tsybulya, S.V., Cherepanova, S.V.: Introduction to the structural analysis of nanocrystals. Textbook, Novosibirsk, 92 p. (2008) 11. Skryshevsky, A.F.: Structural analysis of liquids and amorphous alloys. Higher School, 327 p. (1980) 12. Delfino, S., Ferro, R., Capelli, R., Borsese, A.: Phase equilibria in the silver-cerium system. J. Less-Common Metals. 41. 59–64 (1975) 13. Vogt, E., Frommeyer, G.: Solidification parameters and microstructures of rapidly solidified Fe-Si and Fe-C melt-spun ribbons. Z. Metallkunde. 78(4), 262–267 (1987) 14. Bakonyi, I., Cziraki, A.: Nanocrystalline-forming ability of alloys by melt-quenching. Nanostruct. Mater. 11(1), 9–16 (1999)

System Identification of a Nonlinear One-Degree-of-Freedom Vibrating System ˙Ipek Lök1 , Carmine Maria Pappalardo2(B) , Rosario La Regina3 , Sefika ¸ and Levent Malgaca4 1 Department of Mechatronics Engineering, The Graduate School of Natural and Applied

Sciences, DokuzEylul University, ˙Izmir, Türkiye 2 Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy [email protected] 3 MEID4 Academic Spin-Off of the University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy 4 Department of Mechanical Engineering, DokuzEylul University, Izmir, Türkiye

Abstract. In this paper, the modeling of a nonlinear one-degree-of-freedom mechanical system is investigated with nonlinear system identification methods. To this end, a nonlinear mechanical system with a cubic law for its stiffness characteristics is formulated using MATLAB/SIMULINK software. To identify the nonlinear properties of the mechanical system at hand, the Nonlinear ARX model is studied as the identification method. The nonlinear ARX model consists of linear and nonlinear output functions. More specifically, Feed Forward Network and Sigmoid Network functions are studied as nonlinear output functions of the Nonlinear ARX model to investigate the nonlinear dynamics of the mechanical system of interest. Numerical experiments show that the nonlinear mathematical models of the mechanical system are identified successfully. Keywords: Nonlinear mechanical system · System identification · Nonlinear ARX model

1 Introduction In engineering applications, the study of the dynamic behavior of linear and nonlinear mechanical systems represents an important field of research. Several theories in literature are proposed for modeling mechanical systems, beams, and manipulators. The system identification approaches have more advantages than other modeling techniques. The analysis time of identification approaches is shorter, and the identification process is not affected by the complexity and order of the system. When using the system identification approach, there are various identification models such as linear models, nonlinear models, time-domain models, and frequency-domain models. In particular, the Nonlinear ARX modeling approach is generally used in the literature for the investigation of the nonlinear dynamical behavior of the nonlinear mechanical system [1, 2]. A short literature review is summarized below about the identification of mechanical systems, beams, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 348–355, 2023. https://doi.org/10.1007/978-3-031-31066-9_38

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and manipulators using linear and nonlinear identification methods. Malgaca et al. studied the modeling of a 5-DOF half vehicle model and single-link flexible manipulators with the identification methods [3–5]. Pappalardo et al. investigated the identification of a latching mechanism of an aircraft hatch door, and the modeling and nonlinear control of a pantograph scissor lift mechanism [6–8]. In [9], the identification of a forced Duffing oscillator is investigated using a deep learning model with six layers of cascaded feedforward nets. In [10], mathematical models of a single-link manipulator are estimated with Linear ARX and Nonlinear ARX models to investigate the nonlinear behavior of the manipulator. A Steward platform manipulator is identified with the Nonlinear ARX model using a Wavelet Network nonlinear output function in [11]. A modified BoucWen mechanical system is modeled to investigate the forward and inverse dynamical behavior of a magnetorheological damper with the Nonlinear ARX model in [12]. The large number of research papers found in the literature about the various applications of applied system identification methods testify to the importance of this topic in the vast field of mechanical and industrial engineering [13–17]. For instance, one of the emerging sectors in which the use of system identification methods seems to be promising is precision agriculture [18–22], which is constantly evolving towards innovative solutions based on autonomous vehicles, collaborative robotic manipulators, and smart control systems [23–25]. When using the methods of applied system identification in engineering applications [26–28], one of the main challenges is to understand if the identified model effectively is able to reproduce the dynamic behavior of the system of interest in realistic conditions, different from the test cases used to obtain the model, instead of simply memorizing the pattern behind the input-output datasets employed to perform the analysis [29–32].

2 Benchmark Problem In this section, a single-degree-of-freedom nonlinear mechanical system with a nonlinear cubic spring model is considered as the case study and explained in detail. To this end, the nonlinear mechanical system is shown in Fig. 1.

Fig. 1. Nonlinear mechanical system.

In Fig. 1, m represents the mass of the mechanical system, k and knl respectively denote the stiffness of the linear and nonlinear cubic spring models, whereas c represents the coefficient of the damper. The displacement of the point mass of the considered mechanical system is denoted with x ≡ x(t), the velocity of the point mass is denoted

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with x˙ ≡ x˙ (t), and the acceleration of the point mass is denoted with x¨ ≡ x¨ (t). The force generated by the nonlinear cubic spring model is denoted with Fknl and is given by: Fknl = −knl x3

(1)

The equation of motion of the mechanical system can be written using the D’Alembert’s principle, which considers the forces of all the components of the mechanical system, as follows: Fi + Fk + Fknl + Fc + Ff = 0

(2)

where Fi = −mx¨ represents the inertia force, Fk = −kx denotes the linear elastic force, Fknl = −knl x3 denotes the nonlinear elastic force, Fc = −c˙x represents the force generated by the damper, and Ff = f is the applied input force of the system. The equation of the motion of the mechanical system can be written as follows: m¨x(t) + c˙x(t) + kx(t) + knl x3 (t) = f(t)

(3)

In the numerical analysis, the following set of initial conditions is considered:  x(0) = x0 (4) x˙ (0) = v0 where x0 and v0 represent initial displacement and initial velocity of the point mass, respectively. The numerical parameters of the nonlinear mechanical system used in the numerical analysis are given in Table 1. The numerical dataset of the mechanical system is obtained with the use of the classical fourth-order Runge-Kutta method. Table 1. Numerical parameters of the mechanical system. Description

Symbols

Data (Units)

System mass

m

3 (kg)

Linear stiffness

k

1.1 (kg s-2)

Cubic stiffness

knl

1.1 (kg s-1)

Damper coefficient

c

1 (kg s-1)

Initial displacement

x0

0 (m)

Initial velocity

v0

0 (m s-1)

3 Simulation Methods In this section, the Nonlinear ARX model used to model the nonlinear mechanical system is described. The nonlinear ARX model is an extended version of the linear ARX

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model, which is used to identify the nonlinear effects of dynamic systems [1, 2]. A nonlinear ARX model contains regressors and output functions. The regressors are a set of regressors combination of linear, polynomial, and custom regressors. The Sigmoid Network, the Feed Forward Network, the Wavelet Network, the Custom Network, and the Gaussian Process as the nonlinear output function are used in the Nonlinear ARX model. The output function consists of a linear function, a nonlinear function, and an offset term. The block diagram of the Nonlinear ARX model is shown in Fig. 2.

Fig. 2. The block diagram of the Nonlinear ARX model.

The Linear function of the model is given as follows: y(t) = y0 + X(t)T PL

(5)

where y0 , X(t), P, and L represent respectively the output offset, the vector of regressors with dimensions m x 1, the projection matrix with dimensions m x j, and the vector of weights with dimensions p x 1, where m and p denote the number of regressors and the number of linear weights, respectively. When the linear function is used with the linear regression and without the nonlinear output function, the model is basically a Linear ARX model [1, 2]. The Sigmoid Network output function uses an iterative search technique for estimating parameters. The equation of the Sigmoid Network is given by: y(t) = y0 + X(t)T PL + S(X(t))

(6)

being: S(X) =

n 

  si f XT Qbi + ci

(7)

i=1

where Q represents a projection matrix with dimensions m x q, si is a generic output coefficient, bi is a generic dilation coefficient, and ci is a generic translation coefficient. The Feed Forward Networkoutput function uses a neural network function for a nonlinear mapping object in Nonlinear ARX model [1, 2].

4 Results and Discussion In this section, the identification results of the nonlinear mechanical system are discussed. For this purpose, a comparison of the vibration responses of the nonlinear mechanical

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system and the identified mathematical models with the Sigmoid Network and Feed Forward Network nonlinear functions is shown in Fig. 3.

(a)Numerical and Nonlinear ARX-1 results for the identification dataset.

(b) Numerical and Nonlinear ARX-2 results for the identification dataset.

(a)Numerical and Nonlinear ARX-1 results for the validation dataset.

(b) Numerical and Nonlinear ARX-2 results for the validation dataset.

Fig. 3. Comparison of the vibration responses obtained from the nonlinear mechanical system and the mathematical models identified by using the Nonlinear ARX model.

In Fig. 3, the label Nonlinear ARX-1 describes the Nonlinear ARX model with the Sigmoid Network Function, while the label Nonlinear ARX-2 describes the Nonlinear ARX model with the Feed Forward Network function. By observing the numerical results shown in Fig. 3, it is apparent that the identified vibration responses successfully match the vibration response of the nonlinear mechanical system. The fit value and RMS value are calculated for two identified models are given as follows:   n 1  yi2 (8) RMS =  n i=1

and

fit = 100 1 −



y − yˆ

y − mean(y)

 (9)

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where n is the number of samples and yi is the samples of a vibration signal, whereas y and y denote the numerical data and the identified data, respectively. The numerical results of the system identification applied to the nonlinear mechanical system considered as the benchmark problem of this work are reported in Table 2. For the Nonlinear ARX-1 and Nonlinear ARX-2 models, it is shown in Table 2 that the fit values are equal to 94.30 (%) and 99.67 (%), respectively. The numerator and denominator orders are selected as 2 for both models. According to the fit values, the best estimation is achieved by the Nonlinear ARX model with the Sigmoid Network function, which exhibits a 99.67 (%) performance index [33, 34].

Table 2. Numerical results of nonlinear mechanical system considered as the case study. Identification Fit (%) Numerical

-

Validation RMS 1.5307

Fit (%) -

RMS 1.3902

Nonlinear ARX-1

94.3018

1.5374

91.7795

1.3951

Nonlinear ARX-2

99.669

1.5305

99.4708

1.3886

5 Conclusions This paper is part of a wider research plan focused on the connections between multibody system dynamics, nonlinear optimal control, and applied system identification. In particular, in this work, the nonlinear dynamic behavior of a one-degree-of-freedom mechanical system with a cubic law for its stiffness characteristic is investigated with the Nonlinear ARX model. The numerical solution of the nonlinear mechanical system is studied using the classical Runge-Kutta method to obtain a numerical dataset for the nonlinear system. Different nonlinear output functions are studied to identify the nonlinear mechanical system. According to numerical results, the mathematical model of the mechanical system is successfully estimated using the Nonlinear ARX model with the Sigmoid Network function and Feed Forward function. The authors plan the identification of a nonlinear two-degree-of-freedom mechanical system in future works.

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Multibody Modeling of a Serial Manipulator for In-Space Applications Salvio Veneziano1 and Marco Claudio De Simone2(B) 1 MEID4 Academic Spin-Off of the University of Salerno, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy 2 Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy [email protected]

Abstract. Launching satellites into orbit presents insurmountable constraints related to the cost directly proportional to the weight of the cargo and the volume it occupies. In-orbit assembly or in-space fabrication (ISM) itself is a possible solution to these problems, involving the production of artifacts in low Earth orbit (LEO) through various manufacturing processes suited to microgravity conditions. A small robotic island would reduce the problem of sending the necessary instrumentation and raw materials for production. This makes it possible to manufacture various products from small satellites to large structures. One possible configuration is the combination of additive manufacturing and robotics, using a 3D printer for the production of semi-finished products and a robotic arm for their handling and assembly, respectively. The present work focuses on the preliminary study of a serial manipulator for use within a robotic platform for in-orbit assembly of CubeSat nanosatellites. The objective is to model the robotic island in a multi-body SimScape environment and analyze the kinematic and dynamic behavior of the manipulator by planning trajectories for the main steps of the fabrication process. Keywords: multi-body · serial manipulator · SimScape · dynamic · motion laws

1 Introduction In recent years, in-space manufacturing, or the set of activities related to manufacturing and robotic assembly in space, has emerged as an important solution to address the problem related to payload and cost per single trip. The idea is to launch into orbit a kit consisting of a 3D printer and robots capable of working together to build small satellites in low Earth orbit. Such would reduce the ratio given by the cargo volume and the launch cost. At an early stage, a preliminary study was carried out to address the basic principles of robotics related to manipulator modeling and trajectory planning. Defined the mechanical structure, attention was placed on the central part of the study, which focused on a careful kinematic and dynamic analysis of a SCARA manipulator used for Low Earth Orbit (LEO) assembly of CubeSat-type nano-satellites with TRL © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 356–364, 2023. https://doi.org/10.1007/978-3-031-31066-9_39

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2 (Technology Readiness Level). In particular, differential kinematic analysis was performed to calculate the relationships between the velocities of the joint variables and the corresponding linear and angular velocities of the end organ through the Jacobian transformation matrix. The study aims to simulate in the SIMULINK environment the behavior of a multibody model of an in-space facility equipped with SCARA manipulator to evaluate attitude control issues.

2 Materials and Methods The standard that defines an industrial robot is the ISO TR/8373-2.3, which defines it as “a manipulator with multiple degrees of freedom, automatically governed, reprogrammable, multi-purpose that can be fixed-mounted or mobile for use in industrial automation.” The mechanical structure of a robot manipulator consists of a series of arms (or links), assumed to be rigid bodies, interconnected through joints (or joints) that are intended to set in motion the end effector appropriately for the performance of an assigned task [1]. The type of joints and their disposition will affect the position limits of the end effector. Another important parameter that defines a manipulator is the load capacity that depends on the power of the installed motors, which affects the speed of the movements [2, 3]. Specifically, this study focuses on SCARA manipulators designed for precision assembly. This makes them suitable for handling many tasks with speed unthinkable for an anthropomorphic manipulator. The reason why attention has dwelt on these robots is the advantages that these robots have. In particular: minimal size and weight, low purchase cost, and minimal maintenance due to the simplicity of the structure [4]. The versatility of SCARA manipulators means that they can be installed either singly or in pairs with other manipulators of the same or different types and operate either in stations with fixed or mobile workstations, such as rotary tables or conveyor belts [5]. The objective of the study is to evaluate the feasibility of using a tiny robotic island, consisting of a 3D printer and a SCARA-type serial manipulator, for the production and assembly in Low Earth Orbit (LEO) of CubeSat-type nano-satellites with TRL 2 (Technology Readiness Level) [6]. For purposes of the study, the use of the kinematics of a SCARA manipulator was found to be valid. The mechanical structure of a SCARA robot consists of two rigid links connected by rotoidal joints that allow translations in the x-y plane (within the workspace) of the end organ (see Fig. 1a). In the vicinity of the latter are two other joints, a prismatic one that allows translation along the vertical z-axis and a rotoidal one that allows rotation around the same axis [7]. Each joint is associated with a degree of freedom that constitutes a joint variable. In SCARA-type (4-axis) manipulators, there are thus 3 rotoidal and 1 prismatic joint to which 4 degrees of freedom correspond. Topologically, the SCARA robot has an RRPR-type structure, referring to the type of joints present, as underlined in Fig. 1b [8].

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Fig. 1. a) SCARA robot scheme description and b) topological diagram of the manipulator

3 Mathematical Model and Numerical Activity The kinematic model of a manipulator robot is a description of the correlation between the positions of the joints (qj , θj ) and the corresponding pose of a particular member; usually, the end effector, described concerning a Cartesian coordinate system (xe , ye , ze , θe ). To define the position of a point P of the body, the homogeneous transformation matrix can be used, which binds the coordinates of the same point to two different reference systems, i.e., the absolute frame and the local body frame [9]. Having defined a reference frame(base frame) Ob xb yb zb , the direct kinematics function is given by the homogeneous transformation matrix:  b  ne (q) seb (q) aeb (q) peb (q) b Te (q) = 0 0 0 1 where q is the vector (nx1) of joint variables, ne , se , ae are the verses of a local frame of the end-effector. In detail: – ne versor normal to the following ones; – se sliding versor; – ae approach versor, coincident with the direction of approach to the object. The matrix in compact form can be rewritten as follows:  b  Re (3 × 3) peb (3 × 1) b Te (q) = 0 (1 × 3) 1(1 × 1) where: Rbe of size (3 × 3) represents the orientation of the end-effector with respect to the base frame; peb of size (3 × 1) is the vector identifying its position with respect to the same triad; 0 is the vector representing a perspective transformation that is equal to 0 for manipulator arms; 1 is a scaling operator (see Fig. 2).

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Fig. 2. Position and orientation of the end-effector in space

If, on the other hand, an open-chain manipulator having n arms is considered, the overall coordinate transformation describing the position and orientation of the n-th triad with respect to the triad integral to link 0 can be written as the product of the homogeneous transformation matrices: Tn0 (q) = A10 A21 · · · Ann−1 The equation applied to the end-effector to detect its position relative to the base triad is equal to: Teb (q) = T0b Tn0 Ten where T b1 and T ne are the transformations describing, respectively, the position and orientation of the arm local frame 0 with respect to the base tern and the end-effector tern with respect to the n frame [10].For the Denavit-Hartenberg convention, as reported in Fig. 3, the parameters that need to be determined are the following: aj link length measurement; d j translation offset; α j torsion angle θ j joint angle between two consecutive arms

Fig. 3. Denavit-Hartenberg Convention

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The parameters that need to be determined are: aj link length measurement; d j translation offset; α j torsion angle θ j joint angle between two consecutive arms The parameters referred to the SCARA manipulator model are illustrated in Table 1: Table 1. SCARA manipulator model parameters Link i

Link length ai

Link offset di

Joint angle θi

Link twist αi

1

l1

0

θ1

0

2

l1

0

θ2

0

3

0

d3

0

0

4

0

0

θ4

0

It can be seen from the parameters that aj , αj and dj are constant and dependent on the robot geometry. The rotation θj is variable and measures the relative rotation between link i and link i - 1. For a prismatic joint, on the contrary, the parameter dj is variable and represents the translation between two adjacent joints [11, 12]. The characteristic dimensions of the manipulator under consideration are: d0 = 160 mm, l 1 = 350 mm, l2 = 300 mm, d3 = ±210◦ , θ 1 = ±148◦ , θ2 = ±150◦ and θ4 = ±360◦ . Homogeneous matrices related to each pair of consecutive arms, dependent on the respective joint variable, are calculated.The transformation matrix expressing the position and orientation of frame 4 with respect to triplet 0 is given by: T40 (q) = A01 (θ1 )A12 (θ2 )A23 (d3 )A34 (θ4 ) The overall transformation that binds the position and orientation of the tool backhoe relative to the base is: Teb (q) = T0b T40 Ten Substituting everything, we arrive at the following formula: ⎤ −sin(θ1 + θ2 + θ4 ) cos(θ1 + θ2 + θ4 ) 0 a1 cos(θ1 ) + a2 cos(θ1 + θ2 ) ⎢ cos(θ1 + θ2 + θ4 ) sin(θ1 + θ2 + θ4 ) 0 a1 sin(θ1 ) + a2 sin(θ1 + θ2 ) ⎥ ⎥ Teb (q) = ⎢ ⎦ ⎣ 0 0 −1 d0 + d3 0 0 0 1 ⎡

Finally, it is possible to write the direct kinematics equation, which allows the variables in the operational space, in which the manipulator works, to be calculated from the variables in the joint space: xe = k(q)

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T

with q = θ1 θ2 d3 θ4 vector of joint variables, defined in joint space, with n = 4 equal to the minimum number of mutually independent parameters [13–15]. ⎡ ⎤ ⎡ ⎤ px a1 cos(θ1 ) + a2 cos(θ1 + θ2 )   ⎢ py ⎥ ⎢ a1 sin(θ1 ) + a2 sin(θ1 + θ2 ) ⎥ pe ⎥ ⎢ ⎥ =⎢ xe = ⎣ pz ⎦ = ⎣ ⎦ d0 + d3 ∅e ∅e θ1 + θ2 + θ4 Inverse dynamics allows joint variables to be determined known the position of the end effector, so that having assigned a desired trajectory, it is possible to define the motion to be assigned in joint space [16]. The goal would be to determine the joint pose of the end-effector, specifically the initial variables θ1 , θ2 , θ3 , θ4 for an assigned  ones q(t=0) = θ1,0 θ2,0 θ3,0 θ4,0 . By making geometrical considerations, it can be P seen that θ1 = α ± β with α = tan−1 Pyx . Having derived the initial configuration from the inverse kinematics, we define the path the manipulator must follow to do its work in space [17–19]. The basic problem is to move the end-effector along an assigned path by passing through a sequence of intermediate positions and orientations or by specifying only the initial position to a desired position(point-to-point motion), that is, to move the tool triad from its current value Pj to the desired final value Pf .

Fig. 4. Trajectory of the end-effector in three-dimensional operational space

The model was implemented in MathWorks’ SimScape multi-domain simulation environment [20, 21]. Several simulations were conducted by varying the laws of motion used to move the end-effector. This paper reports the analyses performed on the model employing trapezoidal velocity profiles that, in a simple manner, replicate the dynamics of an electromechanical actuator [22]. Figure 4 shows the trajectory of the end-effector in three-dimensional operational space. The results of kinematic analysis first and dynamic analysis later allowed us to estimate the torques required for the individual actuators to make the end effector carry out these trajectories and to evaluatethe reactions constrained to the base of the manipulator base frame [23]. For simulation purposes, it is necessary to know all the variables related to displacements, velocities, and accelerations and their time trends with reference to each joint. A second-order kinematic inversion algorithm was implemented to compute the joint variable trend known as the trajectory of the end-effector in the operational space.

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4 Results and Discussions From the reverse dynamics simulation, it was possible to estimate the torques required at the manipulator’s joints, even under microgravity conditions, to be used as input data for the direct dynamics. From the simulations, the torques that each actuator must be able to develop turn out to be much lower than those needed on the ground. This information is helpful at the manipulator design stage by giving the possibility of fitting drives optimized for the purpose. Among the analyses performed is the detection of forces and torques measured at the base of the manipulator and transferred to the platform and the calculation of the displacements to which the latter would be subjected if it were not rigidly fixed. This analysis is critical if the platform is found to operate installed on a gateway or orbiting vehicle of modest size and mass. To perform the analyses under such conditions, the microgravity condition was modeled. The results in Fig. 5 report forces and reaction torques at the manipulator’s base. Such information is essential to emulate the dynamics of the satellite in orbit with its attitude controller. As can be guessed from the system’s response, it is essential to define the right time law to minimize inertial actions and make the attitude controller’s work less onerous.

Fig. 5. Forces and reaction torques at the base of the manipulator generated during processing

5 Conclusion This study discussed the kinematic and dynamic aspects of a SCARA-type serial manipulator that is thought to work in orbit. The ultimate goal is to use the manipulator to

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move parts and spares of CUBESAT-type nano-satellites with TRL 2 output from a 3D printer to downsize the carrier payload by lowering launch costs. In the study of inverse and direct kinematics, the robot’s initial position was derived by means of joint variables with which, when hourly laws were defined, the dynamic behavior of the module could be analyzed. The rigid multibody model was realized in MathWorks SimScape environment. The results obtained from the inverse and direct numerical activities allowed to estimate torque values at the joints that were found to be in accordance with the technical specifications of commercially available motors mounted on this type of manipulator. An important aspect is the microgravity condition implemented in the simulator to make the results realistic. The direct dynamics were obtained by imposing as input the torques obtained from the inverse dynamics to calculate the constrained reactions and the displacements attached to the base of the manipulator to verify when the latter was not fixed or if it was operating on a gateway or an orbiting vehicle of modest size and mass, no conditions would occur such that the orbit would not be maintained. This preliminary study and the calculated data will be essential for the preliminary design of cubesats for on-orbit maintenance application implemented with manipulators and 3d printers.

References 1. Pappalardo, C.M., La Regina, R., Guida, D.: Multibody modeling and nonlinear control of a pantograph scissor lift mechanism. J. Appl. Comput. Mech. 9(1), 129–167 (2023) 2. Manrique-Escobar, C.A., Pappalardo, C.M., Guida, D.: On the analytical and computational methodologies for modelling two-wheeled vehicles within the multibody dynamics framework: a systematic literature review. J. Appl. Comput. Mech. 8(1), 153–181 (2022) 3. Sun, X., Liu, H., Song, W., Villecco, F.: Modeling of eddy current welding of rail: threedimensional simulation. Entropy 22, art. no. 947 ((2020)) 4. Pappalardo, C.M., Lettieri, A., Guida, D.: A general multibody approach for the linear and nonlinear stability analysis of bicycle systems. Part I: methods of constrained dynamics. J. Appl. Comput. Mech. 7(2), 655–670 (2021) 5. Formato, A., Romano, R., Villecco, F.: A novel device for the soil sterilizing in sustainable agriculture. In: Karabegovi´c, I. (ed.) NT 2021. LNNS, vol. 233, pp. 858–865. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_94 6. Pappalardo, C.M., Lettieri, A., Guida, D.: A general multibody approach for the linear and nonlinear stability analysis of bicycle systems. Part II: application to the whipple-carvallo bicycle model. J. Appl. Comput. Mech. 7(2), 671–700 (2021) 7. Liguori, A., Formato, A., Pellegrino, A., Villecco, F.: Study of tank containers for foodstuffs. Machines 9(2), 44 (2021). https://doi.org/10.3390/machines9020044 8. De Simone, M.C., Celenta, G., Rivera, Z.B., Guida, D.: Mechanism design for a low-cost automatic breathing applications for developing countries. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V, pp. 345–352. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-031-052309_40 9. Pappalardo, C.M., Vece, A., Galdi, D., Guida, D.: Developing a reciprocating mechanism for the emergency implementation of a mechanical pulmonary ventilator using an integrated CAD-MBD procedure. FME Trans. 50(2), 238–247 (2022) 10. Manrique-Escobar, C.A., Pappalardo, C.M., Guida, D.: A multibody system approach for the systematic development of a closed-chain kinematic model for two-wheeled vehicles. Machines 9(11), 245 (2021)

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11. Pappalardo, C.M., Lettieri, A., Guida, D.: Identification of a dynamical model of the latching mechanism of an aircraft hatch door using the numerical algorithms for subspace state-space system identification. IAENG Int. J. Appl. Math. 51(2), 346–359 (2021) 12. Salvati, L., d’Amore, M., Fiorentino, A., Pellegrino, A., Sena, P., Villecco, F.: Development and Testing of a Methodology for the Assessment of Acceptability Systems. Machines 8(47) (2020). https://doi.org/10.3390/machines9020044 13. Pappalardo, C.M., Manca, A., Guida, D.: A combined use of the multibody system approach and the finite element analysis for the structural redesign and the topology optimization of the latching component of an aircraft hatch door. IAENG Int. J. Appl. Math. 51(1), 175–191 (2021) 14. Manrique Escobar, C.A., Pappalardo, C.M., Guida, D.: A parametric study of a deep reinforcement learning control system applied to the swing-up problem of the cart-pole. Appl. Sci. 10(24), 9013 (2020) 15. Pappalardo, C.M., Guida, D.: Dynamic analysis and control design of kinematically-driven multibody mechanical systems. Eng. Lett. 28(4), 1125–1144 (2020) 16. Formato, A., Ianniello, D., Pellegrino, A., Villecco, F.: Vibration-based experimental identification of the elastic moduli using plate specimens of the olive tree. Machines 7(2), 46 (2019). https://doi.org/10.3390/machines7020046 17. Liguori, A., Armentani, E., Bertocco, A., Formato, A., Pellegrino, A., Villecco, F.: Noise reduction in spur gear systems. Entropy 22, 1306 (2020) 18. Villecco, F., Aquino, R.P., Calabrò, V., Corrente, M.I., Grasso, A., Naddeo, V.: Fuzzy-assisted ultrafiltration of wastewater from milk industries. In: Naddeo, V., Balakrishnan, M., Choo, K.H. (eds.) Frontiers in Water-Energy-Nexus—Nature-Based Solutions, Advanced Technologies and Best Practices for Environmental Sustainability: Proceedings of the 2nd WaterEnergyNEXUS Conference, November 2018, Salerno, Italy, pp. 239–242. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-13068-8_59 19. De Simone, M.C., Veneziano, S., Guida, D.: Design of a non-back-drivable screw jack mechanism for the hitch lifting arms of electric-powered tractors. Actuators 11(12), 358 (2022) 20. Li, T., Kou, Z., Wu, J., Yahya, W., Villecco, F.: Multipoint optimal minimum entropy deconvolution adjusted for automatic fault diagnosis of hoist bearing. Shock Vibrat. 2021, art.no. 6614633 (2021) 21. Mei, S., Liu, M., Kudreyko, A., Cattani, P., Baikov, D., Villecco, F.: Bendlet transform based adaptive denoising method for microsection images. Entropy 24, 869 (2022). https://doi.org/ 10.3390/e24070869 22. Formato, A., Romano, R., Cattani, P., Villecco, F.: Stability analysis of self-propelled hydrodynamic irrigation machines used for food industry crops. Lect. Notes Networks Syst. 472, 788–797 (2022) 23. De Simone, M.C., Laiola, V., Rivera, Z.B., Guida, D.: Dynamic analysis of a hybrid heavyvehicle. Lect. Notes Networks Syst. 472 LNNS , 236–243 (2022)

Design of an Instrumented Rail Seat Test-Rig for Continuous Vehicle Monitoring Giampiero Celenta1 , Tony Luigi Leopoldo Lenza2 , and Marco Claudio De Simone2(B) 1 University of Salerno, MEID4 Academic Spin-Off, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy 2 Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy [email protected]

Abstract. The need for constantly efficient machines or systems and the increased costs associated with maintaining such efficiency has gradually changed the way in which maintenance of machines or devices is carried out. Such activities are, in fact, increasingly dependent on technologically advanced systems capable of predicting component deterioration over the course of regular use. In order to optimize maintenance interventions, therefore, the need arises to be able to predict the behavior of artifacts by monitoring the wear status of the component under operating conditions. This aspect is particularly felt in cases where the variables that determine deterioration are difficult to predict in their frequency while knowing the type of external actions that lead to deterioration. Current monitoring technologies rely primarily on the use of sensors, coupled with the relative ease of being able to manage data and share it in real time on the cloud, which is increasingly leading companies to equip their devices with sensor networks capable of recording a wide range of signals to monitor the health of the device itself. This paper reports on the preliminary development phase of a fatigue testing machine for testing instrumented seats using a Cartesian manipulator. Keywords: multi-body · test-rig · SimScape · experimental apparatus · railway application

1 Introduction The test-rig project arose from the need of a rail seat manufacturer to test instrumented seats. Seats in trains and buses are repeatedly subjected to stresses of various kinds that result in their gradual deterioration until they become unfit for service. These can be of various kinds, from the effect of regular use of the seat to stresses associated with improper use. Consider, for example, luggage of various kinds resting on the seat or sharp bodies such as to cause sudden deterioration of the upholstery. Similarly, structural parts improperly stressed can also deteriorate prematurely; for example due to improper loading of armrests. While having a sufficiently complete picture of the stresses insisting © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 365–372, 2023. https://doi.org/10.1007/978-3-031-31066-9_40

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on the seat, it is often difficult to relate possible damage to temporal or area-of-use parameters. Therefore, the suitability of the seat over time can only be ensured by implementing an expensive monitoring program of the installed seats, dictated by time deadlines that require massive personnel deployment. Alternatively, the solution to be adopted is to take advantage of sensors of various types to be integrated into the seat covers and structure and detect, from the analysis of the signals, damage or its imminent occurrence. In this way, operator intervention will be limited only to the occurrence of the damage event or its imminent occurrence [1].

2 Materials and Methods When undertaking a predictive maintenance activity, it is critical to relate the generic damage/deterioration event to a specific signal or combination of signals detected by the sensors [2]. The reference standard for those concerned with fatigue resistance of seats is the French standard NF F 31-119 of December 1995. Taking a cue from the standard and in consultation with the seat manufacturer, it was decided to develop a fatigue test machine to test a newly designed seat in the full Factory 4.0 view, doctored with appropriate IoT sensors for continuous monitoring of the state of the seat and the vehicle on which it is mounted [3, 4]. Continuous monitoring would allow for early notification of the need for intervention to fix or replace part or all of the seat itself. In order to then associate the sensor measurement with the occurrence of the defect or misuse of the seat by users, it will be necessary to correlate, through the analysis of large amounts of data, causes to effects [5]. This activity, which we might call “sensor setting,” is based on an intensive and exhaustive laboratory testing campaign. The fatigue-testing test rig will also allow testing sensors installed in the seats, information management, and transmission phase [6]. The processing of the data collected on board the vehicles will

Fig. 1. The concept

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enable targeted intervention at optimal times and ways, ensuring the company optimizes the internal resources, both productive and devoted to maintenance and the comfort of end customers [7]. For this reason, there is a need to design a test-rig that allows replication of a specific range of action to which, typically, the seat is subjected during regular use on vehicles. Downstream of specific test campaigns thus realized, it will be possible to associate the occurrence of damage/wear/deterioration with a specific signal or combination of signals [8, 9]. The concept of the experimental apparatus is reported in Fig. 1. The choice of such configuration was the result of a combination of parameters including, mainly: the types of effects to be replicated, possible evolutions of the “seat system” to be tested, reconfigurability of the system, ease of use, and the cost of the machine [10]. Cartesian configurations are widely used in the packaging and machine tool sectors. The current evolution of Cartesian robots makes them a crucial support system for material and component handling needs in the most modern production lines. The growth of industrial robotic applications is closely linked to the acceleration of industrial automation: technological improvements and the redefinition of robots as agents of connected artificial intelligence will foster the proliferation of robots [11]. Within this framework, Cartesian robots will continue to play an important role. Indeed, because of their characteristics, this type of manipulator, used mainly in industrial production for injection molding, is a testament to the technological evolution of the entire sector: indeed, there is a constant increase in their degrees of freedom, their precision, their speed, and their load capacity [12, 13]. Not to mention the possibility, based on the development of modular solutions, of realizing complex applications. The prospects for further development of Cartesian robotics are still excellent, especially in packaging and machine tool servicing [14]. This is due, on the one hand, to the still too high cost of anthropomorphic robots and, on the other hand, to the knowledge required to use them to the best effect, which has yet to be universally widespread.

Fig. 2. Detail of the assumed aluminum profile structure for the test-rig

Cartesian systems are also more flexible and easy to customize and have a significantly longer range. The level of performance that Cartesian robots provide is, therefore,

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superior at a cost that can also prove significantly lower, presenting higher levels of versatility and modularity than anthropomorphic robots [15–17]. Their ability to provide higher load levels relative to their size and achieve, concomitantly, high levels of precision make them a crucial support system for material and component handling needs in the most modern production lines [18]. The system makes it possible to perform wear tests on the seats by simulating the effect generated by external actions during the life of the device. In the 3D representation of the concept designed for the test machine, the four hypothesized subassemblies can be identified: Frame, Seat Support, Cartesian Assembly, and Main Actuator [19]. The frame forms the supporting structure of the test bench. For the machine frame, it was decided to use a modular and flexible approach that can adapt the apparatus’s size to the end customer’s needs. For this reason, it was decided to use aluminum profiles to ensure the rigidity of the structure in the face of low weight (see Fig. 2). Bosh-Rexroth products were chosen for the profiles, using 90 × 90 mm profiles for the structural parts and 45 × 45 mm for the less stressed areas. The seat support consists of an aluminum profile frame. The seat to be tested will be anchored to this frame. The Cartesian assembly will consist of two linear drives on which the actuator for fatigue testing will finally be mounted. The concept behind this system is to be found in the desire to make a single articulated system capable of moving anywhere in a region of space and in any direction, a wide range of “End-Effectors” will be able to be connected to the final actuator so that the widest possible range of real effects can be replicated on the seat. Real effects are defined as all the systematic and occasional actions to which the seat cover is or may be subjected during a generic cycle of use [13, 20]. The system thus constituted will have 2 degrees of freedom.

3 Numerical Activity In industrial applications, the process of designing new and complex mechanical systems, as in the present case, requires unconventional methods to analyze and validate a general

Fig. 3. Multibody model of the concept in SimScape multidomain environment

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design solution [21]. In addition, in terms of the possible final devices to be used during testing, the shape must be such that it can faithfully replicate the effect that the fabrics worn by the passengers exert on the seat upholstery. For this reason, it will be necessary to provide appropriately placed anchors that will allow the attachment of fabric upholstery to the surfaces of the end pieces. All of the above movements will be accomplished with linear or rotary electroactuators [22]. To this end, the dynamic behavior of mechanical systems constrained by joints and governed by kinematic actuators can be effectively studied through dynamic simulators that allow the import of three-dimensional geometries [12]. Multibody systems are models consisting of rigid or flexible bodies connected by kinematic joints.In Fig. 3 the multibody model of the concept is proposed. Through a multibody analysis, it is possible to size the actuators to be installed on the system, knowing the physical parameters of the machine and the required motion laws [23]. Generally, a set of differential-algebraic equations of motion governs the dynamic behavior of a multibody system. Therefore, advanced analysis approaches and computational procedures are needed to perform reliable dynamic simulations, significantly reducing the design time of a new device or machine. In addition, such procedures enable the design and testing of different actuator control strategies. Figure 4 reports the multibody model control system developed in the Simulink Stateflow environment [24].

Fig. 4. Machine management system implemented in the Stateflow environment

In SimScape environment, it is possible to model and test the mechanical model and the electromechanical or hydraulic subsystems. In order to test the dynamic behavior of the machine, it is necessary to set the desired trajectory for each degree of freedom with the corresponding motion laws. For the simulations, it was decided to use trapezoidal motion laws capable of best reproducing the dynamics of an electric actuator. This environment is a control logic tool used to model reactive systems using state machines and flow diagrams within a Simulink modelOnce the chosen trajectories and the corresponding time laws have been assigned, the system’s dynamic behavior can be monitored using the three-dimensional graphs. In addition, it is possible to measure the forces and torques that arise within the structure and the force that the end effector exchanges with the seat. The expected result of this step is the definition of the actuators and the required powers, depending on the masses, loads, and boundary conditions [25]. The device is driven by two linear actuators. The SimScape built-in function “Spatial Contact Force”

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was used to evaluate the effect of butt-seat contact during the test and evaluate in this way the respons of the sensors of the seat. The Spatial Contact Force block models the contact between a pair of bodies using the penalty method. This method allows the bodies to penetrate each other by a small amount to determine the contact forces. The block determines the normal and tangential (frictional) contact forces between the two bodies. The normal contact force is calculated using the equation of the classical spring-damper system. During contact, the normal contact force is proportional to its corresponding penetration depth and velocity. As the penetration depth is within the transition region, the block gradually increases in force [26]. At the end of that region, the stiffness and damping fields are applied at their maximum value.

Fig. 5. The developed Test-Rig during an experimantal activity

Figure 5 shows the fatigue testing machine for instrumented seats built at the laboratory of the Applied Mechanics group at the University of Salerno. The machine is controlled by a Siemens Plc and operated by the operator through an HMI. The endeffector consists of a CYLTRONIC electromechanical actuator to which different probes can be mounted depending on the test to be performed. The design task has been greatly simplified by being able to test and optimize the system in simulation and test the machine management system using Software In the Loop (SIL) techniques.

4 Results and Conclusions In order to optimize maintenance operations, the need arises to be able to monitor the behavior of machines or systems in real time by monitoring their component wear status during operating conditions. This method requires instrumented devices capable of handling large amounts of data and performant algorithms capable of correlating sensor responses to a particular defect. Using the Simscape multi-body modeling environment, an electromechanical model was built to test the dynamic behavior of the machine for different configurations, laws of motion and power requirements of the actuators. By means of inverse and direct dynamic analyses, it was possible to evaluate the frame reactions and the torques and speeds required by the actuators.To simulate the contact

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between the culoid and the seat, the contact was modeled for both the seat and the backrest. Normal and tangential forces between the culoid and seat have been evaluated. Reported. For the simulations conducted, given the most commonly used materials, it was decided to use a static and a dynamic friction coefficient of 0.5 and 0.3, respectively.The definition of the trajectories, duration of transients, and steady-state phases contribute to the definition of the time laws and the resulting mechanical power required.

References 1. Guida, C.G., Gupta, B.B., Lorusso, A., Marongiu, F., Santaniello, D., Troiano, A.: An Integrated BIM-IoT approach to support energy monitoring. In: International Conference on Smart Systems and Advanced Computing (Syscom-2021) (2021) 2. Manrique-Escobar, C.A., Pappalardo, C.M., Guida, D.: On the analytical and computational methodologies for modelling two-wheeled vehicles within the multibody dynamics framework: a systematic literature review. J. Appl. Comput. Mech. 8(1), 153–181 (2022) 3. Pappalardo, C.M., Lettieri, A., Guida, D.: A general multibody approach for the linear and nonlinear stability analysis of bicycle systems. Part I: methods of constrained dynamics. J. Appl. Comput. Mech. 7(2), 655–670 (2021) 4. De Simone, M.C., Veneziano, S., Guida, D.: Design of a non-back-drivable screw jack mechanism for the hitch lifting arms of electric-powered tractors. Actuators 11(12), 358 (2022) 5. Lorusso, A., Messina, B., Santaniello, D.: The use of generative adversarial network as graphical support for historical urban renovation. In: Cheng, L.-Y. (ed.) ICGG 2022 - Proceedings of the 20th International Conference on Geometry and Graphics, pp. 738–748. Springer International Publishing, Cham (2023). https://doi.org/10.1007/978-3-031-13588-0_64 6. Salvati, L., d’Amore, M., Fiorentino, A., Pellegrino, A., Sena, P. Villecco, F.: Development and testing of a methodology for the assessment of acceptability systems. Machines 8(47) (2020). https://doi.org/10.3390/machines9020044 7. Colace, F., Guida, C.G., Gupta, B., Lorusso, A., Marongiu, F., Santaniello, D.: A BIMbased approach for decision support system in smart buildings. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds.) Proceedings of Seventh International Congress on Information and Communication Technology. LNNs, vol. 447. Springer, Singapore (2023). https://doi.org/10. 1007/978-981-19-1607-6_42 8. Formato, A., Romano, R., Cattani, P., Villecco, F.: Stability analysis of self-propelled hydrodynamic irrigation machines used for food industry crops. Lect. Notes Networks Syst. 472, 788–797 (2022) 9. De Simone, M.C., Celenta, G., Rivera, Z.B., Guida, D.: Mechanism design for a low-cost automatic breathing applications for developing countries. LNNS 472, 345–352 (2022) 10. Casillo, M., Guida, C.G., Lombardi, M., Lorusso, A., Marongiu, F., Santaniello, D.: Predictive preservation of historic buildings through IoT-based system. In: 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), pp. 1194–1198. IEEE (2022) 11. Pappalardo, C.M., La Regina, R., Guida, D.: Multibody modeling and nonlinear control of a pantograph scissor lift mechanism. J. Appl. Comput. Mech. 9(1), 129–167 (2023) 12. Formato, A., Ianniello, D., Pellegrino, A., Villecco, F.: Vibration-based experimental identification of the elastic moduli using plate specimens of the olive tree. Machines 7(2), 46 (2019). https://doi.org/10.3390/machines7020046 13. Sun, X., Liu, H., Song, W., Villecco, F.: Modeling of eddy current welding of rail: threedimensional simulation. Entropy 22, art. no. 947 (2020)

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14. Pappalardo, C.M., Lettieri, A., Guida, D.: A general multibody approach for the linear and nonlinear stability analysis of bicycle systems. Part II: application to the whipple-carvallo bicycle model. J. Appl. Comput. Mech. 7(2), 671–700 (2021) 15. Liguori, A., Armentani, E., Bertocco, A., Formato, A., Pellegrino, A., Villecco, F.: Noise reduction in spur gear systems. Entropy 22, 1306 (2020) 16. Pappalardo, C.M., Vece, A., Galdi, D., Guida, D.: Developing a reciprocating mechanism for the emergency implementation of a mechanical pulmonary ventilator using an integrated CAD-MBD procedure. FME Trans. 50(2), 238–247 (2022) 17. Liguori, A., Formato, A., Pellegrino, A., Villecco, F.: Study of tank containers for foodstuffs. Machines 9(2), 44 (2021). https://doi.org/10.3390/machines9020044 18. Manrique-Escobar, C.A., Pappalardo, C.M., Guida, D.: A multibody system approach for the systematic development of a closed-chain kinematic model for two-wheeled vehicles. Machines 9(11), 245 (2021) 19. Pappalardo, C.M., Lettieri, A., Guida, D.: Identification of a dynamical model of the latching mechanism of an aircraft hatch door using the numerical algorithms for subspace state-space system identification. IAENG Int. J. Appl. Math. 51(2), 346–359 (2021) 20. Li, T., Kou, Z., Wu, J., Yahya, W., Villecco, F.: Multipoint optimal minimum entropy deconvolution adjusted for automatic fault diagnosis of hoist bearing. Shock Vibrat. 2021, art.no. 6614633 (2021) 21. Pappalardo, C.M., Manca, A., Guida, D.: A combined use of the multibody system approach and the finite element analysis for the structural redesign and the topology optimization of the latching component of an aircraft hatch door. IAENG Int. J. Appl. Math. 51(1), 175–191 (2021) 22. Manrique Escobar, C.A., Pappalardo, C.M., Guida, D.: A parametric study of a deep reinforcement learning control system applied to the swing-up problem of the cart-pole. Appl. Sci. 10(24), 9013 (2020) 23. Pappalardo, C.M., Guida, D.: Dynamic analysis and control design of kinematically-driven multibody mechanical systems. Eng. Lett. 28(4), 1125–1144 (2020) 24. Formato, A., Romano, R., Villecco, F.: A novel device for the soil sterilizing in sustainable agriculture. Lect. Notes Networks Syst. 233, 858–865 (2021) 25. Mei, S., Liu, M., Kudreyko, A., Cattani, P., Baikov, D., Villecco, F.: Bendlet transform based adaptive denoising method for microsection images. Entropy 24, 869 (2022). https://doi.org/ 10.3390/e24070869 26. De Simone, M.C De., Laiola, V., Rivera, Z.B., Guida, D.: Dynamic analysis of a hybrid heavyvehicle. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V, pp. 236–243. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_27

Analysis and Design of Test-Rigs for Laboratory Tests Under Microgravity Conditions Salvio Veneziano1 , Giampiero Celenta1 , and Marco Claudio De Simone2(B) 1 MEID4 Academic Spin-Off of the University of Salerno, Via Giovanni Paolo II, 132,

84084 Fisciano, Italy [email protected], [email protected] 2 Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy [email protected]

Abstract. The restrictions imposed by the pandemic have severely affected the aerospace sector. To cope with this deepening crisis, therefore, the aerospace industry should use its know-how in the implementation of disruptive and highly innovative projects that would lead it, in the medium to long term, to cope with the current post-pandemic economic crisis. This is the context of the collaboration between the Italian Space Agency (ASI) and the European Space Agency (ESA) in connection with the European Advanced Generation Carrier (Vega). Such launchers simultaneously put into orbit about 50 small, lightweight satellites that will be used for a variety of applications-including earth observation, telecommunications, science, technology, and education. Given the growing interest of companies in this field, it was hypothesized to create a test rig for testing under microgravity conditions. The following work presents the design of a parallel manipulator capable of simulating flight conditions and performing vibration tests specifically for this type of minisatellite. The 3D model of the manipulator and CubeSat was developed in Solidworks while the rigid/flexible multibody model was modeled in Mathworks’ Simscape multidomain environment. Keywords: multi-body · parallel manipulator · SimScape · Solidworks · dynamisc · micro-gravity

1 Introduction With the advent of a new microsatellite standard, CubeSats are being developed, thanks to their high versatility, including earth observation, telecommunications, science, technology, and education. The “CubeSat” satellites whose standards provide for classification based on cube size and weight [1]. For example, a 1U CubeSat corresponds to a cube with sides equal to 10 cm and a mass not exceeding 2 kg. In addition to the standards, these types of satellites have to undergo several standards, among which as a requirement is the submission of the satellite to some mandatory tests such as: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 373–380, 2023. https://doi.org/10.1007/978-3-031-31066-9_41

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– Vibration Test: the CubeSat’s ability to withstand vibration due to launch; – Shock Test: the CubeSat’s ability to resist shocks and impacts inside the dispenser at launch; – Thermal Vacuum Bakeout: tests whether proper outgassing of components occurs; – EMI Test: the effectiveness of shielding and attenuation of electrical interference; – Magnetic Calibration And Testing: tests the hardware in an electromagnetically controlled environment. This paper reports the preliminary design phase of a vibration test rig to analyze the dynamic behavior of minisatellites and manipulators for space applications. Specifically, a Stewart platform was developed in the Solidwork environment [2–4]. A rigid multibody model was developed for the SimScape multi-domain simulation environment for estimating constraint reactions in joints, velocity, and power required for movement [5].

2 Materials and Methods The idea of designing a six-degree-of-freedom system capable of vibration testing arose from the Applied Mechanics of Machines research group’s need to expand to environmental maintenance and monitoring using minisatellites [6]. The systems present at research facilities employ parallel manipulators in most cases. For example, The SDTS is a six-degree-of-freedom device with a repositionable, fixed upper platform and a moving lower base capable of testing large-scale docking and mooring systems. It is nothing more than a parallel six-degree-of-freedom mechanism named Stewart’s platform [7]. All simulations are controlled by a series of interconnected computers that run the simulations in real-time using specific software. Having to repurpose the space environment to perform the simulations requires the introduction of the physical equations governing the phenomena in that context. For simplicity, orbital mechanics can be described through Kepler’s equations [8–10]. The motion of a satellite in orbit to be defined, one must consider three reference frames: – An inertial reference frame integral to Earth, where the x1 axis is directed toward the intersection of the equatorial plane and the Greenwich meridian, the z1 axis is oriented toward the North Pole, and to complete the levogyric tern the y1 axis [11]. – An orbit reference tern with origin in the CoG of the satellite where: xr is the roll axis, zr is the yaw axis, and finally, yr is the pitch axis [12]. Concerning the frame, the angular velocity to the inertial frame ωri and the angular velocity expressed in the reference system integral to the satellite ωrib . – Frame integral to the satellite with origin in the satellite’s CoG where the calculated angular velocity with respect to the orbit reference tern is equal to: ωbr = pi + qj + rk To evaluate the attitude of the satellite, Euler angles were evaluated, which allow the transformation of a vector from the coordinates of one reference system to another through three successive rotations [13–15]. The angular velocity of the reference system with respect to the inertial system is called the “rate of frequency,” which is calculated with respect to the reference system

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integral to the body through the linearized transformation matrix. The angular velocity of the body with respect to the inertial triad can be written as: ⎡ ⎤ ⎡ ⎤ ˙ − ω0  ωx ⎣ ωy ⎦ = ⎣ θ˙ − ω0 ⎦ ˙ + ω0  ωz While the vector of satellite acceleration with respect to the inertial triad can be written as: ⎡ ⎤ ⎡ ⎤ ¨ − ω ˙ 0  ω˙x ⎣ ω˙y ⎦ = ⎣ ⎦ θ˙ ¨ ˙  + ω0 ω˙ zz Working in LEO orbits, i.e., low orbits, gravitational action acts on the body by implying a torque that causes it to be aligned so that the triad integral to the body coincides with the orbit reference triad [16–19]. If the satellite attitude involves non-zero Euler angles, this torque is to be considered as the disturbance torque to be compensated for, which will be equal to: dTg = −ρ × μ ∗ dm ∗

r μdm =− 3 ∗ ρ×R 3 r r

where − μ ∗r 3dm is the infinitesimal attractive force acting on such a small element and r = R + ρ.

3 Numerical Activity Stewart’s platform is a six-degree-of-freedom mechanism; therefore, three translations and three rotations will be required to describe it [20]. From Fig. 1a, it can be seen that

Fig. 1. a) Schematization of Stewart’s platform and b) loop equation of one leg

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two platforms characterize Stewart’s platform: one fixed and one movable, which are connected by six linear actuators that can be schematized with two ball joints at the end and in the middle by a prismatic joint. We define q as the generalized coordinate vector consisting of the six variables chosen to describe the position and orientation of the moving platform: q = [X1 , Y1 , Z1 , ϕ, θ, ψ]T In contrast to a serial manipulator, it is convenient for a parallel manipulator to work within an inverse kinematics framework: the inverse kinematics problem consists of determining the joint variables once the pose of the end organ has been assigned [21]. In the specific case of Stewart’s platform being moved by linear actuators, the resolution of inverse kinematics involves determining the lengths between the coupling points of the fixed and movable platform, which are necessary to achieve the desired motion. The geometric and trigonometric relationships related to the platform under consideration were exploited to determine the lengths (see Fig. 1b). We define the “leg vector” l regarding the fixed triad as: l = t + Rp − b The length of the leg can be expressed by making the Euclidean norm of the vector l: l = l The latter two equations represent the closed solution to the inverse kinematic problem since the required actuator length can be expressed through the norm of a given Cartesian coordinate vector q, representing the position and orientation of the moving platform [22]. To obtain the dynamic model of the manipulator, it must be divided into two parts: the moving part and the six actuators together with the basic platform. The dynamic model can be developed through the Lagrange equations to calculate the constrained reactions of the joints or by using multibody modelling [7]. In this case, the 3D model of Stewart’s platform was made in Solidworks. In contrast, the model used for kinematic and dynamic analysis was implemented in the Simscape Multibody multi-domain simulation environment for simulation. The purpose of the Test-Rig to be carried out is to be able to perform vibration and approach tests for minisatellites. In particular, the most severe conditions to which the structure is subjected are examined. The most severe conditions will undoubtedly be those that the system will have to undergo during the launch phase [23]. For this reason, it was decided to size the test rig subjected to Shock Vibration Test, where the velocities involved will undoubtedly be high. For this reason, it was chosen to build a platform capable of withstanding vibrations with frequencies ranging from 95 to 2000 Hz, just as indicated by the regulations provided by NASA [21]. The most common configuration for this type of structure uses six links mounted on plates of semi-regular hexagonal shape, the hexagon of which must be able to be inscribed in a circumference according to a mixed configuration between type 6–6 and type 3–3, which is among the most

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controllable and straightforward. On the other hand, it allowed us to investigate the values of elongation, forces, velocities, and, therefore, the powers of the individual actuators as the frequency varies. This information was crucial to the sizing and catalog selection of the six actuators. For simplicity’s sake, the choice of the type of actuators fell on the electric ones since they are more controllable and manageable in contrast to hydraulic or air actuators [24, 25] (Fig. 2).

(a)

(b)

Fig. 2. a) Simulink canvas and b) Multibody model in the SimScape multidomain simulation environment

4 Results For the model shown in the figure, different tests were carried out by changing both the load to be tested, amplitude and frequency of the excitation to be subjected to the CubeSat, and levels of accelerations [26, 27]. From the simulations performed, the maximum force, maximum speed and maximum power to which the individual actuators are subjected are equivalent to about 18 kN, 25 cm\s and 2 kW, respectively. From the analysis of the constraint reactions also, it was possible to evaluate the type of joint to be used [28, 29]. The safest choice may fall on magnetic spherical joints, which reach a ball rotation angle of 242° and for which cost, size and holding force are taken into consideration, characteristics that increase with each other, of which the holding force should be neither too low nor in order to prevent the joint from separating during operation [30]. Importantly, the six legs must operate together, in a coordinated manner, otherwise position and orientation will be incorrect; this sometimes implies the insertion of a shaft coupler in series with the actuator [4, 6].

5 Conclusion The increasing interest of private companies in investing in aerospace and, in particular, in the design and launch of new space explorers, such as Cubesat, have contributed significantly to the decision made regarding the sizing of a Test-Rig for prelaunch vibration

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testing [28]. The orbital dynamics were analyzed, and a multibody model of the Test-Rig to be built was developed. By means of an inverse dynamics analysis, linear actuators to be installed on the prototype were sized for specific tests. The data obtained from this study will make it possible to move on to the implementation phase and develop a platform to test CubeSat satellites for land monitoring, such as detection and monitoring of illegal spills, weather conditions, and monitoring possible environmental disasters [30].

References 1. Ding, X., Isaksson, M.: Quantitative analysis of decoupling and spatial isotropy of a generalised rotation-symmetric 6-DOF Stewart platform. Mech. Mach. Theory 180, art. no. 105156 (2023). https://doi.org/10.1016/j.mechmachtheory.2022.105156 2. Casillo, M., Guida, C.G., Lombardi, M., Lorusso, A., Marongiu, F., Santaniello, D.: Predictive preservation of historic buildings through IoT-based system. In: 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), pp. 1194–1198. IEEE (2022) 3. Manrique-Escobar, C.A., Pappalardo, C.M., Guida, D.: On the analytical and computational methodologies for modelling two-wheeled vehicles within the multibody dynamics framework: a systematic literature review. J. Appl. Comput. Mech. 8(1), 153–181 (2022) 4. Horoub, M.M., et al.: Study the effect of changing Cables’ pattern on the workspace of a six DOF floating parallel marine robot (FPMR). Alexandria Eng. J. 64, 847–858 (2023). https:// doi.org/10.1016/j.aej.2022.08.043 5. Pappalardo, C.M., Lettieri, A., Guida, D.: A general multibody approach for the linear and nonlinear stability analysis of bicycle systems. Part II: application to the whipple-carvallo bicycle model. J. Appl. Comput. Mech. 7(2), 671–700 (2021) 6. Mei, Q., She, J., Wang, F., Nakanishi, Y., Hashimoto, H., Chugo, D.: Disturbance rejection and control system design using {1}-Inverse-based equivalent-input-disturbance approach. IEEE Trans. Industr. Electron. 70(2), 1666–1675 (2023). https://doi.org/10.1109/TIE.2022. 3161805 7. Manrique-Escobar, C.A., Pappalardo, C.M., Guida, D.: A multibody system approach for the systematic development of a closed-chain kinematic model for two-wheeled vehicles. Machines 9(11), 245 (2021) 8. Pappalardo, C.M., Lettieri, A., Guida, D.: Identification of a dynamical model of the latching mechanism of an aircraft hatch door using the numerical algorithms for subspace state-space system identification. IAENG Int. J. Appl. Math. 51(2), 346–359 (2021) 9. Mishra, S.K., Kumar, C.S.: Design exploration of stewart platform. Lect. Notes Mech. Eng. 127–140 (2023). https://doi.org/10.1007/978-981-19-3716-3_10 10. Manrique Escobar, C.A., Pappalardo, C.M., Guida, D.: A parametric study of a deep reinforcement learning control system applied to the swing-up problem of the cart-pole. Appl. Sci. 10(24), 9013 (2020) 11. Pappalardo, C.M., Guida, D.: Dynamic analysis and control design of kinematically-driven multibody mechanical systems. Eng. Lett. 28(4), 1125–1144 (2020) 12. Salvati, L., d’Amore, M., Fiorentino, A., Pellegrino, A., Sena, P., Villecco, F.: Development and testing of a methodology for the assessment of acceptability systems. Machines 8(47) (2020). https://doi.org/10.3390/machines9020044 13. Formato, A., Ianniello, D., Pellegrino, A., Villecco, F.: Vibration-based experimental identification of the elastic moduli using plate specimens of the olive tree. Machines 7(2), art. no. 46 (2019). https://doi.org/10.3390/machines7020046

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14. Sun, X., Liu, H., Song, W., Villecco, F.: Modeling of eddy current welding of rail: threedimensional simulation. Entropy 22, art. no.947 (2020). https://doi.org/10.3390/e22090947 15. Liguori, A., Armentani, E., Bertocco, A., Formato, A., Pellegrino, A., Villecco, F.: Noise reduction in spur gear systems. Entropy 22, 1306 (2020). https://doi.org/10.3390/e22111306 16. Villecco, F., Aquino, R.P., Calabrò, V., Corrente, M.I., Grasso, A., Naddeo, V.: Fuzzy-assisted ultrafiltration of wastewater from milk industries. In: Naddeo, V., Balakrishnan, M., Choo, KH. (eds.) Frontiers in Water-Energy-Nexus—Nature-Based Solutions, Advanced Technologies and Best Practices for Environmental Sustainability. ASTI. Springer, Cham (2020). https:// doi.org/10.1007/978-3-030-13068-8_59 17. Pappalardo, C.M., Vece, A., Galdi, D., Guida, D.: Developing a reciprocating mechanism for the emergency implementation of a mechanical pulmonary ventilator using an integrated cad-mbd procedure. FME Trans. 50(2), 238–247 (2022) 18. Liguori, A., Formato, A., Pellegrino, A., Villecco, F.: Study of tank containers for foodstuffs. Machines 9, art. no. 44 (2021). https://doi.org/10.3390/machines9020044 19. Li, T., Kou, Z., Wu, J., Yahya, W., Villecco, F.: Multipoint optimal minimum entropy deconvolution adjusted for automatic fault diagnosis of hoist bearing. Shock Vibrat. 2021, art.no. 6614633 (2021) 20. Formato, A., Romano, R., Villecco, F.: A novel device for the soil sterilizing in sustainable agriculture. In: Karabegovi´c, I. (ed.) NT 2021. LNNS, vol. 233, pp. 858–865. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_94 21. Pappalardo, C.M., Manca, A., Guida, D.: A combined use of the multibody system approach and the finite element analysis for the structural redesign and the topology optimization of the latching component of an aircraft hatch door. IAENG Int. J. Appl. Math. 51(1), 175–191 (2021) 22. Mei, S., Liu, M., Kudreyko, A., Cattani, P., Baikov, D., Villecco, F.: Bendlet transform based adaptive denoising method for microsection images. Entropy 24, 869 (2022). https://doi.org/ 10.3390/e24070869 23. Formato, A., Romano, R., Cattani, P., Villecco, F.: Stability analysis of self-propelled hydrodynamic irrigation machines used for food industry crops. Lect. Notes Networks Syst. 472, 788–797 (2022). https://doi.org/10.1007/978-3-031-05230-9_94 24. De Simone, M.C., Veneziano, S., Guida, D.: Design of a non-back-drivable screw jack mechanism for the hitch lifting arms of electric-powered tractors. Actuators 11(12), 358 (2022) 25. Pappalardo, C.M., La Regina, R., Guida, D.: Multibody modeling and nonlinear control of a pantograph scissor lift mechanism. J. Appl. Comput. Mech. 9(1), 129–167 (2023) 26. Guida, C.G., Gupta, B.B., Lorusso, A., Marongiu, F., Santaniello, D., Troiano, A.: An Integrated BIM-IoT approach to support energy monitoring. In: International Conference on Smart Systems and Advanced Computing (Syscom-2021) (2021) 27. Lorusso, A., Messina, B., Santaniello, D.: The use of generative adversarial network as graphical support for historical urban renovation. In: Cheng, LY. (eds.) ICGG 2022 - Proceedings of the 20th International Conference on Geometry and Graphics. ICGG 2022. LNDECT, vol. 146. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-13588-0_64 28. De Simone, M.C., Celenta, G., Rivera, Z.B., Guida, D. : Mechanism design for a low-cost automatic breathing applications for developing countries. Lect. Notes Networks Syst. 472, 345–352 (2022). https://doi.org/10.1007/978-3-031-05230-9_40 29. Colace, F., Guida, C.G., Gupta, B., Lorusso, A., Marongiu, F., Santaniello, D.: A BIMbased approach for decision support system in smart buildings. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds.) Proceedings of Seventh International Congress on Information and Communication Technology. LNNS, vol. 447. Springer, Singapore (2023). https://doi.org/10. 1007/978-981-19-1607-6_42

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30. De Simone, M.C., Laiola, V., Rivera, Z.B., Guida, D.: Dynamic analysis of a hybrid heavyvehicle, LNNS, 472, 236–243 (2022). https://doi.org/10.1007/978-3-031-05230-9_27

Contributions Regarding the Implementation of the Digital Archiving Process in a Public Organization Constantin Dorin Olteanu1 , Cristian Vasile Doicin1 , Nicolae Ionescu1 , and Aurel Mihail T, ît, u2,3(B) 1 Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest,

Splaiul Independen¸tei nr. 313, 6th District, Bucharest, Romania [email protected], {cristian.doicin,nicolae.ionescu}@upb.ro 2 Lucian Blaga University of Sibiu, 10 Victoriei Street, Sibiu, Romania [email protected] 3 The Academy of Romanian Scientists, 54 Splaiul Independentei, Bucharest, Romania ,

Abstract. The scientific paper presents original research on implementing the digital archiving process within a public organization. Current archiving is mainly done in physical format, which is not beneficial. Physical archiving involves using significant material resources, physical space resources, time resources, and additional human resources. The research proposed by the authors follows the orientation of the current society towards the digitization of the activities of a public organization and the implementation of digital archiving, considerably reducing the resources used for physical archiving and, finally, the quality of the services offered to citizens can increase significantly. In this scientific paper, we have proposed mathematical modeling that respects a dedicated research methodology and is carried out with experimental data analysis software. Later I processed and interpreted the experimental data. More, an estimate was made for 20 years of the number of files that should be archived. The digital capacity required for the digital archiving of the scanned documents, the estimation of the time needed for the scanning documents, and the estimation of the energy consumption required for the scanning documents for archiving were also estimated. At the end of the paper, the conclusions that emerge from this essential and helpful research to be effectively implemented are presented. Keywords: digital archiving · mathematical modeling · experimental research · digitization of activities · public organization

1 Introduction Following an analysis of the studied organization, we identified a real need to improve an existing situation. In the studied county organization, for records of persons, a viable solution is proposed that can be applied at present. As a result of all the activities carried out within the organization, very large amounts of documents result from that must be kept for a certain period in a physical archive within the organization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 381–388, 2023. https://doi.org/10.1007/978-3-031-31066-9_42

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The current trend in managing technological processes is the widespread use of mathematical models [1]. They reproduce the researched process with the help of functional relationships and allow finding the optimal operating conditions in real time and with much lower material costs than physical models [2]. Research with the help of mathematical models eliminates the disadvantages that appear in the case of research on physical models. These disadvantages are the long time allocated to research, a large amount of work, and the impossibility of including economic factors [3]. Using mathematical modeling by simultaneously examining various factors, results can be obtained that lead to improving a system, a process, or a product [4]. Moreover, a mathematical model can be understood as a representation in mathematical terms of the behavior of real systems, devices, and objects [5]. We propose to do a mathematical modeling to see if it is possible, from a technical point of view, to achieve digital archiving, considering that different factors can influence the system’s performance [6]. For this, we estimated the number of archived files for 20 years. We estimated the digital storage capacity, the time required for the digital scanning of the documents, and an estimate of the electricity consumption for these scans. Digital archiving is an option that, in current times, can provide a solution to the archiving needs of the organization under study. The creation of a digital archive is part of the current orientation of society toward the digitization of activities [7]. The implementation of digital archiving considerably reduces the resources used for physical archiving, and finally, the quality of services offered to citizens will increase.

2 Mathematical Modeling of the Digital Archiving Process Storing document files in a physical archive requires significant time and physical, financial, and human resources. In addition, using information from a physical archive takes much work. For example, searching for a document in the archive requires effort and allocating time to travel through the archive search, and in addition, there is a risk that the document sought may not be found or may be damaged. On the other hand, Digital archiving provides fast and secure access to archived documents, and rigorous control over document access eliminates storage space and the risk of damage to these documents. The archiving period is specific to each document type and is established by the archival nomenclature approved by the executive director. Within the studied organization, most archived documents are made by the Civil Status Service and the Personal Records Service. Likewise, in the other departments of the studied organization, namely the Financial department, accounting, and materialtechnical assurance, The legal litigation department, and the human resources and public relations department, as a result of the activities carried out, there is a reasonably significant amount of paper documents that must also be archived. The last record of the files archived within the studied organization is from the year 2021. In that year, the files made until the end of 2019 were archived because the files made in the last two years were not archived. Therefore, it is considered that they can still be used in the current activity. The number of files created in 2019 is 389 files.

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Depending on the nature of the information in the documents, files must be kept for three years, but some of which may be kept permanently. However, most are kept for ten years. The experimental data we hold is for files archived between 2009 and 2019 and are presented in Table 1 for each service and department, SSC (Civil Status Service), SEP (Personal Records Service), CFCATM (Financial, Accounting, and Technical Insurance Department Material), CCJRU (Legal Litigation Department and Human Resources and Public Relations Department), CI (Informatics Department). Also, Table 1 also records the specific archiving periods. Table 1. Files archived in the years 2009 – 2019 Indicator

Archiving period

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

SSC

5 years 10 years 20 years 50 years 100 years

0 0 1 0 0

0 1 0 0 0

0 11 0 1 1

6 28 2 29 0

2 36 2 33 1

5 39 0 35 1

12 33 0 35 1

5 76 0 10 1

1 106 0 11 3

1 116 0 12 0

2 139 0 10 2

SEP

5 years 10 years 15 years Permanent

4 4 2 0

11 4 3 1

14 77 16 2

23 63 12 0

12 71 13 1

17 102 11 1

19 93 6 2

44 110 8 1

82 140 8 1

81 123 5 0

50 107 6 1

CFCATM 5 years 10 years 50 years Permanent

0 24 0 0

0 1 0 0

4 0 0 0

11 37 1 7

62 45 0 4

13 55 0 4

4 43 0 2

8 49 0 4

8 47 0 4

5 37 1 1

6 40 0 7

CCJRU

3 years 5 years 10 years 50 years 80 years Permanent

0 0 5 0 2 2

0 3 8 0 2 4

0 1 4 0 1 2

0 2 6 1 13 4

0 4 4 0 7 1

0 9 6 0 8 7

4 4 2 1 8 4

6 4 2 0 7 2

1 3 5 0 2 5

1 2 3 0 12 7

3 2 1 0 6 5

CI

5 years 20 years

0 0

0 0

0 2

5 1

5 1

3 1

0 0

1 0

3 0

2 0

2 0

44

38

136

251

304

317

273

338

430

409

389

Total

In the field of statistics, specialized software, such as MINITAB or Statgraphics, support the introduction, planning, analysis, and interpretation of experimental data [8]. From the experimental data in Table 1, with MINITAB data analysis and graphing software were used to analyze and visualize these data. Linear regression was used for the analysis. Processing the data with the MINITAB program, the following equation resulted in linear regression: No. of files = 35, 33 + 38, 49 ∗ Years

(1)

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Starting from this equation, we estimated the number of files for 20 years. It should be noted that not all archived files need to be kept permanently. The results for each year of the estimated 20 years are given in Table 2, and the graphic representation is in Fig. 1.

Total/Year without Overdue Files

12

-0

54

-0

1

-0

2

1

0

2

74

74

74

74

-0 -0 -1 -1 -1 -1 -2 -2 -2 -3 -3 -3 -4 -4 -4 -4 -5 -5 -5

18 24 30 36 42 49 55 61 67 73 79 85 92 98 104 110 116 122 128

-0 -0 -0 -0 -12 -18 -24 -30 -36 -42 -49 -55 -61 -67 -73 -79 -85 -92 -98

83 111 140 168 196 225 253 282 310 338 367 395 424 452 480 509 537 566 594

-0 -0 -0 -0 -0 -0 -0 -0 -0 -54 -83 -111 -140 -168 -196 -225 -253 -282 -310

2 2 3 4 4 5 5 6 6 7 8 8 9 9 10 11 11 12 12

-0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -0 -1 -2 -2 -3 -4

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

2 2 3 4 4 5 5 6 6 7 8 8 9 9 10 11 11 12 12

1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 4 4 4 4

4 5 6 8 9 10 11 13 14 15 17 18 19 20 22 23 24 26 27

112 151 189 228 266 305 343 382 420 459 497 536 574 613 651 690 728 767 805

112 151 189 227 253 285 317 350 382 359 363 366 370 374 376 379

186 337 526 754 1020 1325 1668 2050 2470 2929 3426 3962 4536 5149 5800 6490

382 386 389

7218 7984 8790

186 337 526 753 1006 1291 1609 1958 2340 2699 3062 3428 3799 4172 4549 4928 5311 5696 6085

10 years

5 years

Total Files Archive

Permanent

-0

1 1 1 2 2 2 3 3 3 4 4 4 4 5 5 5 6 6 6

Total Files Collected

100 years

Total/Year

80 years

1

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

15 years

1

3 years

50 years

Period in years

Table 2. Estimated number of files archived in the next 20 years.

In the next step, the storage capacity was estimated for each year of the first 20 years. For this estimate, the PDF scan was chosen in Table 3. Dosare vs Ani 6085

6000

5696 5311 4928

5000

4549

Număr Dosare

4172 3799

4000

3428 3062

3000

2699 2340 1958

2000 1000 74

186

337

526

753

1006

1291

1609

0

0

5

10

15

20

Ani

Fig. 1. An annual increase in the total number of files and the number of archived files / Estimate of the total number of files for 20 years

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385

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

74

186

337

526

753

1006

1291

1609

1958

2340

2699

3062

3428

3799

4172

4549

4928

5311

5696

6085

18500

46500

84250

131500

188250

251500

322750

402250

489500

585000

674750

765500

857000

949750

1043000

1137250

1232000

1327750

1424000

1521250

7,94685

14,3983

22,4734

32,1719

42,9814

55,158

68,7445

83,6556

99,9765

115,315

130,824

146,461

162,312

178,249

194,356

210,549

226,913

243,362

259,982

Estimated capacity

Pieces b

Estimated pages

GB

Estimated files

Pieces

YEAR

3,16165

Table 3. Simulation of storage capacity – calculation with simulated number of files for 20 years

3 The Use of the Factorial Experiment in the Proposed Research Next, experimental statistical modeling is presented using the central compound factorial experiment method for the addressed research. I chose the objective functions: Y1 - Standard Scanning with Compression and Priority Quality, Y2 - Required scanning time, and Y3 - Electricity consumption required for Digital Archiving, for which I identified minimums and maximums. The Standard Scan with Compression and Quality Priority (SSCCCP) objective function represents the digital storage capacity required for the chosen scanning method. SSCCCP min = 18500 ∗ 0, 000170898 = 3, 16162 GB

(2)

SSCCCP max = 201250 ∗ 0, 000170898 = 34, 3932 GB

(3)

The objective function, Required Scan Time (TS), represents the time required to scan documents. 18500 ∗ 3, 3 sec = 16, 958 hours 3600

(4)

201250 ∗ 3, 3 sec = 184, 4792 hours 3600

(5)

TS min = TS max =

The objective function, Electricity consumption for Digital Archiving (CAD), represents the electricity required to scan documents. CAD min = TS min ∗ 0, 06 KW = 16, 958 ∗ 0, 06 KW = 1, 01748 KW (6) CAD max = TS max ∗ 0, 06 KW = 184, 479 ∗ 0, 06 KW = 11, 06875 KW (7) For the input data used in the experiment, the indicators obtained by shortening the name of the service/department were used. For X1 - SSC (Civil Status Service), for X2

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- SEP (Personal Records Service), for X3 - CFCATM (Financial, accounting, and technical-material insurance department), for X4 - CCJRU (Legal litigation, human resources, and public relations department), for X5 - CI (Informatics compartment). Each indicator reflects many archived files, highlighted in Table 4. Table 4. Design matrix of variables X1

X2

X3

X4

X5

Y1

Y2

Y3

SSC

SEP

CFCATM

CCJRU

CI

SSCCCP

TS

CAD

1

29

31

10

1

3,16165

16,9583

1,0175

2

29

31

10

3

4

3,28982

17,6458

1,05875

3

29

31

10

35

1

4,52885

24,2916

1,4575

4

29

31

10

35

4

4,65702

24,9791

1,49875

5

29

31

110

3

1

7,43415

39,875

2,3925

6

29

31

110

3

4

7,56232

40,5625

2,43375

7

29

31

110

35

1

8,80135

47,2083

2,8325

8

29

31

110

35

4

8,92952

47,8958

2,87375

9

29

339

10

3

1

16,3209

87,5416

5,2525

10

29

339

10

3

4

16,4491

88,2291

5,29375

11

29

339

10

35

1

17,6881

94,875

5,6925

12

29

339

10

35

4

17,8163

95,5625

5,73375

13

29

339

110

3

1

20,5934

110,458

6,6275

14

29

339

110

3

4

20,7216

111,145

6,66875

15

29

339

110

35

1

21,9606

117,791

7,0675

16

29

339

110

35

4

22,0888

118,479

7,10875

17

317

31

10

3

1

15,4664

82,9583

4,9775

18

317

31

10

3

4

15,5946

83,6458

5,01875

19

317

31

10

35

1

16,8336

90,2916

5,4175

20

317

31

10

35

4

16,9618

90,9791

5,45875

21

317

31

110

3

1

19,7389

105,875

6,3525

22

317

31

110

3

4

19,8671

106,562

6,39375

23

317

31

110

35

1

21,1061

113,208

6,7925

24

317

31

110

35

4

21,2343

113,895

6,83375

25

317

339

10

3

1

28,6257

153,541

9,2125

26

317

339

10

3

4

28,7539

154,229

9,25375

27

317

339

10

35

1

29,9929

160,875

Number of determinations

3

9,6525 (continued)

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Table 4. (continued) X1

X2

X3

X4

X5

Y1

Y2

Y3

Number of determinations

SSC

SEP

CFCATM

CCJRU

CI

SSCCCP

TS

CAD

28

317

339

10

35

4

30,1211

161,562

9,69375

29

317

339

110

3

1

32,8982

176,458

10,5875

30

317

339

110

3

4

33,0264

177,145

10,6287

31

317

339

110

35

1

34,2654

183,791

11,0275

32

317

339

110

35

4

34,3936

184,479

11,0687

Mathematical modeling y1 = f(x1, x2) → SSCCCP = f(SSC, SEP). It can be seen in Fig. 2, the evolution of the objective function SSCCCP according to the indicators/experimental factors SEP and SSC. The objective function SSCCCP - Standard scan with compression and priority quality, reaches the maximum value of 34.39363 GB per year when the indicator SSC (number of files archived for the Civil Status Service) has the value 317 files archived. The indicator SEP (number of archived files for the Personal Records Service) has the value of 339 archived files. Similar modeling was done for and for the other indicators f(x1, x3), f(x1, x4), f(x1, x5), f(x2, x3), f(x2, x4), f(x3, x5), f(x3, x5), f(x4, x5). Also, modeling was done for objective functions Y2 (TS) and Y3 (CAD).

Fig. 2. 3D response surface plot resulting from modeling the relationship between the objective function SSCCCP and the variables SSC and SEP

4 Conclusions Creating a digital archive eliminates the need for physical storage space, the documents will not deteriorate, and the search for information in the documents will be high-speed. There is also the possibility of printing the searched information. At the same time, by implementing a digital archive, essential costs will be reduced with the maintenance and

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ensuring the storage conditions, the annual costs for the payment of the archiving services performed by the external company that performs the filing of the documents that must be archived. In order to estimate whether digital archiving can be implemented from a technical point of view, we started by studying the records of the current physical archive, existing from 2009 to 2019. Then, an estimate of the number of files for 20 years was made using a linear regression performed with MINITAB data analysis and graphing software. For document scanning, several scanning methods were tried. After the research was done, the method was chosen: Standard Scanning with Compression and Priority Quality (SSCCCP) because the scanned files have excellent quality and convenient size of the scanned document. The digital storage capacity required to create a digital archive was determined using the chosen scanning method and the estimated number of files, considering that very few files need to be kept permanently. After the end of the archiving term, an essential part of the number of files can be removed from the archive. Therefore, the storage capacity after ten years will increase moderately. An estimate was made of the time required to scan documents and the electricity consumption for scanning. It was found that within the studied organization, there are two services, the Personal Records Service and the Civil Status Service, which, due to their activity, make the most of the archived files. By carrying out the mathematical modeling of the Digital Archiving process, it was confirmed that from a technical point of view, a transition from physical archiving to digital archiving could be made. The existing servers can be used within the organization to host the digital archive, and the storage capacity required for archiving the scanned files can be ensured. Using a digital archive will increase the quality of services offered to citizens, time will be used more efficiently, and savings will be significant.

References 1. Xavier, J.R.A., Robert, A.M., Mathematical Modeling - Encyclopedia of Physical Science and Technology, 3rd edn. Academic Press, New York (2003) 2. T, ît, u, Oprean, Tomut, a˘ : Cercetarea experimental˘a s, i prelucrarea datelor - studii de caz, Editura Universit˘at, ii "Lucian Blaga” din Sibiu, Sibiu (2007) 3. Dubois, G.: Modeling and Simulation - Challenges and Best Practices for Industry. CRC Press, Boca Raton, Florida (2018) 4. Durakovic, B.: Design of Experiments Application, Concepts, Examples: State of the Art, vol. 5, no. 3, Periodicals of Engineering and Natural, pp. 421–439 (2017) 5. Dym, C.L.: Principles of Mathematical Modeling, 2nd edn. Elsevier Academic Press (2004) 6. T, ît, u, A.M., Oprean, C., Boroiu, A.: Cercetarea experimental˘a aplicat˘a în cres, terea calit˘at, ii produselor s, i serviciilor, A.G.I.R., Bucures, ti (2011) 7. Carroll, L., Farr, E., Hornsby, P., Ranker, B.: A comprehensive approach to born-digital archives. Archivaria 72(December), 61–92 (2011) 8. Polhemus, N.: Process Capability Analysis: Estimating Quality. Taylor & Francis Group, USA (2018)

Industry 4.0 Readiness Assesment: Human Resource Readiness and Active Role of Government Administration for Transitional Context of Bosnia and Herzegovina ´ 2 , Savo Stupar2 , and Munira Šesti´c2 Isak Karabegovi´c1(B) , Mirha Biˇco Car 1 Academy of Sciences and Arts of Bosnia and Herzegovina, Sarajevo, Bosnia and Herzegovina

[email protected] 2 School of Economics and Business, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Abstract. For developing countries it is particularly important to create appropriate policies for industrial development in the new context of Industry 4.0. However, as a basis for strategic determination, it is not enough to just assess the readiness of entreprises towards I4.0, knowing that the special challenges of developing countries in promoting and implementing I4.0 are related to human resources (poverty, lack of skills and digital differences), and significantly less state participation in affirmation of I4.0 in relation to developed countries. In this regard, a special challenge is creation of a I4.0 Readiness Assessment Tool for developing countries that would comprehensively assess not only the readiness of entreprises for I4.0, but also human resources readiness as well as the desired role of government. A comprehensive questionnaire would create a basis for an comprehensive review of overall readiness, and the adopted future policies would have a more inclusive and expedient basis for their creation. This paper offers possible proposal for complementing all the mentioned research questions with the aim of determining not only the readiness of enterprises, but also human resources, as well as the desired active role of the state administration through the perception of business actors, all for the transitional context of Bosnia and Herzegovina as a developing country. Keywords: Industry 4.0 · Industry 4.0 Readiness Assessment · Industry 4.0 Human Resources Readiness · Developing country

1 Introduction Industry 4.0 lead to significant progress in numerous segments of the company’s business operations, creating new opportunities, but on the other hand it also brings challenges that are on the path of its implementation. Developed countries are in position to continuously invest in R&D areas within I4.0, which results in the creation of a huge number of innovations and patents that serve as the basis of Industry 4.0. In addition, the developed countries have created strategies aimed at creating context’s conditions for both taking advantage of all the benefits and further development of the fourth industrial revolution, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 389–395, 2023. https://doi.org/10.1007/978-3-031-31066-9_43

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i.e. Industry 4.0, and are investing significantly in its application and further development, all with the goalof proactive action and inclusion in modern business context of competitive global market. Based on national strategies, developed countries support and encourage business subjects to make overall “metamorphosis” towards Industry 4.0. One of the special segments in that spectrum of strategic activities is the continuous monitoring the degree of implementation of Industry 4.0, with the aim of agitate and undertake adequate actions in this regard. Unlike them, for most developing countries the Industry 4.0 concept is mostly new and unused. However there are proactive companies that are familiar with I4.0 trends and have strategic commitments to further implement I4.0 technologies, solutions and methods, but in general, minor number of business subjects in developing countries implement the concept of Industry 4.0.in full capacity comparing to the developed countries. Due to their specific status, developing countries have either only recently adopted national strategies for Industry 4.0 or are just beginning the procedure of its adoption. Moreover, business subjects in developing countries, including Bosnia and Herzegovina, are additionally facing special impediments when implementing Industry 4.0, starting with a lack of information and high complexity of technology, and consequently extremely high application costs.[1]. Additionally, a significant number of developing countries also face special impediments in widening, expansion and implementing technologies I4.0 [2], namely poverty, lack of skills and digital divides among their population. Considering that I4.0 demandadvanced skills for different and new job positions to enable massive digital changes [3], the question arises whether companies in developing countries will have difficulties to successfully adopt all aspects of Industry 4.0 due to mismatch of the required profile of employees, and further more due to lack of investment, the reluctance, and lack of support. Developing countries depend on national policy responses and partnerships to prepare adequate science, technology and innovation policies appropriate to their level of development - in order to prepare people and companies for the period of rapid change required by Industry 4.0 [4]. According to the abovementioned, the question arises as to whether the mentioned challenges of developing countries create space for additional attention to the instrumentation – tool that assesses the degree of the I4.0 implementation. This paper will try to offer an answer and a framework for assessing the readiness of developing countries in relation to the listed challenges that these countries face while implementing Industry 4.0.

2 Literature Review In developing countries companies are dominantly engaged in fabrication, and they are in lower-skill part of global value chains. On the other side, companies from developed countries perform more research and development functions, with China and the United States of America as leaders in investment and capacity in Industry 4.0 technologies, and both acting as a base to the largest digital platforms [5]. An Industry 4.0 readiness assessment describes a company’s preparedness to implement major change or to take on new capabilities, products, or business models. It is

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audit process that examine resources and capabilities of the companies in focus of the assesment. There are several readiness assessment tools created for companies to ratetheir readiness in introducing, processing and further developing for Industry 4.0., having different dimensions of measurement. The development of readiness assessment models for Industry 4.0 in advanced form started on in 2015, with Foundation of the German Engineering Federation presenting the “Industrie 4.0 Readiness” model [6]. Further on, Schumacher et al. [7] developed a maturity model for companies, with nine selected dimensions to rate its present implementation phase with result rang from „not implementing “to” fully implemented“ for each dimension with different weight factor. Later on Warwick University developed an Uni-Warwick assessment tool as simple assessment path for companies to measure both readiness and goals within digitalization [8]. Furthermore self-assessment approaches in online format were also presented by BCG, McKinsey and PWC [9–11]; for example, PwC create assessment tool not only as a tool to assess the readiness of company but also as facing the challenges of digitalization, such as security, legal, and taxation [12]. Human capital is essential for technological learning and innovation [5]. Companies are aware of the need for their employees to have and further acquire key knowledge and skills of work within Industry 4.0, enabling new human role in production processes [13]. The role of HRM in Industry 4.0 implementation has been recognized [14–16], with authors suggesting that human resource strategies represent a key advantage for taking in the opportunities of the forth industrial revolution [17, 18]. Yet, therediness issue of HR for Industry 4.0 is modestly discussed in scholar’s literature and accordingly through assessment [19]. Having in mind that developing countries, like Bosnia and Herzegovina, face three main challenges in promoting and implementing advanced technologies [2]: – Economic and social poverty issues; – Lack of people’sskills; – Digital differences (for example, particularly pronounced technological shortcomings of a stable and fast fixed Internet connection). Therefore, it is clear that developing countries should direct special attention within the assessment of their readiness for Industry 4.0 to the readiness of the human factor to implement and exploit the advantages of Industry 4.0 [20]. The importance of the Government’s role is emphasized, because Industry 4.0 has a perspective development dimension as it can reduce the gap between countries with developed and developing countries. Governments can create an enabling context where inventions could be monetized as Industry 4.0 will: increase wealth by reducing the distance between inventors and market; increase productivity: expand consumer choices: create new forms of financial services: empower small and medium-sized enterprises; creates disruption in the labour market [4]. All these context challenges will require governmental response, inclusiveness and collaboration among stakeholders with major question of balancing the interests of the public and continuious support for innovation and technology development. Governments will be in position for need to improve their

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agility, and regulators able to create policies and regulations in real time, continuously adapting to fast-changing context [21]. Governmental support is important component of success of strategy of development of Industry 4.0. as well as the organizational and managerial component for development of recommendations and its practical implementation for developing countries [2, 22].

3 Conceptual Framework All noted challenges and particularities facing developing countries emphasize the need for the assessment of the readiness of business entities, the human factor and the role of the government administration to be specially dimensioned and evaluated for Industry 4.0 readiness in accordance with the specifics. Analysis of several assessment tools, suggests for their combination [12] in those segments where it is suitable, and this paper futhermore suggest the inclusion of a separate set of questions concerning the readiness of employees in developing countries, their values and skills, and the identification of government administration activities recognized by business entities as desirable for createing a pro-active context for the implementation and development of Industry 4.0. The “Industry 4.0 Readiness” is model formatted by the IMPULS Foundation of the German Engineering Federation, IW Consult and the Institute for Industrial Management at RWTH Aachen University [6]. It is designed with simple and effective focus that allow companies to conduct both on-line and self-check by themselfs. The IMPULS’s tool measures six dimensions[12]: strategy and organization, smart factory, smart operations, smart-products, data-driven services, and employees. Each dimension has several sub-dimensions and the company’s readiness is explained by six levels. The University of Warwick [8], create an Industry 4.0 readiness assessment tool aiming for a simple and intuitive way for companies to portray their readiness and future ambition in Industry 4.0. Their readiness assessment tool is comprehensive in its nature. It consider six core dimensions: products and services; manufacturing and operations; strategy and organisation, supply chain, business model and legal considerations, offering 37 sub-dimensions. Through the assessment process company can build a picture of company’s current Industry 4.0 readiness position, still reflecting company’s future ambition, and furthermore identifying the gaps between current and future desired position [8]. PricewaterhouseCoopers (PwC) offer assessment tool as a tool to assess the I4.0 company readinessas well as the future plans toward industry 4.0. The tool consists of seven dimensions[12]: digital business models and customer access; digitisation of product and service offerings; digitisation and integration of vertical and horizontal value chains; data and analytics as core capability; agile IT architecture; compliance, security, legal and tax; and organisation employees and digital culture, with four levels Industry 4.0 readiness, start from digital novice, vertical integrator, horizontal collaborator, and digital champion [11]. The analysis shows that IMPULS [12] tool is superior in the number of dimensions and categories, while PwC present more attractive online self-assessment tools. On the other hand, Uni-Warwick model serves as a base for the businesses to act proactively [8] to the opportunities of Industry 4.0., aspect that is very important for the business

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entities in developing countries. It is a basic references for new assessment tool creation [12] to be further expanded. Human resources and their readiness, as well as ability to acquire new skills and competencies, are key factors in the success of introducing and implementing Industry 4.0 into businesses and economy [18]. Still, most researches focus on how to learn and develop knowledge and capabilities for a future I4.0 environment - only few investigate the changes induced by Industry 4.0 [23], and classifying needed knowledge and capabilities [19] into areas of: professional, personal and social. Abovementioned skills are expanded with the technical and then classified into “must have skills”, “should have skills” and “can have skills”. Such skills, arising as a result of the digitization trend, show clear similarities to past trends, such as electrification and automation, and the significant socio-economic impacts are also noted [19]. Employees within I4.0 are expected to have the competencies to do the complete job from the beginning to the end [20], in terms of knowledge, skills and competencies, and the also to know the way and have the time to acquire them, and therefore special attention should be given to the human resource readiness in developing countries due to their specifics [2]. Government administration in developing nation [2, 4] can play an important role to create pro-active Industry 4.0 context and further motivate the business entities for further implementation and development of its technologies. The rapid pace of change of the Industry 4.0 therefore encourages [24] the concept of so-called “agile governance administration,” where government bodies and regulatory agencies act together with business and civil society to protect public interests while supporting innovation - the main motive for government administration is a chance to increase national tax revenue and social security contributions by workers whose earnings (income and wealth) will increase due to the Industry 4.0 (high-skilled people) and apply a tax relief for workers whose income will be reduced.

4 Conclusion Developed countries have been the biggest beneficiaries of industrial development. Developing countries need to design and implement policies to take advantage of Industry 4.0, and they cannot afford to miss this new wave of technological change connecting people, equipment and machines [5, 25]. The development balance may shift if developing countries take the necessary measures and tailored assess their readiness for Industry 4.0 and according to the results upgrade regulations, adjust the unsettled innovation climate, develop digital infrastructure and invest in human capital [21, 22]. In order for the readiness of compenies in developing countries to be adequatly assessed, it is necessary to dimension the evaluation instrument that would take into account all the specificities and particularities of developing countries, especially against the challenges that these countries are facing. By combining the existing readiness models, and the distinct inclusion of human resource readiness and the desirable role of the government in context creation, a framework of the readiness model is created that takes into account the challenges and specificities of developing countries, as for Bosnia and Herzegovina.

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All in all, by creating a pro–Industry 4.0 context and navigating the anticipated development all stakeholders in developing country must ensure that their country correctly graded and according to this well prepared at the national, regional and international levels, shaping its objectives and accelerating their potentials to manage the complexity of Industry 4.0 [26]. Acknowledgements. The authors acknowledge the financial support from the Ministry of Science, Higher Education and Youth, Canton Sarajevo, Bosnia and Herzegovina, grant for cofinancing of scientific research/artistic research and research projects of special interest to Sarajevo Canton for 2022. (Number:27-02-35-35137-57/22, Sarajevo: 28.09.2022).

References 1. Karabegovi´c, I., et al.: Industry of Bosnia and Herzegovina within Industry 4.0. In: Karabegovi´c, I. (ed.) Proceedings of the International Conference “Application of Industry 4.0 – an Opportunity for a New Step Forward in all Industrial Branches“, pp. 49–69. Academy of Sciences and Arts of Bosnia and Herzegovina, Sarajevo (2022). https://doi.org/ 10.5644/PI2022.202.20 2. United Nations Industrial Development Organization UNCTAD. Technology and Innovation Report 2021 (2020). https://unctad.org/system/files/official-document/tir2020_en.pdf 3. Jin, S.H., Choi, S.O.: The effect of innovation capability on business performance: a focus on IT and business service companies. Sustainability 11, 5246 (2019) 4. United Nations Industrial Development Organization – UNCTAD Report from the 1st Regional Conference on Industrial Development: Unlocking the Potential of Industry 4.0 for Developing Countries. Asia Pacic. Vienna (2019) 5. United Nations Economic and Social Council - Comission on Science and Technology for development. Industry for Inclusive Development – Report of the Secretary General, March - April, Geneva, Switzerland (2022) 6. Trstenjak, M., Opetuk, T., Cajner, H., Hegedi´c, M.: Industry 4.0 readiness calculation— transitional strategy definition by decision support systems. Sensors (Basel) 22(3), 1185 (2022). https://doi.org/10.3390/s22031185 7. Schumacher, A., Selim, E., Sihn, W.: A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP 52, 161–166 (2016). https://doi. org/10.1016/j.procir.2016.07.040 8. Agca, O., Gibson, J., Godsell, J., Ignatius, J., Davies, C.W., Xu, O.: An Industry 4.0 Readiness Assessment Tool. University of Warwick, Warwick (2017) 9. Boston Consulting Group - BCG, Industry 4.0 Strategy Consulting Services (2022). https:// www.bcg.com/capabilities/manufacturing/industry-4.0. Accessed December 2022 10. McKinsey, Manufacturing’s next Act. https://www.mckinsey.com/business-functions/operat ions/our-insights/manufacturings-next-act. Accessed December 2022 11. PriceWaterhouseCoopers – PWC (2016) Global Industry 4.0 Survey. www.pwc.com/indust ry40 12. Axmann, B., Harmoko, H.: Industry 4.0 readiness assessment: comparison of tools and introduction of new tool for SME. Tehniˇcki Glasnik 14, 212–217 (2020). https://doi.org/10.31803/ tg-20200523195016 13. Plawgo, B., Ertman, A.: Competency needs of Indsutry 4.0 Companies. Central Euro. Manage. J. 29(4), 172–195 (2021)

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14. Cimini, C., Boffelli, A., Lagorio, A., Kalchschmidt, M., Pinto, R.: How do industry 4.0 technologies influence organisational change? An empirical analysis of Italian SMEs. J. Manufact. Technol. Manage. 32(3), 695–721 (2021) 15. Kaasinen„ E., et al.: Empowering and engaging industrial workers with Operator 4.0 solutions. Comput. Indust. Eng. 139, 105678 (2020). https://doi.org/10.1016/j.cie.2019.01.052 16. da Silva, L.B.P., et al.: Human resources management 4.0: Literature review and trends. Comput. Indust. Eng. 168, 108111 (2022). https://doi.org/10.1016/j.cie.2022.108111 17. Shaw, P., Varghese, R.M.: Industry 4.0 future of HR. J. Manage. 5(6), 96–103 (2018) ˇ 18. Rahimi´c, Z., Cizmi´ c, E., Šesti´c, M., Hrnji´c, A.: Differences of the employee perception to the main job design parameters in the context of digitalization. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V. NT 2022. LNNS vol. 472. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_126 19. Vrchota, J., Marikova, M., Rehor, P., Rolinek L., Toušek, E.: Human resources readiness for Industry 4.0. J. Open Innov. Technol. Mark. Complex. 6(1), 3 (2019). https://doi.org/10.3390/ joitmc6010003 ˇ 20. Cizmi´ c, E., Rahimi´c, Z., Šesti´c, M., Ahmi´c, A.: The impact of job design parameters on employee satisfaction and effectiveness in developing countries within digitization context. In: Karabegovi´c, I., Kovaˇcevi´c, A., Mandžuka, S. (eds.) New Technologies, Development and Application V. NT 2022. LNNS, vol 472. Springer, Cham (2022). https://doi.org/10. 1007/978-3-031-05230-9_127 21. United Nations Industrial Development Organization. Sustainable Development Goals: Standards and Digital Transformation – Good Governance in Digital Age (2021) 22. United Nations Industrial Development Organization, Department of Policy, Research and Statistics. Inclusive and Sustainable Industrial Development Working Paper Series WP 19, You say you want a revolution: strategic approaches to Industry 4.0 in middle-income countries (2018) 23. Neumann, W.P., Winkelhaus, S., Grosse, E.H., Glock, C.H.: Industry 4.0 and the human factor – a systems framework and analysis methodology for successful development. Int. J. Product. Econ. 233, 107992 (2021). https://doi.org/10.1016/j.ijpe.2020.107992 24. Schwab, K.: The Fourth Industrial Revolution, WEF (2016) 25. Karabegovi´c, I., Karabegovi´c, E., Mehmi´c, M., Husak, E.: The Application of Industry 4.0 in production Processes of the Automotive Industry. J. Mobil. Vehicle, University of Kragujevac, Faculty of Engineering, Kragujevac, Serbia 47(2), 35–44 (2021) 26. Karabegovi´c, I., Turmanidze, R., Daši´c, P.: Structural network for the implementation of “Industry 4.0” in production processes. Int. Sci. J. “Industry 4.0” Year VII, (1), 3–6 (2022). https://stumejournals.com/journals/i4/2022/1/3.full.pdf

Strategies for Reducing Excess and Obsolete Inventory Emir Halilovi´c1(B) , Hadis Bajri´c1(B) , Kristian Melin2(B) , and Ermin Neimarlija3(B) 1 Faculty of Mechanical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

[email protected], [email protected]

2 Lut University Lahti Campus, Mukkulankatu 19, 15210 Lahti, Finland

[email protected]

3 School of Economics and Business, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

[email protected]

Abstract. This paper provides an overview and list of key reasons for accumulating stagnant inventory, based on research across literatures and in companies. Focusing on the metal, wood, process and pulp and paper industries, research and assessment of the state of obsolete inventory in companies in Bosnia and Herzegovina was carried out. Overview of obsolete inventory in Bosnia and Herzegovina to companies was done through an interwiev based on the questionnaire. The goal of the research was to find the answers: How many companies use software as support for ordering and inventory management? Do companies have criteria for classifying obsolete inventry? How often do companies check and analyze obsolete Inventory. Do they have clearly set KPIs regarding obsolete inventory? What is the allowed participation of obsolete stocks in the total stocks? Etc. In the second part of the paper, the case study is shown. For one production company from the cardboard and cardboard packaging industry, a system was developed for the prevention of excess and obsolete inventory, identification and qualification of obsolete stocks, a strategy for dealing with obsolete inventory was defined and an evaluation of the effect of the implemented strategy was made. Developed inventory management policy and strategies to prevent obsolete inventory were resulted in a 50% reduction in obsolete inventory within the first 40 weeks of project initiation. Keywords: excess inventory · obsolete inventory · prevention of excess and obsolete inventory · strategies for dealing with obsolete inventory

1 Introduction with Literature Overview Inadequate inventory management can result in surplus or outdated stock. This increase of such inventory is negative and causes financial losses for the company, as well as economic and environmental harm to the state. Opinions are divided on the subject of inventories. On one hand, having a large amount of inventory is beneficial for a company. This allows for better planning, increased capacity utilization, flexibility, and improved © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 396–410, 2023. https://doi.org/10.1007/978-3-031-31066-9_44

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customer service. Additionally, it also leads to cheaper procurement and greater bargaining power. On the other hand, inventories come with costs, which can range from 20–50% of their value annually. These opposing views on inventory lead to a significant burden and decrease profitability for the company. 1.1 Excess Inventory When excess stock arises, management must determine which items constitute excess inventory and what actions to take. Often, this type of inventory goes unnoticed due to inadequate identification in the management reporting system [1]. In order to expand and grow a business, management must also evolve by implementing new business models, strategies and tactics. Reducing excess inventory is an effective means of increasing productivity within the company [2]. Proper inventory control is vital as it greatly impacts overall costs. Excess inventory requires additional space, equipment, and labor for transportation, storage, and management without providing added value. Overstocked inventory also makes it harder to identify shortcomings and leads to more waste and inefficiency [3]. Ahmed et al. [4] note that companies aim to avoid excess and obsolete inventory. Obsolete inventory refers to slow-moving, valueless items that take up space and excess inventory is the main cause. Accurate inventory management aims to decrease excess inventory and improve overall supply chain management performance. 1.2 Obsolete Inventory In any product-based business, inventory occupies the most cash and as such, there are many opportunities for savings, one of which is reducing excess and obsolete inventory. Obsolete inventory in inventory management refers to slow-moving or excess inventory that remains unsold for a period of time, resulting in high costs for the company [5, 6]. When a product is approaching the end of its lifecycle, it can be classified as obsolete and slow-moving [7]. Grondys et al. [8] found during their study of mass production that the main reasons for excess and obsolete inventory are changes in technology and equipment (27%), changes in production structure (42%), ordering more parts than needed for servicing equipment (23%), and errors in orders due to differences in construction and technical parameters (8%). When the inventory becomes obsolete, the company can no longer realize the planned economic profit from the inventory, which can significantly affect the company’s profit and operations. With 20–30% of inventory being obsolete, it could be a turning point for struggling organizations to write off this type of inventory as lost and explore other options before doing so [9]. Companies often struggle to recognize the costs associated with long-term inventories and may deny the existence of such inventories by claiming that the products will eventually be used up. The primary question for these companies is how to avoid the existence of obsolete stocks at all [10, 11] and what to do with obsolete stocks? Tulchinsky [12] lists some of the ways to get rid of obsolete inventory: donating obsolete stock

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for tax deduction, remarketing activities, sale with discount, bundle product, write-off of obsolete inventory.

2 Preventing Excess and Obsolete Inventory as Well as Dealing with Them Preventing excess and obsolete inventory can bring significant benefits to a company. It’s essential to note that excess and obsolete stocks come with certain costs, and not keeping track of them will directly increase the costs of holding inventory. Richardson [13] attempted to quantify inventory holding costs annually, which are expressed as a percentage of the total value of stocks in the warehouse, ranging from 25 to 55%. By reducing storage costs, increasing cash flow, and improving inventory turnover rates, a company can achieve higher profits. According to Baker [14], some proactive measures to prevent excess and obsolete inventory include: • • • • •

Accurately forecasting demand. Avoiding the use of excess stock to mitigate supply risks. Ceasing to carry unnecessary inventory to prevent stockouts. Optimizing inventory levels throughout the supply chain. Being cautious when purchasing stock.

To reduce excess inventory, there are several strategies that can be implemented, as listed by Bugs [15]: • One option is to return the excess stock for a refund or credit, despite the transportation and handling costs incurred by the delivery company. • Another approach is to repurpose the inventory by using raw materials or components for the production or development of new products. • Building good relationships with industry partners and exchanging goods with them is also a potential solution. • Selling to end customers or distributors, through special contracts for outdated inventory, is another way to dispose of excess stock. • Another alternative is consignment, where independent distributors take a portion of the sales while the company retains ownership, either virtually or through a consignment distributor who handles the storage and delivery. • Liquidating, auctioning, scrapping, recycling, or donating the excess inventory are also options that can be considered. Donating to non-profit organizations can also help in reducing certain tax obligations. A good basis for the development of an inventory management system can be found in the work of Vandeput [16], Silver et al. [17] and Simchi-Levi et al. [18]. When to order and how much to order in most cases can be obtained through well-explained models (Fixed order period or P model and Fixed order quantity or Q model) in the aforementioned works by Vandeput [16], Silver et al. [17] and Simchi-Levi et al. [18].

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3 Overview of Obsolete Inventory in Companies from Bosnia and Herzegovina Many companies make big mistakes in management methods by neglecting internal control and monitoring of funds, i.e. inventories, while focusing on maximizing sales profit. With the fast-paced technology changes in the fourth industrial revolution, it is impossible to imagine a successful business without detailed monitoring of inventories, including their value, turnover, and obsolescence. A study was conducted to examine the extent to which companies in Bosnia and Herzegovina implement inventory management policies, with a focus on managing obsolete inventories. The research also explored the approach these companies use to reduce the negative impact of obsolete inventory. The research covered 30 companies. The largest number of companies (50%) are from the wood and metal industry, and the research also covers the textile industry, the paper, cardboard and cardboard packaging industry, construction, the PVC and ALU carpentry industry, and sales. The data was collected between 10.01.2022 and 20.04.2022 through interviews and online questionnaires. The most important conclusions are presented below. The largest number of surveyed companies (26,7%) perform an inspection and analysis of obsolete inventory once a year, 13,3% of companies analyze obsolete inventory once a month, 23,3% once a quarter, 16,7% companies do it twice a year, while 20% of companies do not carry out regular inventory analysis (see Fig. 1).

Frequency of analysis of obsolete inventory Once a year

16.7%

26.7%

3.3%

Every half year Every three months Every month

23.3%

16.7% 13.3%

We do not work regularly We have not worked so far

Fig. 1. Frequency of analysis of obsolete inventory

Only 30% of companies have a clearly defined KPI (Key performance indicator) regarding obsolete inventory. The permitted percentage of non-current inventory in companies is about 10% in relation to total stocks. Almost 70% of companies say that they are aware of obsolete inventory, so they classify inventory as obsolete according to time criteria. The most common criterion for obsolete inventory is inventory age greater than 365 days.

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The percentage of obsolete inventory in Bosnia and Herzegovina companies that analyze their inventory every three months or more often is 23%, compared to companies that analyze their inventory every six months, once a year or never, which estimate that they have an average of 11% of obsolete inventory compared to the total stock. Based on this, a wrong conclusion could be drawn that if inventory analysis is performed more often, the percentage of obsolete inventory will be higher (see Fig. 2). The correct interpretation is that companies which do not analyze obsolete inventory regularly do not have data on the amount of obsolete inventory and base their answers on estimates. Some research [9] suggests that obsolete inventory makes up 20% to 30% of total inventory, making the 23% percentage more realistic.

Fig. 2. More often control, more realistic state

Inventories are kept for an average of 75 days in companies, which means that the inventory turnover ratio is only 4.86. According to the answers collected, the average delivery time for incoming goods is 18 days. The largest percentage of companies (40%) takes action to deal with obsolete stock once a year, 33% of companies do it twice a year, while other companies do it more often. It is interesting to note that all companies take action on obsolete inventory at least once a year, although there are companies that do not analyze obsolete inventory at least once a year. Smaller companies mostly manage inventory intuitively. Larger companies are more inclined to use Excel or ERP systems (Fig. 3). As much as 30% of companies implement the inventory policy of when and how much to order intuitively, without the support of an ERP system and without certain internally developed spreadsheets in excel. Companies typically take the following actions to deal with obsolete inventory: alternative use of components and raw materials, sale with discount, promotional actions, donation, sale as secondary raw materials, write-off.

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Fig. 3. Software solutions in inventory control

4 Identification of Management Strategies for Dealing with Excess and Obsolete Stocks in the Cardboard Industry In the second part of this paper, the managing resources system of the cardboard industry is presented, along with strategies for managing excess and obsolete inventory. The best approach to managing excess and obsolete stocks is to prevent their creation in the first place, and then correct any that do exist. This chapter of the case study outlines both preventive and corrective measures for reducing this type of inventory. 4.1 Preventive Measures To effectively manage excess and obsolete stocks, prevention is key. The following actions were carried out as part of the project to achieve this goal: • • • • •

Establishing ordering rules for input raw materials. Establishing a monitoring and reporting system for excess and obsolete inventory. Warehouse layout optimization and warehouse management system. Classification of customers and definition of new contracts. Inventory clustering and defining different inventory management policies for different clusters. • Management system for obsolete, scrap and unclassified products. • Implementation of the SMED (Single Minute Exchange of Die) concept on machines for the production of cardboard packaging. 4.1.1 Establishing Ordering Rules for Input Raw Materials The case study company acquires a small number of different materials and consumes them continuously, so it is appropriate to use replenishment systems based on the EOQ

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model. Raw materials are delivered once or twice a week, so a periodic inventory control system and model was chosen. Managing inventories of finished products are dominantly based on make-to-order system keeping some quantities of safety stocks dependently from agreements with customers. A smaller number of products are based on make-tostock system. Below is a presentation of inventory management of one type of material using a model with a fixed period (P model). Figure 4 shows demand, inventory level according to the existing inventory management policy and inventory level according to the proposed policy based on the developed P model. It can be seen that the implementation of the P model leads to a reduction in average inventory while achieving a projected service level of 95%. In this case, the service level is defined as the percentage of weeks in which no shortage of stock occurred. It can be seen that in this case the level of service achieved is higher than projected. The projected service level is 95%, and the achieved service level is 97.5%, i.e. 38/39, because the stock was exhausted only in the 23rd week. 50000

DEMAND BEHAVIOUR

INITIAL STATE

NEW STATE

40000 30000 [kg]

20000 10000 0

1

3

5

7

9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Week

-10000

Fig. 4. Comparison of the initial inventory policy with the new policy

Table 1. Comparison of the initial inventory policy with the new policy Comparison parameters

Initial inventory policy

New inventory policy New inventory policy for service level of 95% for service level of 90%

Average inventory level in kg

29.070

13.457

11.008

Number of stockout cycles

0

1

1

Stockout quantity in kg

0

353

2.883 (continued)

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Table 1. (continued) Comparison parameters

Initial inventory policy

New inventory policy New inventory policy for service level of 95% for service level of 90%

Achieved service level

100%

97,4%

97,4%

Inventory turnover ratio

6,76

14,6

17,85

Table 1 shows the indicators of the current inventory management approach and the developed P model for projected service levels of 95% and 90%. It is obvious that the spread P model maintains the desired level of service while simultaneously reducing inventory. 4.1.2 Establish a Monitoring and Reporting System for Excess and Obsolete Stocks To implement an inventory control system that prevents excess and obsolete inventory, it is necessary to appoint a responsible person and set standards for categorizing inventory into current and different levels of obsolescence. Additionally, it is crucial to set goals and KPIs for each inventory group, such as inventory turnover, inventory availability, and maximum value of obsolete inventory relative to total inventory.

Obsolete inventory classification sistem 50000 45000 40000 35000 30000 25000 20000 15000 10000 5000 [kg] 0 0. The eigenvalues in this case are λ1 = 21 (μ − μ2 − 4ab) and λ2 =  1 2 2 (μ + μ − 4ab). We can been seen that both eigenvalues be real and different if the 2 μ − 4ab > 0, real and equal if μ2 − 4ab = 0 and conjugate complex if μ2 − 4ab < 0. From the above, we conclude√that the equilibrium point A(0, √ 0) is node. More precisely ab) and unstable for μ ∈ (2 ab, +∞). If the parameter it is stable for μ ∈ (−∞, −2  √ √  μ ∈ −2 ab, 2 ab and μ = 0 equilibrium point A(0, 0) is focus. For μ = 0 this equilibrium point is center. The above consideration can be summarized in the following theorem [1, 5–9]. Theorem 1: The character of the point A(0, 0) is: 

 √  a) for μ ∈ −∞, −2 ab nodal sink,  √  b) for μ ∈ −2 ab, 0 spiral sink, c) center ifμ = 0,  √ d) for μ ∈ 0, 2 ab spiral source,  √  e) for μ ∈ 2 ab, +∞ nodal sources.

Global Dynamics of a Certain Nonlinear System

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Let   us now explore the character of the second equilibrium point B b(b+(−1+b)μ) , −b . a−b  0 −b In this case we find that Df (B) = , detDf (B) = −a + b μ + b(b+μ+bμ−2a(1+μ)) a−b −ab + b2 = b(b − a) and trDf (B) = μ + b(b+μ+bμ−2a(1+μ)) . From the value of a−b the determinant detDf (B), we conclude that if b < a equilibrium point B is saddle point. For b > a sign of detDf (B) is positive. The character of the equilibrium point B further depends on the sign of trDf (B). For the value of parameter

 b2 (1+μ) a at intervals (−1 < μ ≤ 0) ((μ > 0) ∧ (μ ≤ b + bμ) (a < −μ+2b(1+μ) ) or  2  b (1+μ) μ (μ > 0 ∧ a < b ∧ (b + bμ < μ)) or −μ+2b(1+μ) < a < b ∧ (μ < −1) ∧ (b > 1+μ ) value of the sign of trDf (B) < 0. If, in addition to the stated condition, the condition is also satisfied (μ +

b(b+μ+bμ−2a(1+μ)) 2 ) > 4(−ab + b2 ) equilibrium point B is a−b 2 true that it is (μ + b(b+μ+bμ−2a(1+μ)) ) < 4(−ab + b2 ) we a−b

nodal sink. Similar if it is have that equilibrium point B is spiral sink. Let us now determine under what condib2 (1+μ) tions it is trDf (B) > 0. For the value of parameter a at intervals ( −μ+2b(1+μ) 0 ∧ (−1 ≤ μ ≤ 0)) ∨ (μ > 0 ∧ (μ < b + bμ)))) ∨ (μ < −1 ∧ a > μ b2 (1+μ) 1 0 ∧ ((b > 0 ∧ a < b ∧ (b + 1+μ ≤ 1)) ∨ (b > 1+μ ∧ a < −μ+2b(1+μ) ))) worth it trDf (B) > 0. In this case, the equilibrium point B is source. More precisely if it is worth

2 ) < 4 −ab + b2 equilibrium point B is sprial source and it (μ + b(b+μ+bμ−2a(1+μ)) a−b 2

if it is (μ + b(b+μ+bμ−2a(1+μ)) ) > 4(−ab + b2 )) equilibrium point B is nodal source. a−b With this, we have fully examined the character of a given equilibrium point. From the above examination of the character of equilibrium points, we conclude that our system (1) has a very rich dynamics, in different regions of parameters. We will illustrate this in the following figures, where we performed simulations, for certain parameter values. If we analyze the Fig. 1 and Fig. 2 on which the simulation was performed, we can see that some kind of bifurcation may occur in some situations.We see that for different parameter values, there are at least three scenarios related to the equilibrium point A(0, 0). Certainly, the simulation itself is not proof of the existence of this statement, so we will examine whether there is a Hopf bifurcation.  Determine the eigenvalues of Df (A), we find that λ1, 2 = 21 (μ± −4ab + μ2 ). From the expressions for eigenvalues we can see that they will be conjugate complex if −4ab+ √ √  μ2 < 0. Let’s analyze the behavior of a given system when μ ∈ −2 ab, 2 ab , when the eigenvalues obtained are conjugate complex. Write down the eigenvalues in the form λ1, 2 = α(μ) ± β(μ)i. To determine the existence of Hopf bifurcation, the following conditions need to be met, for the value of µ = 0 [10, 13–15]: i. α(0) = 0, β(0) = ω = 0, ii sgn(ω) = sgn ∂g ∂x (0, 0) for µ = 0, ∂α(μ) iii ∂μ = d = 0, for µ = 0,

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,

,

,

Fig. 1. The nullclines of the solution forsome parameter values

iv.









∂3f ∂3g ∂2f ∂2f 1 ∂3f 1 (0, 0) + ∂x∂y 2 (0, 0) + ∂y 3 (0, 0) + 16ω ∂x∂y (0, 0) ∂x 2 (0, 0) 16 ∂x3    2 2 2 2 2 ∂2g + ∂∂yf2 (0, 0) − ∂x∂y (0, 0) ∂∂xg2 (0, 0) + ∂∂yg2 (0, 0) − ∂∂xf2 (0, 0) ∂∂xg2 (0, 0)  2 2 + ∂∂yf2 (0, 0) ∂∂yg2 (0, 0) for μ = 0,

c=

v. c = 0.

Specifically for our observed system (1) we have that α(μ) = μ2 , β(μ) = √ 1 2 we find that d = 21 , β(0) = ab, ∂g 2 4ab − μ . By direct verification ∂x (0, 0) = −1, √ √ , for µ = 0 we have that we finally have that ω = − ab and c = − 3(1+μ) 

8 ab

c = − √3 = 0. From the calculation, we see that the conditions for the existence 8 ab of Hopf bifurcation are satisfied. Then a unique curve of periodic solutions bifurcates from the origin into the region if μ > −1 if cd < 0 and μ < −1 if cd > 0. We can combine all our conclusions in the following theorem. Theorem 2: If −1 < μ < 0, then a) there is a limit cycle which is always stable, b) Hopf bifurcation is supercritical. Proof: a) We have that d = 21 > 0 and therefore the equilibrium point A(0, 0) is unstable [1]. Since the equilibrium point is unstable for given values, the limit cycle is stable [1]. b) Since in this case we have a stable limit cycle surrounding the unstable equilibrium point, by definition, we have supercritical Hopf bifurcation (Figs. 3 and 4).

Global Dynamics of a Certain Nonlinear System

- 1.0

1.0

1.0

0.5

0.5

- 0.5

0.5

1.0

- 1.0

- 0.5

0.5

- 0.5

- 0.5

- 1.0

- 1.0

=

=

=

=

=

0.5

1.0

=

0.5

- 1.0

- 0.5

1.5

- 0.5

- 1.0

=

=

=

Fig. 2. Behavior of the solution for some parameter values

431

1.0

432

V. Hadžiabdi´c et al. k¢¢ 0.0006

0.0004

0.0002

- 0.0003

- 0.0002

- 0.0001

0.0001

0.0002

k 0.0003

- 0.0002

- 0.0004

- 0.0006

Fig. 3. Bifurcations for µ = −0.04

Fig. 4. Bifurcation diagram

3 Conclusion After performing a qualitative analysis depending on the parameters, we concluded in the observed multidimensional system with three parameters, Hop bifurcation occurs. The appearance of the Hopf bifurcation represents the basis of the quasi-periodic path to chaos, which was first observed in the dynamics of the Van der Pol oscillator, whereby the spiral node passes into the boundary cycle through the Hopf bifurcation. Which then

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translates into a torus through another Hopf or Neymar-Sacker bifurcation, after which chaos ensues. Of particular interest is the historical development of the invention of a quasi-periodic solution in chaos. Before foreign attractors were known, the theory of turbulence was generally accepted. Therefore, the dynamics of the system changes from a stable equilibrium state to a limit cycle. Although it is very difficult to determine the complete set of bifurcations that lead to chaos, we can say that Hopf’s bifurcation and the quasi-periodic path to chaos are the most common in applications.

References 1. Verhulst, F.: Nonlinear Differential Equations and Dynamical Systems. Springer, Heidelberg (1990). https://doi.org/10.1007/978-3-642-97149-5 2. Kant, S., Kumar, V.: Dynamics of a preypredator system with infection in prey. Electron. J. Differ. Equ. 209, 1–27 (2017) 3. Fulda, J.S.: The logistic equation and population decline. J. Theor. Biol. 91(2), 255–259 (1981) 4. Seifert, G.: A Lotka-Volterra predator-prey system involving two predators. Methods Appl. Anal. 2(2), 248–255 (1995) 5. Hirsch, M.W., Smale, S., Devaney, R.L.: Differential Equations, Dynamical Systems, and an Introduction to Chaos. Academic press, Cambridge (2012) 6. Hadžiabdi´c, V., Mehulji´c, M., Bekteševi´c, J., Šari´c, I.: Application of the nullcline method to a certain model of competitive species. TEM J. 8(1), 73–77 (2019) 7. Hadžiabdi´c, V., Mehulji´c, M., Bekteševi´c, J., Muji´c, N.: Coexistence between predator and prey in the modified Lotka-Volterra model. TEM J. 7(2), 330–334 (2018) 8. Hadžiabdi´c, V., Mehulji´c, M., Bekteševi´c, J.: Lotka–Volterra model with two predators and their prey. TEM J. 6(1), 132–136 (2017) 9. Imamovi´c, Z., Hadžiabdi´c, V., Mehulji´c, M., Bekteševi´c, J., Burgi´c, D.: Modified Gauss-type competitive system. In: Karabegovi´c, I. (ed.) NT 2021. LNNS, vol. 233, pp. 1183–1187. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75275-0_131 10. Hadžiabdi´c, V., Mehulji´c, M., Bekteševi´c, J., Maši´c, A.: Dynamics and stability of Hopf bifurcation for one non-linear system.TEM J. 10(2), 820-824 (2021). https://doi.org/10.18421/ TEM102-40 11. Perko, L.: Differential Equations and Dynamical Systems. Springer, Heidelberg (2001). https://doi.org/10.1007/978-1-4613-0003-8 12. Hadžiabdi´c, V., Mehulji´c, M., Bekteševi´c, J.: Stability of non-hyperbolic equilibrium point for polynomial system of differential equations. TEM J. 10(3), 1418–1422 (2021). ISSN 2217-8309. https://doi.org/10.18421/TEM103-52 13. Guerrini, L.: Hopf bifurcation analysis of a dynamical heart model with time delay. Appl. Math. Sci. 11(22), 1089–1095 (2017) 14. Kuznetsov, Yu.A.: Elements of Applied Bifurcation Theory, 3rd edn. Springer. New York (2004). https://doi.org/10.1007/978-1-4757-3978-7 15. Scott, A. (ed.): Encyclopedia of Nonlinear Science, 1st edn. Routledge (2005). https://doi. org/10.4324/9780203647417

The Global Behavior of a Certain General Difference Polynomial Equation Jasmin Bekteševi´c1(B) , Vahidin Hadžiabdi´c1 , Midhat Mehulji´c1 , Adnan Maši´c1 , and Fatih Destovi´c2 1 Faculty of Mechanical Engineering, Department of Mathematics and Physics,

University of Sarajevo, St. Vilsonovo šetalište 9, 71 000 Sarajevo, Bosnia and Herzegovina [email protected] 2 Faculty of Educational Sciences, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Abstract. We investigatea polynomial difference equation of type   xn+1 = P(xn )xn−1 + P xn−1 xn−1 + bxn−1 , n = 0, 1, 2, . . . in the positive quadrant with initial conditions (x−1 , x0 ) for which it has been fulfilled b ≥ 0, 2P(0) + b < 1 and P(x) is polynomial with nonnegative coeffcients. We find explicit equation of the planar curve that separates basins of attraction for theequilibrium point what is the infinity and explore locally asymptotically stable (LAS) zero equilibrium point. Keywords: basin of attraction · period-two solutions · local stabilityof equilibrium points · global dynamics · equilibrium

1 Introduction In this article, we aim to examine global dynamicsof difference equation of type xn+1 = P(xn )xn−1 + P(xn−1 )xn−1 + bxn−1 , n = 0, 1, 2, . . .

(1)

where parameter b is nonnegative number with condition 2P(0) + b < 1, P(x) is the polynomial with nonnegative coeffcients and initial conditions (x−1 , x0 ) lie in the first quadrant, which we can also say is of polynomial type. The goal of our research is an attempt at establishing some global dynamics results for the equilibrium solutions of (1). One can show that (1) has two equilibrium points (locally asymptotically stable (LAS) zero equilibrium and positive non-hyperbolic equilibrium point) and infinitely many prime solutions that have period two. We have shown that all two-cycles lie on the curve that divides positive quadrant of initial conditions into two parts: all solutions which start below the mentioned curve converge to the zero equilibrium, while all solutions which start above the curve approach to the point at infinity. Polynomial difference equations were studied by many authors (see [1–6]). The study about quadratic polynomial difference equation started in [7, 8], but precise results are given in [9]. The polynomial second order difference equation with infinitely many prime © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 434–441, 2023. https://doi.org/10.1007/978-3-031-31066-9_48

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435

period-two solutions (see [10]) is special case of (1) for P(x) = ax, these are equations that have the following form: 2 xn+1 = axn xn−1 + axn−1 + bxn−1 .

In [11], we have extended our research to equation of type m+1 m xn+1 = axn xn−1 + axn−1 + bxn−1 , m ∈ N,

which is special case of Eq. (1) for P(x) = axm . Our results are basedon the theory of cooperative maps, which can be applied to systems of the type: un+1 = vn and vn+1 = f (vn , un ) where f (x, y) is a continuous function,with the feature that it is increasing in x and y. Based on that we have guarantee the existence and uniqueness manifolds that are stable or unstable, for the fixed points and periodic points (see [12]). For un = xn−1 and vn = xn we find results whichare based are based on results related to monotone difference equations of type xn+1 = f (xn , xn−1 ). Using results and theorems on global attractiveness about monotone difference equations, we can also provide and establish results about solutions and behavior of our Eq. (1). We now give some basic notions about difference equations of type xn+1 = f (xn , xn−1 ). We will use the results given in the reference [12]. Significance of results and theorems from [12] consists in the fact that these results give guarantee existence of the two invariant continuous curves W s (E2 ) (stable manifold - graph of a decreasing function) and W u (E2 ) (unstable manifold - graph of an increasing function), both contain the fixed point (hyperbolic or saddle) E2 from Theorem 1. The stable manifold W s (E2 ) divides the positive quadrantinto two disjoint invariant parts (in general, planar rectangular regions). To establish the results related to Eq. (1), we will also use the results from [13], especially the part related to Theorem 1.1 in [13], as well as the labels used in this x) x) and q = ∂f (x, paper, p = ∂f (x, ∂u ∂v , we will mark with λ1 , λ2 solutions relating to λ2 − pλ − q = 0. In addition to the results given in [12, 13], we will also use the results given in [14], which refer tocompare solutions of nonlinear equations to equations with known dynamics (in terms).

2 Main Results For equilibrium points x of Eq. (1) are the nonnegative solutions of x(2P(x) + b − 1) = 0. Clearly, Eq. (1) always has zero equilibrium. If we set g(x) = 2P(x) + b − 1, then   g(0) = 2P(0) + b − 1 < 0, g(+∞) = +∞ and g (x) = 2P (x) > 0 for all x > 0 (g is increasing function) which implies the equation g(x) = 0 ⇐⇒ 2P(x) + b = 1 has exactly one positive solution x = x+ or we deduce that Eq. (1) always has one positive equilibrium point x = x+ .

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Lemma 1: Our Eq. (1) always has two equilibrium points, one as zero and the other as positive, which is unique. Let P(x) be the polynomial with nonnegative coeffcients and let f (x, y) be a monotone and continuous map defined by f (x, y) = P(x)y + P(y)y + by. In our case we have that it is p = 

∂f (x, x) ∂x



= P (x)x ≥ 0+ and q =

∂f (x, x) ∂y

= 2P(x) +

P (x)x + b ≥ 0. Obviously, for x = 0, we obtain p = 0 and q = 2P(0) + b ∈ (0, 1). The next two statements give answers related to the local stability of zero and positive equilibrium. Proposition 1: If 2P(0) + b < 1, then the zero equilibrium of Eq. (1) is always LAS. Proposition 2: If 2P(0) + b < 1, the positive equilibrium x of Eq. (1) is non-hyperbolic point. Proof. Clearly, if 2P(0) + b < 1, then x = x+ is only positive equilibrium of Eq. (1). After straightforward calculation we get p + q = 2P(x) + 2P  (x)x + b ≥ 0, . q − p = 2P(x) + b = 1. One can see that |p| = |1 − q|, so we deduce that the conditions from [13] are not satisfied, which yield s x = x+ has a non-hyperbolic character. Theorem 1: If 2P(0) + b > 1, then for all solutions {xn } of (1) we have that it is valid lim xn = ∞.

n→∞

Proof. If {xn } is solution of Eq. (1), then {xn } satisfies inequality xn+1 = xn−1 (P(xn ) + P(xn−1 ) + b) ≥ (2P(0) + b)xn−1 . As a consequence of Theorem 3, we get xn ≥ yn , n ≥ 1 where {yn } is given by yn+1 = (2P(0) + b)yn−1 , y−1 = x−1 and y0 = x0 , n = 0, 1, . . . Consequently, x−1 , x0 > 0 then y−1 , y0 > 0 for all n and   n  n xn ≥ yn = λ1 2P(0) + b + λ2 − 2P(0) + b , n = 1, 2, . . . where are λ1 = ∞.

y0 +y−1 2(2P(0)+b)

and λ2 =

y0 −y−1 2(2P(0)+b)

such that yn ≥ 0 for all n, thus lim xn = n→∞

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Theorem 2: Let P(x) be the polynomial with nonnegative coeffcients and suppose that the function f : [0, ∞) × [0, ∞) → [0, ∞) is given in the following way f (x, y) = P(x)y + P(y)y + by with the following properties: b ≥ 0 and 2P(0) + b < 1. Let 0 and x+ are the equilibria of Eq. (1). In that case, the curve given by P(x) + P(y) + b = 1 separates the set [0, ∞) × [0, ∞) into two parts: B(0, 0) = {(x, y) : P(x) + P(y) + b < 1}, B(∞) = {(x, y) : P(x) + P(y) + b > 1}. Let’s notice that every point that belongs toset {(x, y) : P(x) + P(y) + b = 1}\{(x+ , x+ )} is a two cycle of Eq. (1). Proof. From Lemma 1 we have Eq. (1) always has zero and unique positive equilibrium points. In view of the above restriction 2P(0) + b < 1 the Proposition 1 implies the zero equilibrium is LAS. Since 2P(x+ ) + b = 1, based on Proposition 2, we deduce that the second equilibrium point has a non-hyperbolic. Assume that (φ, ψ) is a prime a solution that has period twoof Eq. (1). Then φ = φ(P(ψ) + P(φ) + b) and ψ = ψ(P(φ) + P(ψ) + b), which is true if (φ, ψ) = (0, 0) so it has to be P(ψ) + P(φ) + b = 1. Hence, all two cycle of Eq. (1) are described by the set {(φ, ψ) : P(φ) + P(ψ) + b = 1} \ {(x+ , x+ )}. Let for some fixed x > 0 there exist y1 and y2 (0 < y1 < y2 ) such that (x, y1 ), (x, y2 ) ∈ {(x, y) : P(x) + P(y) + b = 1}. The polynomial P(t) is increasing function for all t > 0 which yields 1 = P(x) + P(y1 ) + b < P(x) + P(y2 ) + b = 1, which is impossible, so the curve P(x) + P(y) + b = 1, represents a function in the (positive) first quadrant. Furthermore, by computing the first derivative of the implicit function P(x) + P(y) + b = 1 we have 





P (x) + P (y)y = 0 



which is equivalent to y = − P  (x) < 0, for all x, y > 0. Now, one can conclude that the P (y) curve P(x)+P(y)+b = 1 is the graph of decreasing function in the positive quadrant. Set y) ∂h(x, y) = ∂P(x) = ∂P(y) h(x, y) = P(x)+P(y)+b. Since ∂h(x, ∂x ∂x > 0 and ∂y ∂y > 0, we deduce that h(x, y) is increasing function in x and in y on [0, ∞) × [0, ∞). Assume that {xn } is solution of Eq. (1) for (x0 , x−1 ) with the properties h(x0 , x−1 ) < 1 (the point (x0 , x−1 ) is under the curve h(x, y) = 1). We now proceed to show that (0, 0)ne (x2n , x2n−1 )ne (x0 , x−1 ) for all n > 0. Indeed, h(x0 , x−1 ) < 1 and xn+1 = xn−1 h(xn , xn−1 ).

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Now, x1 = x−1 h(x0 , x−1 ) < x−1 , and x2 = x0 h(x1 , x0 ) < x0 h(x−1 , x0 ) = x0 h(x0 , x−1 ) < x0 . One can see that (x2 , x1 ) and (x0 , x−1 ) are in North-East ordering (x2 , x1 )ne (x0 , x−1 ) which yields h(x2 , x1 ) < 1 (the point (x2 , x1 ) is under the curve h(x, y) = 1). Similarly, we also find that x3 = x1 h(x2 , x1 ) < x1 , and x4 = x2 h(x3 , x2 ) < x2 h(x1 , x2 ) = x2 h(x2 , x1 ) < x2 . Using this methodwe have (0, 0)ne . . . ne (x2n , x2n−1 )ne . . . ne (x4 , x3 )ne (x2 , x1 )ne (x0 , x−1 ). Hence, both subsequences {x2n } and {x2n−1 } of the solution {xn } of Eq. (1) are monotonically decreasing, limited from below with 0. So here the solution of (1) converges to a zero equilibrium and this is a consequence of the fact thatthere are no prime period-two solutions below the given curve. To complete the rest of proof, assume that h(x0 , x−1 ) > 1 (the initial condition (x0 , x−1 ) lies above curve h(x, y) = 1). This case can be handled in similar way, so one can show that (x2n , x2n−1 )ne . . . ne (x4 , x3 )ne (x2 , x1 )ne (x0 , x−1 ). Hence, the both subsequences of even and odd terms of the solution of Eq. (1) are monotonically increasing. Since Eq. (1) has no equilibrium points or prime period-two solutions above the curve h(x, y) = 1, we deduce that both subsequences {x2n } and {x2n−1 } converge monotonically to infinity. 1 The following Fig. 1 presents previous theorem for P(x) = 21 x2 + 21 x + 16 , b = 18 1 and x+ = 2 . Next we present application of our main result (Theorem 2). Proposition 3: Observe the following equation xn+1 = P(xn )xn−1 + Q(xn−1 )xn−1 + bxn−1 , (3)

(3)

  i with nonnegative initial conditions where P(x) = si=0 ui xi , Q(x) = ti=0 vr i x are the polynomials with nonnegative coeffcients. Let r = max{s, t} and m(x) = i=0 min{ui ,  vi }xi and M (x) = ri=0 max{ui , vi }xi .

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1 , b = 1 and x = 1 Fig. 1. Presentation of Theorem 2 for P(x) = 21 x2 + 21 x + 16 + 8 2

Assume that b ≥ 0, 2m(0) + b < 1 and 2M (0) + b < 1. Therefore the global stable manifold passing through the point (x+ , x+ ), where x+ is the positive solution of Eq. (3), is between two curves: p1 : m(x) + m(y) + b = 1 and p2 : M (x) + M (y) + b = 1. Proof. Let g : [0, ∞) × [0, ∞) → [0, ∞) be a function defined by. g(x, y) = P(x)y + Q(y)y + by. It is not difficult toverify that Eq. (3) has exactly two equilibrium points: zero and unique positive x+ . If we set z(x) = P(x) + Q(x) + b − 1, then z(0) = P(0) + Q(0) + b − 1 < 2M (0) + b − 1 < 0, 





z(+∞) = +∞ and z (x) = P (x) + Q (x) > 0 for all x > 0 (z is increasing function) which implies the equation z(x) = 0 (or equivalently P(x) + Q(x) + b = 1) has exactly one positive solution x = x+ . For zero equilibrium x = 0 we get p=

∂g(0, 0) ∂g(0, 0) = 0andq = = P(0) + Q(0) + b < 2M (0) + b < 1. ∂x ∂y

As a consequence of Theorem 2, the zero equilibrium is always LAS. Since the zero equilibrium and the positive x+ are two consecutive equilibriums in oredreding

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of North-East, we deduce that x+ must be unstable.In this case we have at most two scenarios: either the equilibrium x+ is a saddle point (non-hyperbolic) or a repeller. Since we require x+ be unstable, then the results applied in [12] give the next global behavior. If x+ is a saddle point or a non-hyperbolic,therefore there exists a global stable manifold W s (E) passing through the point E(x+ , x+ ). In this case global dynamics of Eq. (3) follows from Theorem 9 in [9]. On the other hand, if the equilibrium x+ is a repeller, then there exists a prime period-two solution (φ, ψ) of Eq. (3) whichis a saddle point. This implies there are two global stable manifolds W s (P1 ) and W s (P2 ), both passing through the points P1 (φ, ψ) and P2 (ψ, φ). Finally, the global dynamics of (3) is given by Theorem10 in [9]. Let yn+1 = m(yn )yn−1 + m(yn−1 )yn−1 + byn−1

(4)

zn+1 = M (zn )zn−1 + M (zn−1 )zn−1 + bzn−1 .

(5)

and

Using [14] every solution {xn } of (3) satisfiesthe following inequality yn ≤ xn ≤ zn for all n. The rest of proofof Proposition 3 follows from the fact that Eq. (4) and (5) satisfy all conditions given in [13].

3 Conclusion In our research we investigatedthe certain polynomialsecond order difference equation Eq. (1). We have determined the basins of attractions of all equilibriumsof Eq. (1). Also, we found an explicit formulafor curve that dividespositive quadrant into two regions. In general, the computation of approximations of the global stable manifold(s) leadsus to the calculation which are very difficult to implement (see [15, 16]).

References 1. Bedford, E.: Complex Henon maps with semi-parabolic fixed points. J. Differ. Equ. Appl. 16, 425–426 (2010) 2. Bedford, E., Smillie, J.: Real polynomial diffeomorphisms with maximal entropy: tangencies. Ann. Math. 160(2), 1–26 (2004). No. 1 3. Bedford, E., Smillie, J.: Real polynomial diffeomorphisms with maximal entropy II: small Jacobian. Ergodic Theory Dyn. Syst. 26(5), 1259–1283 (2006) 4. Bonifant, A., Kiwi, I., Milnor, J.: Cubic polynomial maps with periodic critical orbit, Part I: escape regions. Conform. Geom. Dyn. 14, 68–112 (2010) 5. Bonifant, A., Kiwi, I., Milnor, J.: Errata for cubic polynomial maps with periodic critical orbit, Part II: escape regions. Conform. Geom. Dyn. 14, 190–193 (2010) 6. Fornaess, J.E., Sibony, N.: Compex Henon mappings in C2 and Falou-Bieberbach domains. Duke Math. J. 65(2), 345–380 (1992)

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7. Amleh, A.M., Camouzis, E., Ladas, G.: On the dynamics of a rational difference equation, Part I. Int. J. Differ. Equ. 3, 1–35.B (2008) 8. Amleh, A.M., Camouzis, E., Ladas, G.: On the dynamics of a rational difference equation, Part II. Int. J. Differ. Equ. 3, 195–225 (2008) 9. Bekteševi´c, J., Kulenovi´c, M.R.S., Pilav, E.: Global dynamics of quadratic second order difference equation in the first quadrant. App. Math. Comp. 227, 50–65 (2014) 10. Bekteševi´c, J., Hadžiabdi´c, V., Mehulji´c, M., Muji´c, N.: The global behavior of a quadratic difference equation. Filomat 32(18), 6203–6210 (2018) 11. Bekteševi´c, J., Hadžiabdi´c, V., Mehulji´c, M., Muji´c, N.: The global behavior of a certain difference polynomial equation. Filomat 35(11), 3901–3908 (2021) 12. Brett, A., Kulenovi´c, M.R.S.: Basins of attraction of equilibrium points of monotone difference equations. Sarajevo J. Math. 5(18), 211–233 (2009) 13. Kulenovi´c, M.R.S., Ladas, G.: Dynamics of Second Order Rational Difference Equations with Open Problems and Conjectures. Chapman and Hall/CRC, Boca Raton (2001) 14. Camouzis, E., Ladas, G.: Dynamics of Third Order Rational Difference Equations with Open Problems and Conjectures. Chapman and Hall/CRC, Boca Raton London (2008) 15. Bekteševi´c, J., Kulenovi´c, M.R.S., Pilav, E.: Asymptotic approximations of the stable and unstable manifolds of fixed points of a two-dimensional cubic map. IJDE 10(1), 39–58 (2015) 16. Bekteševi´c, J., Kulenovi´c, M.R.S., Pilav, E.: Asymptotic approximations of the stable and unstable manifolds of the fixed points of a two-dimensional quadratic map. J. Comput. Anal. Appl. 21(1), 35–51 (2016)

Local Dynamics and Global Behavior of Certain Second Order Nonlinear Difference Equation Midhat Mehulji´c(B) , Jasmin Bekteševi´c, Vahidin Hadžiabdi´c, Sadjit Metovi´c, and Adnan Maši´c Faculty of Mechanical Engineering, University of Sarajevo, St. Vilsonovo šetalište 9, 71 000 Sarajevo, Bosnia and Herzegovina [email protected]

Abstract. In this paper we observed a certain rational difference equation of the second order with quadratic terms. The local stability of this equation was fully tested and the absence of periodic solutions of period-two was proven. The stability of the zero equilibrium has been proven for all values of positive parameters, while depending on the positive parameters, two, one or no equilibria may occur. The equation is bounded on both sides. Four conjectures are given for the remaining parameter values for which the global dynamics were not examined. Their reason is the simulations that were made and listed in the paper. Keywords: boundness · equilibrium · period-two solutions · local stability · global stability

1 Introduction A general rational second order difference equation with quadratic terms of the form xn+1 =

2 Axn2 + Bxn xn−1 + Cxn−1 + Dxn + Exn−1 + F 2 bx x 2 axn+ n n−1 + cxn−1 + dxn + exn−1 + f

, n = 0, 1, . . . ,

(1)

where A, B, C, D, E, F, ab, c, d , e, f ≥ 0 and A + B + C + D + E + F > 0 and a + b + c + d + e + f > 0 and where the initial conditions x−1 and x0 are arbitrary nonnegative real numbers such that x−1 + x0 > 0. Many special cases of Eq. (1) have been considered earlier, for more details see [1–9]. In this paper we studied a differential equation of the form xn+1 =

Axn2 , axn2 + bxn xn−1 + c

where A, a, b, c > 0, which using the shift xn →

c xn , A

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 442–449, 2023. https://doi.org/10.1007/978-3-031-31066-9_49

(2)

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is reduced to the equation xn+1 =

xn2 , αxn2 + βxn xn−1 + 1

(3)

where α = Aac2 > 0 and β = Abc2 > 0. The mapping associated with Eq. (3) has the property that it is monotonically increasing in the first variable, and monotonically decreasing in the second variable. This form of monotonic mapping tells us that we are dealing with equations that have quite complicated dynamics and for the study of which there is no detailed developed theory, in contrast to equations that have the characteristic that the associated mapping is monotonically decreasing in the first variable and monotonically increasing in the second variables, as is the case with the equations considered in [10]. Now, one can see that holds the following inequality xn+1 =

1 xn2 < αxn2 + βxn xn−1 + 1 α

which implies that every solution {xn } of Eq. (3) is bounded. Regardless of the boundness of the solution of Eq. (3) and to the specified monotonicity of the associated mapping for Eq. (3) it is not possible to apply the forced linearization method used in [11].

2 Analysis of Local Stability The equilibrium points of Eq. (3) are the solutions of equation   x (α + β)x2 − x + 1 = 0. We always have the zero equilibrium and in addition to the zero equilibrium the Eq. (3) has: i) no positive equilibriums if 4(α + β) > 1, ii) one positive equilibrium x = 2 if 4(α√ + β) = 1, 1−4(α+β) iii) two positive equilibriums x1,2 = 1± 2(α+β) if 4(α + β) < 1. Let’s investigate local stability of the nonnegative equilibrium applying linearized stability Theorem in [1]. If we put f (u, v) =

u2 , αu2 + βuv + 1

then ∂f u(βuv + 2) = 2 ≥ 0 ∂u αu2 + βuv + 1 and −βu3 ∂f = 2 ≤ 0. ∂v αu2 + βuv + 1

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Let x be an equilibrium point of difference equation Eq. (3) and let p=

x(βx2 + 2) ∂f (x, x) =  2 ∂u (α + β)x2 + 1

q=

−βx3 ∂f (x, x) =  2 ∂v (α + β)x2 + 1

and

denote the partial derivatives of f (u, v) evaluated at the equilibrium point x. Theorem 1: Let x be an equilibrium point of difference Eq. (3), then: i) the zero equilibrium is always locally asymptotically stable. ii) If 4(α + β) = 1, only equilibrium point x = 2 is the nonhyperbolic point. iii) If 4(α + β) < 1, then equilibrium point x1 is unstable saddle point and x2 is the locally asymptotically stable equilibrium point.

Proof:

i)

It easy to verify that hold p=

∂f ∂f (0, 0) = 0 and q = (0, 0) = 0, ∂u ∂v

thus by the linearized stability Theorem [1], the zero equilibrium is always locally asymptotically stable. ii) If 4(α + β) = 1, then Eq. (3) has one positive equilibrium x = 2. Now p= and q=

∂f (2, 2) = 2β + 1 ∂u

  ∂f 1 (2, 2) = −2β ∈ − , 0 , ∂v 2

and p+q = 1 ⇔ |p| = |1 − q|. So the equilibrium point x = 2 is the nonhyperbolic point. √ 1−4(α+β) iii) If 4(α + β) < 1, then Eq. (3) has two positive equilibriums x1,2 = 1± 2(α+β) (x1 < x2 ) and by using the fact that (α + β)x2 + 1 = x we have that p=

 ∂f 2 (x, x) = 3x + > 2 2β ∂u x

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and q=

445

  ∂f 1 (x, x) = −βx ∈ − , 0 . ∂v 2

For equilibrium x1 we have that p+q=

 4(α + β) 2 = = 1 + 1 − 4(α + β) > 1. √ x1 1 − 1 − 4(α + β)

  So, p + q > 1 and q ∈ − 21 , 0 which implies that |p| > |1 − q| and it obvious that p2 + 4q > 0. Finaly, equilibrium point x1 is the saddle point. For equilibrium x2 we have that  4(α + β) 2 = = 1 − 1 − 4(α + β) < 1. √ x2 1 + 1 − 4(α + β)   Hence, p + q < 1 and q ∈ − 21 , 0 which implies that |p| < 1 − q < 2. So, equilibrium point x2 is the locally asymptotically stable. p+q=

3 Period-Two Solution and Stability Period-two solutions . . . , , , , , . . . satisfy the system = =

2 α 2 + β + 1 α2

2 , + β + 1

from which we conclude that (α − 1)( + ) = β + 1. If α < 1 then the period-two solution does not exist. In next section, we’ll see that if α > 1, then every solution {xn } of Eq. (3) with initial condition x−1 , x0 ∈ (0, ∞) converges to zero equilibrium. Therefore, in this case we don’t need to find condition for existence of period-two solution and investigate its stability.

4 Analysis of Global Dynamics Conjecture 1: If 4(α + β) > 1, then every solution {xn } of Eq. (3) is eventually monotonically decreasing. Conjecture 2: If 4(α + β) > 1, then every solution {xn } of Eq. (3) with initial condition x−1 , x0 ∈ [0, ∞) converges to zero equilibrium. Theorem 2: Let one of the following statements is true

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i) 4(α + β) > 1 and there is a nonnegative integer k such that xk ≤ 1, ii) 4α ≥ 1, then every solution {xn } of Eq. (3) with initial condition x−1 , x0 ∈ [0, ∞) converges to zero equilibrium. Proof: i) If there is k ∈ N 0 such that xk ≤ 1, then xk+1 = xk+2 =

xk2 αxk2 + βxk xk−1 + 1 2 xk+1

2 αxk+1 + βxk+1 xk + 1

< xk2 < xk ≤ 1,

2 < xk+1 ≤ 1, < xk+1

and continuing on this we have that xn+1 < xn for all n ≥ k. Since 0 < xn < α1 , it implies that {xn } is convergent and xn → 0, when n → ∞. ii) If 4α ≥ 1, then 4(α + β) > 1 and xn+1 xn 1 xn < 2 ≤ √ ≤ 1, = 2 xn αxn + βxn xn−1 + 1 αxn + 1 2 α So {xn } is monotonically decreasing, as it is bounded it implies that it is convergent. Hence xn → 0, when n → ∞. Remark 1: Now, let suppose that there is no  positive integer k such that xk ≤ 1, it implies that xn > 1 for all n and let α ∈ 0, 41 . In this case we have xn xn−1 1 xn+1 xn < 2 < . = 2 xn αxn + βxn xn−1 + 1 αxn + βxn xn−1 + 1 β Thus, if β ≥ 1 then {xn } is monotonically decreasing, as it holds 1 < xn < α1 it implies that it is convergent, so xn → 0, when n → ∞, which is impossible. Therefore it has to be β ∈ (0, 1) and α + β < 45 . If α + β ≥ 1, then xn xn+1 xn 1 < ≤ 1. = 2 = xn αxn + βxn xn−1 + 1 αxn + βxn α+β which implies   point, which is  that {xn } is convergent and {xn } tends to only equilibrium impossible 1 < xn < α1 . It remains to us to show that if α ∈ 0, 41 , β ∈ (0, 1) and   α + β ∈ 41 , 1 , then xn > 1, for all n is not true. Conjecture 3: If 4(α + β) = 1, then the global dynamics of Eq. (3) is described on the Fig. 1.

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Fig. 1. α = 0.10, β = 0.15, x1 = 0 and x2 = 2.

The green region on Fig. 1 is the basin of attraction of nonhyperbolic equilibrium point x = 2, and the blue region is the basin of attraction of zero equilibrium. Theorem 3: If 4(α + β) = 1 and xk ≤ 1 for some k, then every solution {xn } of Eq. (3) with initial condition x−1 , x0 ∈ [0, ∞) converges to zero equilibrium. Proof: If there is k ∈ N 0 such that xk ≤ 1, then xk+1 = xk+2 =

xk2 αxk2

+ βxk xk−1 + 1 2 xk+1

2 αxk+1 + βxk+1 xk + 1

< xk2 < xk ≤ 1,

2 < xk+1 ≤ 1, < xk+1

and continuing on this we have that xn+1 < xn for all n ≥ k. Since 0 < xn < α1 , it implies that {xn } is convergent and xn → 0, when n → ∞. Now, one can conclude that the rectangle [0, ∞)×[0, 1] is a part of the basin of attraction of the zero equilibrium of Eq. (3). Conjecture 4: If 4(α + β) < 1, then the global dynamics of Eq. (3) is described on the Fig. 2. The green region on Fig. 2 is the basin of attraction of equilibrium point x3 , and the blue region is the basin of attraction of zero equilibrium. Theorem 4: If 4(α + β) < 1 then the box [0, 1]2 is a part of the basin of attraction of the zero equilibrium point. Proof: Clearly, x1 < x02 ≤ x0 ≤ 1, x2 < x12 ≤ x1 < 1, and continuing on this we get xn+1 < xn , for all n ≥ 0. As xn is bounded then it is a convergent. As positive equilibriums are both grater than 1, it implies that xn → 0, when n → ∞.

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Fig. 2. α = 0.10, β = 0.11, x1 = 0, x2 = 1.42857 and x3 = 3.33333.

5 Conclusion For a given difference equation, the local dynamics is fully investigated, while the global dynamics is determined only for special values of positive parameters. Due to the complexity of obtaining results on global dynamics, each conjecture came in handy as an aid in analyzing the stability of the given equation at the global level for the remaining parameters. The program package Mathematica provides a great help in this, in order to get an insight into what the behavior of the dynamic system will be in the long time. Due to the absence of periodic solutions of period two, but also the absence of a repeller as an equilibrium point, the dynamics of this equation is so much simpler, unlike, for example, the equations observed in [12, 13]. However, due to the fact that the associated mapping has the property that it is monotonically decreasing in the second variable, it greatly complicates the analysis itself at the global level. What is particularly interesting, given in Conjecture 3 and seen in Fig. 1, is the basin of attraction of the nonhyperbolic equilibrium point. In this case, the only two points of equilibrium from the first quadrant that are located in the northeast arrangement are both points that attract, so they have their own basins of attraction shown in Fig. 1. This kind of dynamic scenario is not so common. Of course, all this needs to be proved strictly mathematically. A much more natural and common situation is given in Conjecture 4 and shown in Fig. 2. Then there is a saddle point between two locally asymptotically stable equilibrium points that have their own basins of attraction.

References 1. Kulenovi´c, M.R.S., Ladas, G.: Dynamics of Second Order Rational Difference Equations with Open Problems and Conjectures. Chapman and Hall/CRC, Boca Raton (2001) 2. Amleh, A.M., Camouzis, E., Ladas, G.: On the dynamics of a rational difference equation, Part I. Int. J. Differ. Equ. 3, 1–35 (2008) 3. Amleh, A.M., Camouzis, E., Ladas, G.: On the dynamics of a rational difference equation, Part II. Int. J. Differ. Equ. 3, 195–225 (2008)

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4. Kalabuši´c, S., Kulenovi´c, M.R.S., Mehulji´c. M.: Global period-doubling bifurcation of quadratic fractional second order difference equation. Discrete Dyn. Nat. Soc. 2014(1), 1–13 (2014) 5. Kalabuši´c, S., Kulenovi´c, M.R.S., Mehulji´c. M.: Global dynamics and bifurcations of two quadratic fractional second order difference equations. J. Comput. Anal. Appl. 21(1), 1–14 (2016) 6. Bekteševi´c, J., Mehulji´c, M., Hadžiabdi´c, V., Kalabuši´c. S.: Global asymptotic behavior of some quadratic rational second-order difference equations. Int. J. Differ. Equ. 12(2), 169–183 (2017) 7. Mehulji´c, M., Hadžiabdi´c, Bekteševi´c, J.: Existence and local stability of prime period-two solutions of certain quadratic rational second order difference equation. TEM J. 11(1), 914– 919 (2022) 8. Bekteševi´c, J., Hadžiabdi´c, V., Mehulji´c, M., Maši´c, A.: Local dynamics and global stability of certain second order rational difference equation in the first quadrant with quadratic terms. New Technol. Dev. Appl. V 472(1), 411–419 (2022) 9. Mehulji´c, M., Hadžiabdi´c, Bekteševi´c, J., Maši´c; A.: Global period-doubling bifurcation of a certain second-order quadratic rational difference equations. New Technol. Dev. Appl. V 472(1), 427–435 (2022) 10. Kalabuši´c, S., Kulenovi´c, M.R.S., Mehulji´c. M.: Global dynamics of monotone second order difference equation. J. Comput. Anal. Appl. 29(1), 172–184 (2021) 11. Kalabuši´c, S., Kulenovi´c, M.R.S., Mehulji´c. M.: Global behavior of some rational second order difference equations. Int. J. Differ. Equ. 7(2), 151–160 (2012) 12. Gari´c-Demirovi´c, M., Hrusti´c., S., Nurkanovi´c, Z.: Local and global stability of certain mixed monotone fractional second order difference equation with quadratic terms. Axioms 10, 1–20 (2021) 13. Nurkanovi´c, Z., Nurkanovi´c, M., Gari´c-Demirovi´c, M.: Stability and neimark-sacker bifurcation of certain mixed monotone rational second-order difference equation. Qual. Theory Dyn. Syst. 20, 1–41 (2021)

An Approach to Dynamic Modelling of Industrial Robots Based on 3D Cad Technique Maida Cohodar Husic1(B) , Mirko Ficko2 , Derzija Begic-Hajdarevic1 , Tadej Persak2 , Ahmet Cekic1 , and Simon Klancnik2 1 Faculty of Mechanical Engineering, University of Sarajevo, 71000 Sarajevo,

Bosnia and Herzegovina [email protected] 2 Faculty of Mechanical Engineering, University of Maribor, 2000 Maribor, Slovenia

Abstract. With the development of 3D CAD technology, new possibilities for performing experiments with virtual models have opened up. The paper proposes the development of a virtual model of a robotic manipulator based on its dynamics in the Simscape/Multibody programming environment. Such a model can serve as a research platform for optimizing system performances. This has demonstrated in the paper using the example of the ABB SCARA robot. Keywords: robot · dynamic model · 3D CAD · path planning · simulation

1 Introduction Robots have become an indispensable part of modern production systems, and they are increasingly participating as very important devices in all areas of human life, in households, medicine, education, as toy robots, etc. In addition to the usual application of industrial robots in tasks such as welding, pick and place, painting, handling, etc., robots are increasingly being used in machining processes, such as drilling, grinding, milling, grinding, etc. [1, 4, 7, 8, 13]. Robots also have played a very significant role during the COVID-19 pandemic. Many researchers recognized an importance of robots in period of isolation caused by COVID-19 pandemic [3, 18, 20, 25]. Robots have used for rapid testing of COVID-19 virus, automated neutralizing antibody test, accelerating vaccine [29] and many others. All of these pointed out are the reasons why the interest of researchers around the world for robot investigation has grown exponentially in recent years. Many papers in the last a few decades, deal with the robot dynamic modelling trying to improve robot performances: accuracy, velocity, lower energy consumption etc. Considering importance of robot dynamic, this paper proposes development of simulation model of robot dynamic that can serve as a research platform for the analysis and research of robot behaviour under of various constraint conditions and control algorithms. The paper is organized as follows: The second section gives review of actual investigations in this field. The dynamic model of industrial robot SCARA (ABB IRB 910) © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 450–458, 2023. https://doi.org/10.1007/978-3-031-31066-9_50

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[29] is developed step by step using MATLAB/Simulink in the third section of the paper. The system has observed as an open loop (OL) system. For known motions within the joints, the coordinates of the origin of the end-effector coordinate system (TCP point) have measured. In the second numerical experiment for defined trajectory of TCP point in the workspace, motions and actuated moments/forces in the joints are automatically computed. Finally, it was shown how the dynamic model of the robotic manipulator can be created automatically. In the last part of the paper, concluding considerations are given and directions for future research are indicated.

2 Related Work In process of the manipulator design and selection of an adequate driving subsystem, the knowledge of the robot dynamic model plays an increasingly important role. In a large number of robotic applications, bearing in mind the need to work the robot in an unstructured environment, as answer on demands for better structure stiffness and positioning accuracy, lower energy consumption, in addition to the kinematic model, it becomes mandatory to know the dynamics of the robot [5]. With known and developed the robot dynamic model, it is possible to analyse the behaviour of the robot for different control inputs (as open and closed loop systems), to test different control strategies, etc. Thus, many researchers put focus in own investigations on development of the robot dynamic model: to track desired trajectory [17], to predict vibration [6], to develop linear feedforward controller [24]. Kane dynamic model for 7-DOF robot was presented in [16], the accurate dynamic model of the hybrid robot which taking account the friction of each joint in [26], direct and inverse dynamic model for hybrid robots based on recursive Newton–Euler formalism in [14]. Development of dynamic model of robot in an analytical form is a complex task especially for robot manipulator with more DoF. It is usually performed using special software such as BondSim [9, 11], MATLAB/Simulink [2, 10, 21], ADAMS [28], and many others. With the development of new technologies, based on 3D CAD modelling, the process of dynamic modelling of 3D rigid multibody system is greatly simplified. In the last several decades, many programming platforms for dynamic analysis and visualization of industrial robots and industrial processes generally are developed. By visualization of processes many benefits are obtained: check possible collision between parts, better use of the space, analysis and optimization of execution time of each process steps etc. Simulation model of industrial robot for grasping parts of complex shape based on the existing ROS and Gazebo framework is developed in [4]. The simulation processes and analysis of robot performances are based on Virtual reality (VR) in [19, 22] and Augmented reality (AR) in [4, 15]. Modelling based on URDF file is proposed in [12]. Development of virtual model of process provides possibility of connection and exchanging information between virtual and real systems during the work, that is basic idea of digital-twining [23]. Simulation dynamic model of robot has included in digital-twining software in [27].

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3 Methodology of Robot Dynamic Modelling Main idea of the paper is to develop dynamic model of robot manipulator using robot parts created in any software for 3D CAD modelling. Developed platform provides performing more different experiments with the relatively simple modification: analysing of robot behaviour as OL system, as CL system for testing control algorithms, etc. The robot used for the experiments in this paper is Selective Compliance Articulated Robot Arms (SCARA) of ABB with four DoF, Fig. 1. With first two revolute joints and prismatic third, it is enabled positioning of end-effector inside of workspace. Fourth rotation joint provides partially orientation of the grasped part. With such configuration SCARA can be used for an assembly of small parts, material handling (picking and placing, part transferring, part handling, sorting, packing) and inspection. In this paper, ABB modelIRB 910SC-3/0.45 is considered: with payload capacity of 3 kg and maximum reach of 0.45 m [29]. The direct kinematic model which provides calculation of the coordinates of TCP point (in the global frame X g Y g Z g ) in function of joint variables (θ 1 , θ 2 , d 3 ) is given by well-known equations: ⎧ ⎨ px = L2 cos(θ1 ) + L3 cos(θ1 + θ2 ) (1) p = L2 sin(θ1 ) + L3 sin(θ1 + θ2 ) ⎩ y pz = L1 + L4 + d3

Fig. 1. The robot SCARA: a) Kinematic structure; b) Visual form of developed model

The dynamic model and numerical experiments have performed in MATLAB/Simulink Simscape Multibody program environment.

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3.1 Case 1 Dynamic model of SCARA IRB910-3/0.45 is created step by step using blocks to represent links (block File Solid) and joints from the library of MATLAB/Simulink, Simscape/Multibody (Fig. 2). The global frame is defined on such way that X g axis is oriented to right, Z g goes to up (Fig. 1a). The robot links are represented by their 3D CAD models in form of CATIA files (CATPart). These models are obtained from step file (IRB 910SC_IRC5C_Base_Standard_rev0.step) which is taken from [29]. This step file is firstly imported to CATIA, and then each link (Base, Arm1, Arm2 and Shaft) is created by exporting to format CATPart. Because the frame X c Y c Z c in which these bodies are originally developed is oriented as shown in Fig. 1a, each time before importing the body to the dynamic model we have to perform transformation from corresponding frame to frame X c Y c Z c and after importing of the body go back. These transformations are shown in Fig. 2 (on the left bottom). To systematically present dynamic model several blocks should be organized as subsystems, as done for bodies and their necessary transformations. Material properties of links are automatically calculated from geometry based on the body mass. The total robot mass of 24.5 kg is divided on the bodies proportional to their volumes. To verify developed model (Fig. 2), the joints are actuated to provide desired motions:   θ1 = 100 · sin(t) deg, (2) θ2 = 100 · sin(t) deg , d3 = 0.1 · sin(t) [m].

Fig. 2. Dynamic model of robot manipulator SCARA IRB910

Obtained trajectory of TCP point projected in the global frame is shown in Fig. 3a. Comparison coordinates of point TCP obtained during simulation and these one calculated by (1) provides good agreement. Errors are order of 1e−6 m, Fig. 3b. After that, it was performed experiment similar to one from [9]. Robot has task to rotate to the left and presses the mark on the part located on the table, then rotates and

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Fig. 3. Direct kinematic model: a) Trajectory of TCP point; b) Position error

presses the mark on the part located on the other table. Joints are actuated to provide desired motions by the following inputs: ⎧  ⎪ ai · sin π3 t ⎪ ⎪ ⎪ ⎪ ⎨ ai  θi = ai · sin π3 (t − 2) ⎪ ⎪ ⎪ ⎪ −ai  ⎪ ⎩ ai · sin π3 (t − 4)

0 ≤ t ≤ 1.5

1.5 ≤ t ≤ 3.5   −0.1 · sin(π (t − 2)) 2 ≤ t ≤ 3 [m]. 3.5 ≤ t ≤ 6.5 deg , d3 = −0.1 · sin(π (t − 7)) 7 ≤ t ≤ 8 6.5 ≤ t ≤ 8.5 8.5 ≤ t ≤ 10

(i = 1, 2) a1 = 90, a2 = −60.

(3)

Obtained coordinates of TCP point are measured and compared with analytically computed ones, showing good agreement, Fig. 4.

Fig. 4. a) Trajectory of TCP point; b) Position error

3.2 Case 2 In the second case the trajectory of TCP point is known and defined by: px = 0.25 − 0.5 · cos2 (u) − 0.2 cos(u) [m], py = sin(u) · [0.2 + 0.5 · cos(u)] [m], pz = 0.2202 + 0.1 [m],  · sin(t)  u = 100 · sin(t) deg. .

(4)

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Trajectory is implemented by three Matlab functions as shown in Fig. 5 (left down). If we know numerical values of coordinates of TCP point at some time instants, the known trajectory can be represented by 1-D Lookup Table. Constrained desired motion of TCP point should be obtained by Cartesian joint which leads TCP point along desired trajectory, Fig. 5. In doing so, the necessary movements and moments/forces in the joints are automatically calculated. Obtained joint variables and coordinates of TCP point are depicted in Fig. 6.

Fig. 5. The robot dynamic model with constrained motions

Fig. 6. The task defined in the operational space: a) Joint variables; b) Trajectory of TCP point

3.3 Case 3 If structure of robot manipulator is complex with more DoF, it is very useful automatically created the dynamic model as done in the third case. The assembly of robot manipulator SCARA in form sldasm (created in Solid Works) is taken from [30] and exported to Simscape Multibody using Simscape Multibody link, installed in SolidWorks. Two files have exported, the one in form of xlm and other as Matlab code file with necessary geometrical and material properties of robot. By importing created xml file to Matlab the dynamic model is automatically created, as shown in Fig. 7. Some components should be organized as subsystems to systematically present model. The model is ready for investigations as presented for cases 1 and 2 or many others.

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Fig. 7. Automatically created the dynamic model by exporting from SolidWorks

4 Conclusion To investigate and optimize the robot performances this paper shows and proposes concepts how to develop the basic virtual platform based on dynamic model of robot manipulator. If robot structure is simple, model could be created step by step. Each body, considered as rigid, can be represented by 3D CAD model in CATIA format CATPart. Thus, material properties will be automatically loaded to the dynamic model. But, if structure is complex, it is possible import model from SolidWorks assembly with extension SLDASM via link which transform this file to file with extension xml. Simulink model with extension slx will be obtained by importing xml file. In each case, it is obtained dynamic model of robot mechanical part. The resulting system can serve as a research platform for analysing and performing many experiments. Its capabilities can be significantly expanded and improved by adding sensors, control algorithms, etc. Finally, after testing the developed algorithms, it is possible to manage a real robotic station via ROS. In future research, we plan to establish a connection with a real robot via ROS and analyse the behaviour of real systems. Acknowledgments. This work is realized in part of bilateral collaboration of researchers from University of Sarajevo – Faculty of Mechanical Engineering and Faculty of Mechanical Engineering, University of Maribor, the project “Development of control algorithm and systems in the prevention of adverse consequences of COVID-19 in production systems PRECOVIR21_22”.

References 1. Baratta, A., Cimino, A., Gnoni, M.G., Longo, F.: Human robot collaboration in industry 4.0: a literature review. Procedia Comput. Sci. 217, 1887–1895 (2023) 2. Bârsan, A., Racz, S.-G., Breaz, R., Crenganis, , M.: Dynamic analysis of a robot-based incremental sheet forming using Matlab-Simulink SimscapeTM environment. Mater. Today Proc. 62, 2538–2542 (2022). https://doi.org/10.1016/j.matpr.2022.03.134 3. Bigliardi, B., et al.: Industry 4.0 and Covid-19: evidence from a case study. Procedia Comput. Sci. 217, 1803–1809 (2023). https://doi.org/10.1016/j.procs.2022.12.380 4. Chen, C., Pan, Y., Li, D., Zhang, S., Zhao, Z., Hong, J.: A virtual-physical collision detection interface for AR-based interactive teaching of robot. Robot. Comput. Integr. Manuf. 64, 101948 (2020)

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Electrical Engineering, Computer Science, Information and Communication Technologies, Control Systems

FPGA Based Logistics Service Robot Control in E-Commerce Warehouse System Lejla Banjanovi´c-Mehmedovi´c1(B) , Lejla Husi´c1(B) , Anel Husakovi´c2(B) , and Nermin Sarajli´c1(B) 1 Faculty of Electrical Engineering, University of Tuzla, 75000 Tuzla, Bosnia and Herzegovina

{lejla.mehmedovic,nermin.sarajlic}@untz.ba, [email protected] 2 Faculty of Mechanical Engineering, University of Zenica, 72000 Zenica, Bosnia and Herzegovina [email protected]

Abstract. Logistic 4.0 requires the integration of different types of technologies, such as robotics, internet of Things (IoT), advanced data analytics, artificial intelligence (AI), which results in a powerful smart supply chain management system with the possibility of being used in different application. The wireless capability, path tracking and speed/position controllers have become important in the design of mobile robots since they are extensively applied in industrial and service fields. In this paper, we propose an e-commerce warehousing management concept based on the service mobile robot with a controller implemented on the Altera FPGA Cyclone IV board and Android application for remote control. According to the latest trends in RFID localization, the proposed navigation algorithm is implemented in the RFID based environment, using the FPGA based control platform. The perspectives of cyber security in the framework of the communication system and embedded application in an e-commerce warehouse are also presented. From experimental results, we are able to track what is inside a supply chain and what state it is and to see the benefits of a strategic logistic approach. Keywords: FPGA · Industry 4.0 · logistic · service robots · warehouse · cybersecurity

1 Introduction Logistic 4.0 or smart supply chain management involves a variety of various aspects of end-to-end logistics in the business, supply chain and context of Industry 4.0. Logistics tasks, which include the movement of goods, materials, data, etc., use the new technologies, advanced data analytics and (semi)autonomous decisions enabled by artificial intelligence (AI). Industry 4.0 partially transfers autonomy, intelligence and autonomous decisions to machines and to the edge, supply chain and logistics. Similarly, in different applications it includes technology, human and business aspects and elements [1]. There are various different types of applications, from driverless transportation to smart warehousing, smart shelves to the human and information exchange in all possible © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 461–469, 2023. https://doi.org/10.1007/978-3-031-31066-9_51

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logistical chains and contexts. Generally, the application of autonomous logistics systems includes transportation, handling, packaging, classification and delivery [2]. In the logistics industry, the mobile robot appears to be an excellent solution to many issues. Considering the large number of applications, service robots in logistics offer a wide range of different technical and operational solutions. The warehousing and logistics chain automatisation encompass all manner of mobile robots, such as automated guided vehicles (AGVs), autonomous mobile robots (AMRs), mobile manipulators, grid-based automated guided carts, case-picking robots and drones [3]. The idea of this research paper was inspired by mobile logistics robots that are used in modern e-commerce logistics industry, which relies on technologies such as mobile commerce, supply chain management, electronic data exchange (EDI) and automated data collection systems. A large number of robot navigation techniques have been proposed in recent years. Navigation approaches are generally divided into the following categories: dead-reckoning-based, landmark-based, vision-based, and behavior-based techniques [4]. Dead-reckoning is a navigation technique which is based on the integration of incremental motion over time. However, small precision errors and sensor drifts can occur and lead to the increased robot positioning and orientation cumulative errors. Therefore, an independent reference is periodically used to correct these errors. The vision-based navigation follows visual features in the environment and uses them as landmarks to improve the robot position estimation. This method has its drawbacks, such as the complex image processing algorithms with high computational costs, and its dependence on the working environment [4]. This problem can be solved by adopting behavior-based navigation systems. The most attractive form of reactive and behavior navigation is the fuzzy logic controller, which provides reasoning and decision making with uncertain and imprecise information [5]. The behavior-based method can incorporate a relatively large number of sensors, making them suitable for navigation in unstructured environments. To properly localize items, the recent mobile robot navigation trend has been employing radio frequency identification (RFID) in a 3D environment [6]. There are different structures of digital circuits, used for control of real-time embedded applications such as Application Specific Integrated Circuits (ASICs), generalpurpose microcontrollers, Field Programmable Gate Array (FPGA) and System-on-Chip (SoC) [7]. Even though the first option is very efficient and gives very high performance, it is too expensive and less flexible. On the other hand, a microprocessor lacks the essential circuitry on one chip, which requires additional devices and components. In the last decade, the major issues of automated real-time systems have been the design of Systems-on-Chip hardware architectures as well as a FPGA. SOC is an integrated circuit which integrates a CPU, memory, input/output devices, radio modems, FPGA and GPU, all on a single microchip. A FPGAs can accelerate computations and use the best characteristics of reconfigurable FPGA devices. A FPGA-based control system improves scalability of the control system and performs the complex tasks efficiently, especially when it is necessary to achieve more tasks. A framework for dynamically reconfigurable mobile robots has been proposed in [8]. In our paper, we propose an e-commerce warehousing management concept based on

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the service mobile robot with a controller implemented on the FPGA board and Android application for remote control. The first section is the introduction to Logistic 4.0 and embedded solutions in Industry 4.0 scope. The second section is focused on a cybersecurity perspective of warehouse applications. Then, we detail our FPGA based control concept of logistic service robot and the technical description of a Warehouse Management System in the third section. The experimental results are presented in the fourth section. The last section concludes the paper with insights for extensions.

2 Cybersecurity Perspective for the Success of Warehousing Applications Mobile robots are increasingly being used in warehouse operations to improve efficiency and productivity. The establishment of an effective communication system is indispensable for this purpose [9]. These systems are facing various cybersecurity challenges due to the nature of their mobility and the fact that they operate in unstructured environments. It is important for warehouses to consider the security of these systems in their overall security strategy and ensure that they are properly secured and protected. When looking into the question how the attacker reaches the target information, there may be two types, in person and via electronic network [10]. For the former, one needs to ensure physical protection of the robot from physical tampering and attacks, ensuring that the robot’s sensors, such as cameras and lidar or a navigation system, are not compromised by malicious actors. At the same time, one also needs to ensure that the robot’s actions do not harm humans or damage equipment during operation, especially in the era of Industry 5.0 where humans and robots share the same space [11]. Regarding the cybersecurity via electronic network, one needs to establish secure communication, which means ensuring that data transmitted between the robot and other systems are protected from unauthorized access or interception and to ensure that remote management systems are secure and can be used to monitor and control the robot’s actions. When dealing with communication networks such as warehouse systems, security objectives like confidentiality, integrity, availability and authorization (access control on an application layer) [10] are achieved by security protocols at different layers of communication networks. These protocols ensure data protection on communication links as it is transmitted between the robot, warehouse management systems, and other devices. Some of the commonly used secure communication protocols include IoT protocols [12] between different IoT layers that can be divided into a hardware layer, an operating system layer and an application layer [13]. Furthermore, the layers can be granulated to edge (link) layer (RFID tags, sensors, readers), access gateway layer (connection between devices and cloud), internet layer, middleware layer (data management, access control, device discovery) and application layer [12]. The protocols may be classified based on the range of communication into short-range, medium-range, long-range and wired communication [12]. For example, the short-range communication to access the edge layer (RFID) is used in paper [12]. However, wireless short-range links such as Bluetooth or IEEE 802.11

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wireless LANs (WLANs) are particularly vulnerable in the link layer, like DoS attacks by radio jamming, or eavesdropping on the traffic [10]. In the paper [13], it has been shown that the mobile robot may be positioned far away from the owner, enabling illegal users to physically touch the device and modify the software and hardware of the device. The illegal user spies on the system bus through hardware wiring, analyzes the communication data on bus, bypasses the key hardware components in order to destroy original system functions, or accesses non-volatile private data by accessing the memory chip. By design the operating system for embedded systems is a power efficient system with battery usage with limited computing power of CPU and as such it is almost impossible to add security encryption algorithms, while for traditional computers in the embedded system it is possible to install antivirus software [13]. Devices are connected through the network and with various applications, and if the communication protocol is too simple, like it is by an early design of embedded systems, where the plain text or simple encrypt is sent to the network, it may lead to attacks on the Internet, like Trojan horses (Havex virus 2014, “Ghost Push” 2015) [13]. Classical types of software attacks, that are cheaper than hardware attacks, for the embedded systems are related to attack on confidentiality, integrity, availability as security objectives [10] and mostly include tampering (with the goal to modify the code integrity, by modifying relevant data or code of the embedded systems), sabotage (by attacking running software with viruses, Trojan horses, worms, malwares) and theft (to obtain private data or confidential information stored, transmitted or manipulated in the embedded systems) [13]. Typically, on the network layer the embedded systems use TCP/IP connection protocol and software itself which does not encrypt the communication data. There are different protocols used in the embedded systems like Constrained Application Protocol (CoAP), Advanced Message Queuing Protocol (AMQP), Simple/Streaming Text Oriented Messaging Protocol (STOMP), Mosquitto (open source MQTT broker), SimpleSensor Interface (SSI), Simple Media Control Protocol (SMCP), Data Distribution Service (DDS). MQTT is an OASIS standard that relates to dynamic code integrity where verification of integrity of software instruction blocks is performed during operation [13]. It is based on a publish/subscribe communication pattern and is designed to run in an embedded environment where a small footprint is required, especially for wireless networks that experience varying levels of latency due to occasional bandwidth constraints or unreliable connections. MQTT is considered as the second standard IoT protocol (after HTTP and REST) [14]. MQTT is not designed with security in mind and should be used in secure backend networks for application-specific purposes. Some measures regarding the security of Android applications may be to use 2FA (two factor authentication) in order to authorize user credentials [12] and code signing where the applications are digitally signed by the developer to ensure that applications have not been tampered with and to identify the developer. Also, it is always convenient to deploy the firewall at the border of the network or network zone to protect it against unauthorized access from neighboring zones (e.g. Internet) [13]. Furthermore, intrusion detection methods based on artificial intelligence may be used as is done for SCADA systems using support vector machines [15].

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3 Warehouse Management System Based on the FPGA Service Robot In our implementation, we are using the medium-range communication layer, for Wi-Fi communication between the Android applications and MQTT server (broker), which is using Message Queue Telemetry Transport (MQTT) protocol to transmit telemetry information data between devices over a network, and is commonly used in IoT and industrial (IIot) applications. There are two types of communication in realization of logistic service, presented in Fig. 1: • UART communication between the NodeMCU development board and Cyclone IV FPGA. The NodeMCU development board has Wi-Fi capability and serial communication protocols. • MQTT communication between the NodeMCU development board and the server. Namely this type communication enables data transfer via the Internet, so that a mobile robot can be controlled from any part of the world.

Fig. 1. Warehouse Management

FPGA is used instead of a microcontroller for fast prototyping of embedded systems, in cases where a lot of things must be done simultaneously [8]. An implementation of logistic mobile robot based on Altera Cyclone IV FPGA is presented in Fig. 2 using Verilog as Hardware Description Language (HDL). To define the desired trajectory of

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the logistic service robot in warehouse space the RFID tags are used. There are the RFID tags in the row in front of each shelf which indicates the ID of the product. The robot is equipped with the RFID reader to communicate and determine the robot’s relative position with respect to the tags. The servo motor places the product on the desired shelf. Using the Android application, the user can choose the location where the products will be delivered. IR sensors ensure accurate movement of the mobile robot along the line.

Fig. 2. Components of Warehouse Management System

The block-diagram of logistics mobile robot delivery is presented in Fig. 3.

Fig. 3. Block-diagram of logistics mobile robot delivery

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4 Experimental Evaluation Smart logistics enable us to track what is inside the supply chain, where it comes from and in what a state it is. This strategic and holistic approach, which takes into account the value and requirements of consumers, brings considerable benefits. As results of our application, we track state and supply chain of logistic mobile robot. Even though the DC motors values depend on RFID readings, they also depend on IR sensor reading to adjust a logistics mobile robot angle. Interesting cases are marked with blue, pink and red lines, (Fig. 4a). In the first case (marked with the blue line), the IR sensors have next values: (IR1, IR2, IR3) = (0, 1, 0). In this case, the mobile robot is following the line correctly and moving forward (DC motors value are presented with 1). The second case is marked with the pink line. In this case, (IR1, IR2, IR3) = (1, 1, 0), which means that the IR1 sensor has detected the black line and the robot body position is to the left. To adjust this behavior, the mobile robot is moving to the right (DC motors value are presented with value 3). The third case is marked with the red line. In this case, (IR1, IR2, IR3) = (0, 1, 1), which means that the IR2 sensor has detected the black line and the robot body position is to the right. To adjust this behavior, the DC motors value is 2, which means that the robot will turn left. The DC motors value depends on the RFID sensor readings, (Fig. 4b), where the specific cases are labeled on the graph with the pink and red lines. The first case (labeled with the pink line), is when the RFID sensor has detected a position in the warehouse number 2, then the DC motors value is 2 which means that the robot is turning left into the first row of the warehouse. Furthermore, when the RFID sensor has detected the position number 3, labeled with the red line, the value of DC motors is 4, which means that the mobile robot has stopped to make a delivery on the shelf. The value of servo

Fig. 4. Sensor-motor mapping during logistics mobile robot navigation: a). IR sensor - DC motors mapping; b). RFID sensor - DC and servo motors mapping

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motor in this case is 1, which means that the servo motor started working and the product is being delivered on the shelf.

5 Conclusion The ongoing industrial revolution demands efficient logistics and inventory warehouse management. Nowadays, the trend of using warehouses autonomous solutions and service mobile robotics is growing. The overall efficiency of logistic service mainly relies on specialized sensing technologies to track the robot’s motion and measure the positions of the items. This manuscript addresses the problem of RFID tag based navigation for the FPGA controlled service robot in an e-commerce warehouse system. According to the excellent possibilities of acceleration of computer calculations, FPGA provides a reconfigurable framework for increasing the navigation accuracy of logistics robot using the visionbased concept. Also, in the future, cyber security should be provided using artificial intelligence methods.

References 1. Logistics 4.0 (2022). https://www.i-scoop.eu/industry-4-0/supply-chain-management-scmlogistics/ 2. Karabegovi´c, E., Mahmi´c, M.: Distribution and implementation of logistics service robots. In: Karabegovi´c, I., Banjanovi´c-Mehmedovi´c, L. (ed.) Service Robots: Advances in Research and Application, Nova Science Publisher, USA (2021) 3. Mobile Robotics in Logistics, Warehousing and Delivery 2022–2042 (2022). https://www.idt echex.com/en/research-report/mobile-robotics-in-logistics-warehousingand-delivery-20222042/855 4. Gueaieb, W., Miah, Md.S.: An intelligent mobile robot navigation technique using RFID technology. IEEE Trans. Instrum. Meas. 57(9) (2008) 5. Banjanovic-Mehmedovic, L., Balukovi´c, A.: PSO optimized fuzzy controller for mobile robot path tracking. In: Karabegovi´c, I. (eds.) NT 2020. LNNS, vol. 128, pp. 413–421. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-46817-0_47 6. Tripicchio, P., D’Avella, S., Unetti, M.: Efficient localization in warehouse logistics: a comparison of LMS approaches for 3D multilateration of passive UHF RFID tags. Int. J. Adv. Manuf. Technol. 120(12) (2022) 7. Reem, R.I., Saad, M.A., Abbas, H.I.: FPGA Cyclone II Based the Mobile Robot Control System 2018 Third Scientific Conference of Electrical Engineering (SCEE), University of Technology 2018 IEEE 186 (2018) 8. Banjanovic-Mehmedovic, L., Husejnovic, A.: FPGA based hexapod robot navigation using arbitration of fuzzy logic controlled behaviors. In: IEEE ICAT 2019, Bosnia and Herzegovina (2019) 9. Poberezkin, E., Roozbahani, H., Alizadeh, M., Handroos H.: Development of a robust Wi-Fi/4G-based ROS communication platform for an assembly and repair mobile robot with reliable behavior under unstable network or connection failure. Artif. Life Robot. (2022) 10. Dzung, D., Naedele, M., von Hoff, T.: Security for industrial communication systems. In: Proceedings of the IEEE (2005)

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11. Dieber, B., Schartner, P.: Secure communication for the robot operating system. In: 11th Annual IEEE International Systems (2017) 12. Dineva, K., Atanasova, T.: Security in IoT systems. In: XIX International Multidisciplinary Scientific GeoConference SGEM 2019 (2019) 13. Xie, Y., Buchman, A.: A survey for communication security of the embedded system. Carpathian J. Electron. Comput. Eng. 14(2), 15–19 (2021) 14. Gomez, J.R., Mondejar, J.C., Gomez, J.M.C., Villafranca, S.R.: Security analysis of the MQTT-SN protocol for the Internet of Things. Appl. Sci. (2022) 15. Maglaras, L., Jiang, J.: Intrusion detection in SCADA systems using machine learning techniques. In: Science and Information Conference (SAI), pp. 626–631 (2014)

An Overview of Maintenance Strategies Using Petri Net Models Ilija Hristoski1(B) and Tome Dimovski2 1 Faculty of Economics – Prilep, “St. Kliment Ohridski” University – Bitola, Prilepski Braniteli

St. 143, 7500 Prilep, North Macedonia [email protected] 2 Faculty of Information and Communication Technologies – Bitola, “St. Kliment Ohridski” University – Bitola, Partizanska St., 7000 Bitola, North Macedonia

Abstract. The accelerated change in technology, industries, and social patterns and processes, caused by ubiquitous digitalization, increased interconnectedness, and smart automation, commonly referred to as Industry 4.0 revolution, has posed greater challenges to system maintenance issues than ever before. By describing various cost-effective practices to keep systems’ equipment operational, and therefore highly available, maintenance remains the cornerstone set of activities that prevent equipment or facility from failing, keeping it in a good work condition, which is a key premise to carry out its mission. The paper aims to provide an overview of various maintenance strategies, supported by proposed Petri Net models. Such simulation models are suitable for carrying out performance and availability analysis of the strategies, based on a plethora of input parameters. The suggested Petri Net models provide solid frameworks for investigating the effectiveness of various maintenance strategies applied to a wide gamut of systems. Keywords: maintenance strategies · modeling · stochastic Petri Nets

1 Introduction In the Industry 4.0 era, which denotes a profound digital transformation of manufacturing/production, related industries, and value creation processes, the maintenance of cybersecurity systems, augmented reality systems, Big Data systems, IoT systems, Cloud computing systems, autonomous robots, and all other cyber-physical and control systems used in complex system integration, simulation, communication, networking, and additive manufacturing processes becomes of utmost importance. The maintenance of such systems aims to attain high levels of systems dependability, reliability, and availability features. Only the proper and on-time maintenance of networked systems that can flawlessly communicate with other one scan enable continuous and efficient ways of utilization, production, value creation, and real-time optimization. Recognizing the huge significance of systems maintenance in today’s digitalized environment, the paper aims to shed light on some of the most common maintenance strategies by providing their corresponding generic simulation models, based on the utilization of various © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 470–477, 2023. https://doi.org/10.1007/978-3-031-31066-9_52

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classes of stochastic Petri Nets, such as Generalized Stochastic Petri Nets (GSPNs) [1, 2] and Deterministic and Stochastic Petri Nets (DSPNs) [3, 4]. These can serve as suitable frameworks to perform various types of ‘what-if’ analyses vis-à-vis different input parameters.

2 Maintenance Strategies Defined as being a ‘choice’, a “means to say no to certain kinds of things” or simply “choosing what not to do” (Michael Porter), strategy, in general, “is not the consequence of planning, but the opposite: its starting point” (Henry Mintzberg). It is a general plan to achieve one or more long-term or overall goals under conditions of uncertainty. Strategy is essential because the resources available to attain the goals are typically limited, so setting objectives and priorities, deciding which steps to take to attain the goals, and mobilizing resources to carry out the actions are all vital aspects of strategy [5]. Having a strategy is a necessary component of any kind of activity, since “without strategy execution is aimless; without execution, strategy is useless” (Morris Chang). In this regard, maintenance strategy can be defined as a methodology approach, which identifies the sequence of essential activities that have to be completed to keep the used system running properly, by providing scheduling information and being assigned to as many activities as needed, with a single aim “to achieve the agreed plant operating pattern and product quality, within the accepted plant condition and safety standards, and at minimum resource cost” [6]. As such, maintenance strategies are designed to increase productivity, efficiency, reliability, and quality while extending/improving assets’ life, health, and safety, and decreasing/reducing asset failures, repair costs, and operational expenses [7]. When adopting a certain maintenance strategy, choosing the most appropriate one is crucial since multiple factors have to be taken into consideration to provide continuity of operations and risk management. These include (1) economic factors, which are related to minimizing the costs of both repair and downtime in case of failure, (2) evaluation of the failure’s repercussions in terms of economic, environmental, etc. effects to determine the significance of avoiding failures, (3) assessment of the likelihood of failure that can be useful in adjusting maintenance plan/schedule, and (4) evaluation of time-related characteristics (time horizon, shift factor) that can help in defining the maintenance strategy. The rest of the paper addresses the three basic maintenance strategies [8], including (1) Reactive; (2) Preventive; and (3) Condition-based maintenance. 2.1 Reactive/Run-to-Failure/Run-to-Breakdown/Failure-Based Maintenance This strategy, based on the concept of corrective maintenance, is named ‘reactive’ because the maintenance of a given system occurs as a reaction (consequence) to its failure (cause), i.e. there is no maintenance until there is no failure. This strategy is frequently used when the failure has minimal influence and/or is simple to fix. Figure 1 and Fig. 2 show GSPN (Generalized Stochastic Petri Net) models capturing the reactive maintenance approach applied to a whole system and to a system that includes a single sub-system, respectively. The system depicted in Fig. 1 alternates between two opposite states: a working condition (a token in the place P_sys_WORK) and a non-working condition (a token in the place P_sys_FAIL). The system is operational until a failure occurs

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after an average of MTTF (Mean Time to Failure) time units. The failures of the system happen with a rate of λsys = 1/MTTF. When a failure happens, corrective maintenance takes place within MTTR (Mean Time to Repair) time units, on average. The rate of repairing the system is μsys = 1/MTTR. The values of λsys and μsys are firing rates of the exponential transitions T_sys_MTTF and T_sys_MTTR, respectively.

Fig. 1. Generalized Stochastic Petri Net (GSPN) model of reactive maintenance of a system

Fig. 2. Generalized Stochastic Petri Net (GSPN) model of reactive maintenance of a system with a single non-critical subsystem (Source: Authors’ representation)

The GSPN model in Fig. 2 depicts the main system with a non-critical subsystem. Whenever the main system fails, the subsystem becomes non-operational; after the corrective maintenance of the main system, the subsystem restores its operation. However, the failure of the non-critical subsystem (a token in the place P_subsys_FAIL) does not

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affect the operation of the main system, which continues to work despite the failure of the subsystem; the failed component gets operational (a token in the place P_subsys_WORK) as soon as corrective maintenance takes place. 2.2 Preventive Maintenance Based on an old saying stating that “an ounce of prevention is worth a pound of cure”, preventive maintenance is a strategy that takes into consideration a schedule/plan of assets’ inspections and actions to detect and resolve minor faults before they become major concerns. The schedule can be based either on time or on asset usage. In addition, two other maintenance strategies, the predictive and prescriptive ones, belong to this type; however, they will not be taken into consideration in this study. Two distinctive DSPN (Deterministic and Stochastic Petri Net) models of preventive maintenance based on time are portrayed in Fig. 3 and Fig. 4.

Fig. 3. Deterministic and Stochastic Petri Net model of a system undergoing preventive maintenance based on pre-determined time, with no time shifts (Source: Authors’ representation)

The first one (Fig. 3) shows a system that can be subject to failures and consecutive corrective maintenance actions, but it is also subject to preventive maintenance actions scheduled in a pre-determined manner and fixed in time (no time shifts), regardless of whether corrective maintenance occurred or not.

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The second DSPN model (Fig. 4) portrays a system that can be subject to failures and consecutive corrective maintenance actions, but it is also subject to preventive maintenance actions scheduled in a pre-determined manner. The difference with the previous model in Fig. 3 is that the next preventive maintenance is scheduled right after the last corrective maintenance occurred, so preventive actions are not fixed in time but rather shifted in time, depending on whether corrective maintenance occurred. In both cases, the time to the next preventive maintenance is determined by τ, the delay of the deterministic transition T_time_to_prev_maint. The preventive maintenance lasts, on average, 1/ϕsys time units and is resembled by the exponential transition T_prev_maint.

Fig. 4. Deterministic and Stochastic Petri Net model of a system undergoing preventive maintenance based on pre-determined time, with time shifts (Source: Authors’ representation)

The DSPN model in Fig. 5 depicts preventive maintenance of a system based on usage. The system alternates between two states: a working state and a state of being idle, that last for τw (deterministic transition T_working) and τi (deterministic transition T_idle) time units, respectively. Each firing of the transition T_working puts a single token in place P_how_many_times. The immediate transition T_start_prev_maint fires only when the total number of tokens in the place P_how_many_times (i.e. #P_how_many_times) becomes equal to the total pre-defined number of tokens in the place P_ref_value, which means that preventive maintenance occurs after a certain number of times the system was used/working (in this particular case, every N = 3 times).

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Fig. 5. Deterministic and Stochastic Petri Net model of a system undergoing preventive maintenance based on usage (Source: Authors’ representation)

In general, an important factor in choosing preventive maintenance as a strategy may be low maintenance costs compared to failure impact. The aim is to schedule maintenance operations before the occurrence of a failure to reduce failure chances. 2.3 Condition-Based Maintenance Condition-based maintenance is based on constant or continuous monitoring of asset conditions and checking for any deviations that might indicate the beginning of a failure. Deviations may include one or more parameters such as temperature, vibration, speed, power, and moisture, and refer to exceeding a pre-defined maximum limit, failing below a pre-determined minimum limit, or both. This type of strategy can be employed in operations where failure is predictable and the cost is substantial. The latter may be true in circumstances when a failure might result in an interruption of critical operations or when maintenance itself is costly. A DSPN model of a system that is subject to condition-based maintenance is shown in Fig. 6. In the modeled system, the deterministic transition T_check fires after τ time units, which means that a particular system condition is checked every τ time units. On the other hand, the firing of the exponential transition T_condition is a Poisson process, which occurs with a rate of ηcond , i.e. after 1/ηcond time units on average, which is a mean time to an occurrence of a deviation from the specified condition. When a deviation occurs, a token is put in the place P_condition_YES; otherwise, this place contains no token. Given this, the firing of the immediate transition T_no_cond_detected occurs only if there is no token in the place P_condition_YES and if there is a token in the place P_check_END, meaning that the checking of the system’s condition did not detect any deviation. Contrary to this behavior, the firing of the immediate transition

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Fig. 6. Deterministic and Stochastic Petri Net model of a system undergoing condition-based maintenance (Source: Authors’ representation)

T_cond_detected occurs only if there are tokens in the places P_condition_YES and P_check_END, meaning that the system checking detected a deviation of the observed working condition from its normal values. In this case, preventive maintenance is being initiated (a token in the place P_prev_maint) that lasts for 1/ϕsys time units on average (a firing of the exponential transition T_prev_maint). After the preventive maintenance, the system is put again in the working state (a token in the place P_sys_WORK), and there is no deviation of the observed parameter (a token in the place P_condition_NO), whilst the monitoring of the observed parameter continues in regular time intervals (a token in the place P_check_START ).

3 Conclusion In the exceedingly digitalized environment that involves a myriad of systems, components, devices, machines, computers, robots, sensors, etc. the role of effective maintenance has become even bigger and more significant. Based on the corrective and preventive maintenance processes, representing the two basic types of maintenance procedures/actions, the main objective of maintenance is to preserve a system’s capability to provide a reliable, dependable, safe, and highly available service to all of its users. On the other hand, various maintenance strategies, which are deterministic plans specifically intended for equipment preservation and maximizing equipment uptime and facility performance while balancing the associated costs, can help in finding out the most suitable and cost-effective approach to cope with potential failures, having in mind that different assets need different, yet sometimes unique maintenance strategies. The paper addressed some of the most prominent maintenance strategies; however, there are more of them that were not mentioned, such as predetermined, predictive, and

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prescriptive maintenance. However, it should be notified that the latter two cannot be represented as Petri Net models since the first one of them is based on the analysis of a vast amount of data coming from multiple sources, and the second one of them uses artificial intelligence (AI) and machine learning (ML) to not only proactively predict when maintenance will be needed, but also to suggest potential maintenance solutions. As per the validity of the hereby presented simulation models, it was checked and confirmed by TimeNET, a dedicated software tool for modeling and analysis of several classes of stochastic Petri Nets. Future work vis-à-vis the presented models includes conducting a stationary analysis and obtaining steady-state probabilities, as well as the computation of various performance metrics for various input parameters that can help in conducting ‘what-if’ analyses regarding various working scenarios.

References 1. Ajmone Marsan, M., Balbo, G., Conte, G., Donatelli, S., Franceschinis, G.: Modelling with Generalized Stochastic Petri Nets. Wiley Series in Parallel Computing. Wiley, West Sussex (1995) 2. Balbo, G.: Introduction to generalized stochastic Petri Nets. In: Bernardo, M., Hillston, J. (eds.) SFM 2007. LNCS, vol. 4486, pp. 83–131. Springer, Heidelberg (2007). https://doi.org/ 10.1007/978-3-540-72522-0_3 3. Ciardo, G., Lindemann, C.: Analysis of deterministic and stochastic Petri nets. In: Proceedings of the 5th International Workshop on Petri Nets and Performance Models, Toulouse, France, pp. 160–169 (1993). https://doi.org/10.1109/PNPM.1993.393454 4. Lindemann, C.: Performance Modelling with Deterministic and Stochastic Petri Nets. Wiley, New York (1998) 5. Freedman, L.: Strategy: A History. Oxford University Press, New York (2013) 6. Kelly, A.: Maintenance Strategy. Butterworth-Heinemann/Elsevier Science, Woburn (1997) 7. Mobley, R.K.: Maintenance Fundamentals, 2nd edn. Elsevier Butterworth-Heinemann, Oxford (2004) 8. Gackowiec, P.: General overview of maintenance strategies – concepts and approaches. Multidiscip. Aspects Prod. Eng. MAPE 2(1), 126−139 (2019). https://doi.org/10.2478/mape-20190013

Digital Twins Data Visualization Methods. Problems of Human Interaction: A Review Yevhen Palazhchenko1 , Vira Shendryk1(B) , and Sergii Shendryk2 1 Information Technologies Department, Sumy State University, Sumy 40007, Ukraine

[email protected] 2 Sumy National Agrarian University, Sumy 40000, Ukraine

Abstract. Digital Twins (DT) are used in various industries. In particular, when working with robotic systems, the data from Digital Twins allows you to identify problems in the product and modernize it. In addition, Digital Twins technology can be used to train operators to prevent dangerous incidents. Specially developed software or artificial intelligence can analyze the Digital Twins data immediately by a pre-programmed algorithm. On the other hand, a human is not capable of processing such arrays of numerical data and perceives information with the help of the five senses (touch, sight, hearing, smell, and taste). For complete immersion in the process and Digital Twins data processing, we can use a maximum of three of them (touch, sight, and hearing). This work is devoted to the review of data visualization methods of Digital Twins of robot manipulators and the human ability to perceive and use the received data. The paper provides an overview of research in the direction of humanmachine interaction and an overview of multimedia technologies used for data visualization. The work carried out will help systematize knowledge for future researchers. Keywords: Digital Twins · human-machine interaction · multimedia technologies · data visualization

1 Introduction A Digital Twin is a digital model of a physical object or process synchronized due to data flows between them [1]. Digital Twins have been exploited for decades and the popularity of this technology in business and industry is predicted to grow [2]. In absolutely different industries, Digital Twins are beneficial for analyzing data from designed devices and their components throughout the entire life cycle of the product. The concept evolved from the concept of “Mirror World” and grew into the modern concept of Digital Twin [3]. Figure 1 shows Digital Twin evolution timeline. The first practical application was proposed by NASA to analyze data from spacecrafts and aircrafts [4]. This technology is applied in projects of various scales from a single instance of a device to the creation of Digital Twins of entire cities [5].

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 478–485, 2023. https://doi.org/10.1007/978-3-031-31066-9_53

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Fig. 1. Digital Twin evolution timeline (adopted from [2])

It is important to understand the difference between a simple 3D model and a Digital Twin. We can create a 3D model of a device that does not yet exist, that is, create a Digital Prototype. Of course, the resulting model can be used to simulate the operation of the device and make some improvements without building a real object, which makes the production process cheaper. But the Digital Twin is a 3D model that is connected to the real device by sensors and fully reproduces the process of the physical device [6]. The information coming from the sensors can be completely different depending on the device under study. This can be information about the movement and position of individual elements of the device, temperature, humidity, pressure, lubrication level, vibration level, voltage and current, etc. Data from devices can be quickly and efficiently processed by computers and artificial intelligence. But a person is not able to quickly analyze data from sensors in numerical representation, so for better perception of data by a person, it is necessary to visualize not only the 3D model, but also the data coming from the sensors. The paper considers real time data visualization methods of Digital Twin and also a comparison of these methods. Also, a review of works on the human ability to perceive information from Digital Twins and the interaction between human and robot through multimedia equipment. The aim of the work is to determine the actual methods of visualization of Digital Twins data through the prism of human perception.

2 Literature Review 2.1 Digital Twins Concept Modern industry uses digital representations of products throughout the entire life cycle. Initially, a digital model is used to create the design and engineering of individual product elements. Physical constraints can already be imposed on this model [7]. Thus, it is already possible to carry out simulations on the model based on the physics [8]: tensile simulation [9], simulation of aerodynamic properties [10], deformation of model elements due to temperature changes [11], etc. Then, after the real device instance is created, the model can be linked to the physical device and then you can see hidden physical defects that are difficult to detect without sensors that collect information [12]. Digital Twin is a “mirror image” of a real object in the digital world but with bidirectional synchronization [13]. It is also a completely different approach than simulation which is based on the creation of potentially possible situations that are in no

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way reflected in the real object [13]. Usually, in scientific works, Digital Twin reference model is considered as a three-component model: data collection and processing module, information model and bidirectional communication mechanism [14]. In the industry, the Internet of Things (IoT) [15] and Artificial Intelligence (AI) [16] technologies are often considered in conjunction with Digital Twin technology, as these technologies are an integral part of the system working with Digital Twin. Data from the physical object is collected using IoT technology and transmitted to Digital Twin for processing. Then simulation algorithms process the received data and send control commands to the physical robot. The use of artificial intelligence allows the system to automatically adapt to changing production conditions [17, 18]. Figure 2 shows the scheme of data exchange and processing between Digital Twin and Physical Twin.

Fig. 2. Data exchange and processing between Digital Twin and Physical Twin

If Digital Twin is considered as an integral part of a human-controlled system, the human interaction module (user space) is added to the reference model [19]. A user space should provide bidirectional data flows between Digital Twin and a human. Data streams from sensors need to be visualized for human perception. The system response

Fig. 3. A Digital Twin reference model (adopted from [14, 15])

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to human input via data input devices should also be provided. For improved humanmachine interaction, the interface design should be human-centered, that is, take into account the peculiarities of human perception of information [20]. A human-centered environment with auxiliary data analysis and feedback to increase the productivity of operators, a person gets less tired and becomes more creative [21]. Figure 3 shows A Digital Twin reference model with a user space module. Thus, we get a bidirectional chain of communications: human Digital Twin Physical Twin. The whole reference model is divided into Physical World and Digital World. Physical Twin is the physical equipment or process that needs to be controlled. Communication system combines Physical Twin and Digital Twin. Data from the physical device is collected by sensors and control commands are sent to the physical device. Digital Twin itself is responsible for simulation and analysis of Physical Twin data. User Space is a layer that provides interaction of Digital World with a human, in other words, creates a human-robot interface. This layer is responsible for Digital Twin data visualization and feedback. The accuracy of the entire system depends on the quality of data visualization on this layer and the accuracy of processing commands given by a person. The following sections describe the methods of visualization of Digital Twins data and the peculiarities of human perception of this data. 2.2 Digital Twins Data Visualization Methods Digital Twin is different from the traditional Computer Aided Design/Computer Aided Engineering (CAD/CAE) models and from simulations [22]. After all, it is necessary to visualize not only the model data (static data of Digital Twin), but also dynamic data on position and state [23]. The data obtained from Digital Twin should be visualized in a format suitable for human perception. There are several methods for presenting data to humans in a visual format. When choosing a method and appropriate tools, it is necessary to take into account the ability of a person to interact with the Digital World. The use of visual computing technologies enables the operator to better solve real industrial problems in Industry 4.0 scenarios. Visual technologies make a crucial contribution to improving the ability of operators to perform traditional tasks and easily acquire new skills [24]. Data visualization serves to present the results of data analysis in an intuitive and interactive way [25]. Table 1 presents a comparison of data visualization methods [26, 27]. The comparison is based on the general characteristics of the visualization methods and the corresponding hardware. Table 1. Comparison of data visualization methods. Phone/tablet

Desktop Computer

VR

AR

Immersion

Partially

Partially

Partially

Yes

Completeness of data presentation

Partially

Partially

Partially

Yes (continued)

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Desktop Computer

VR

AR

Data entry through natural movements

No

No

Yes

Yes

Head tracking

No

No

Yes

Yes

Mobility

Yes

Partially

Yes

Yes

User-controlled PoV

No

No

Yes

Yes

Of the visualization methods presented, Augmented Reality provides the best immersion and completeness of data presentation because it overlays elements of the digital world on the real world. VR and AR both allow you to control all processes in the first person and interact with the digital world through natural human movements. Instead, tablet and desktop computer do not have such advantages. Robot manipulator is a complex but quite common equipment. The large number of degrees of freedom makes the robot arm an interesting object for research. There are already scientific works describing the process of developing Digital Twins for Robotic Arm [28] or even systems consisting of several robots [29]. The authors use Virtual Reality [31] as a standard method for visualizing the data of Digital Twins [30]. Therefore, Digital Twin data contains both static and dynamic information about the model. The best method of visualizing this data is Augmented Reality, as it provides the best immersion in the environment and provides an intuitive interface for interacting with the digital world. The next section discusses human interaction with the Digital World. 2.3 Problems of Human Interaction Human-machine interaction is becoming key when it comes to human-driven Digital Twins. And accordingly, the systems that are created should be human-centered. That is, the interaction should be based on how a person perceives and processes information, how he interacts with the real world. For example, in order to demonstrate the possibility of integrating human factors into a computerized industrial structure, it is proposed to adopt a human-centered design approach. The approach is based on collecting data about the work of operators. The collected data is integrated into production processes through human-machine interfaces. Such a system of human interaction with smart manufacturing will optimize work processes, increase operator productivity and overall plant productivity [32]. Basically, VR or AR is used to create Human-Machine Interfaces. This decision is due to the peculiarities of human perception and human experience. Virtual reality provides a highly authentic perception of information, and encourages people to act naturally and shape experiences as they would in the real world. The brain perceives virtual experience almost as real. Thus, a person immerses and interacts with the virtual world in a similar way to interacting with reality [33].

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Spatial cognition in VR arises from interaction with virtual environments. The user’s perception of available opportunities in virtual reality affects the ability to move and act in the Digital World. The variety of accessibility types increases the intensity of spatial presence. In other words, virtual spaces with more opportunities for action provide the user with more opportunities for perceiving accessibility, generating a higher intensity of spatial presence [34]. Also, gamification elements can be added to the workflow. For example, a gamified social platform for workplace collaboration combines a collaborative environment with gaming features to encourage and support operator participation in sharing problems, ideas and knowledge. The platform also supports operator engagement in their daily work by stimulating motivation and offering positive feedback [35]. Thus, Virtual Reality and Augmented Reality allow you to create an intuitive interface through which a person can delve into the digital world and get the experience of interacting with the real world. And this has a positive impact on the productivity of operators.

3 Conclusion The paper considers the Digital Twin concept and reveals that there is a part of the work aimed at studying the interaction of a person with a digital twin. This interaction is quite complex, because it is necessary to ensure not only the correct presentation of Digital Twin data to a person, but also to create conditions under which a person could interact with the Digital World. The reviewed scientific works show that Augmented Reality is a good solution for visualizing Digital Twin data, as it combines elements of the digital world and the real one. In addition, a person can track elements of the digital world simply by turning his head, as it happens in familiar conditions. A person perceives the experience gained through VR/AR like a real experience. This has a positive impact on the productivity of operators because a person is immersed in the workflow and interacts with Digital Twin through an intuitive interactive interface. The results of the work can be used for further research in the field of Digital Twin and Human-Machine Interaction.

References 1. IS0/TC184/SC4/WG15. ISO CD 23247-1: Digital Twin Manufacturing Framework—Part 1: Overview and General Principles. Under Development, ISO (2019). https://www.iso.org/sta ndard/75066.html. Accessed 18 Dec 2022 2. Pettey, C.: Prepare for the impact of digital twins (2017). Gartner report. https://go.nature. com/2krzbjd 3. Singh, M., Fuenmayor, E., Hinchy, E., Qiao, Y., Murray, N., Devine, D.: Digital twin: origin to future. Appl. Syst. Innov. 4(2), 36 (2021). https://doi.org/10.3390/asi4020036 4. Glaessgen, E.E.H., Stargel, D.D.S.: The digital twin paradigm for future NASA and USair force vehicles. In: 53rd AIAA/ASME/ASCE/AHS/ASC structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA, p. 1818 (2012)

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5. Tao, F., Qi, Q.: Make more digital twins. Nature 573(7775), 490–491 (2019). https://doi.org/ 10.1038/d41586-019-02849-1 6. Wright, L., Davidson, S.: How to tell the difference between a model and a digital twin. Adv. Model. Simul. Eng. Sci. 7(1), 1–13 (2020). https://doi.org/10.1186/s40323-020-00147-4 7. Aivaliotis, P., Arkouli, Z., Georgoulias, K., Makris, S.: Degradation curves integration in physics-based models: towards the predictive maintenance of industrial robots. Robot. Comput.-Integr. Manuf. 71, 102177 (2021). https://doi.org/10.1016/j.rcim.2021.102177 8. Aivaliotis, P., Georgoulias, K., Arkouli, Z., Makris, S.: Methodology for enabling Digital Twin using advanced physics-based modelling in predictive maintenance. Procedia Cirp 81, 417–422 (2019). https://doi.org/10.1016/j.procir.2019.03.072 9. Zhan, X., Liu, K., Zhao, Y.-B., Yan, H.: Tensile performance of SHCC road-bridge link slabs in fully jointless bridges. Adv. Civ. Eng. 2021, 1–14 (2021). https://doi.org/10.1155/2021/ 6643643. Vignali, V. (ed.) 10. Ruiz, C., Acosta, J.Á., Ollero, A.: Aerodynamic reduced-order Volterra model of an ornithopter under high-amplitude flapping. Aerosp. Sci. Technol. 121, 107331 (2022). https:// doi.org/10.1016/j.ast.2022.107331 11. Mudem, N.R., Jani, S.P.: Modelling and simulating the effect of sunlight heat on front bumper. Int. J. Eng. Adv. Technol. 9(2), 548–554 (2019). https://doi.org/10.35940/ijeat.b3282.129219 12. Bárkányi, Á., Chován, T., Németh, S., Abonyi, J.: Modelling for Digital Twins—potential role of surrogate models. Processes 9(3), 476 (2021). https://doi.org/10.3390/pr9030476 13. Schleich, B., Anwer, N., Mathieu, L., Wartzack, S.: Shaping the Digital Twin for design and production engineering. CIRP Ann. 66(1), 141–144 (2017). https://doi.org/10.1016/j.cirp. 2017.04.040 14. Lu, Y., Liu, C., Wang, K.I.-K., Huang, H., Xu, X.: Digital Twin-driven smart manufacturing: connotation, reference model, applications and research issues. Robot. Comput.-Integr. Manuf. 61, 101837 (2020). https://doi.org/10.1016/j.rcim.2019.101837 15. Fuller, A., Fan, Z., Day, C., Barlow, C.: Digital Twin: enabling technologies, challenges and open research. IEEE Access 8, 108952–108971 (2020). https://doi.org/10.1109/access.2020. 2998358 16. He, B., Bai, K.-J.: Digital twin-based sustainable intelligent manufacturing: a review. Adv. Manuf. 9, 1–21 (2020). https://doi.org/10.1007/s40436-020-00302-5 17. Barricelli, B.R., Casiraghi, E., Fogli, D.: A survey on Digital Twin: definitions, characteristics, applications, and design implications. IEEE Access 7, 167653–167671 (2019). https://doi.org/ 10.1109/access.2019.2953499 18. Rasheed, A., San, O., Kvamsdal, T.: Digital Twin: values, challenges and enablers from a modeling perspective. IEEE Access 8, 21980–22012 (2020). https://doi.org/10.1109/access. 2020.2970143 19. Bevilacqua, M., et al.: Digital twin reference model development to prevent operators’ risk in process plants. Sustainability 12(3), 1088 (2020). https://doi.org/10.3390/su12031088 20. Pizzagalli, S.L., Kuts, V., Otto, T.: User-centered design for human-robot collaboration systems. IOP Publishing, UK (2021). https://doi.org/10.1088/1757-899x/1140/1/012011 21. Romero, D., Stahre, J., Taisch, M.: The operator 4.0: towards socially sustainable factories of the future. Comput. Ind. Eng. 139, 106128 (2020). https://doi.org/10.1016/j.cie.2019.106128 22. Madni, A., Madni, C., Lucero, S.: Leveraging Digital Twin technology in model-based systems engineering. Systems 7(1), 7 (2019). https://doi.org/10.3390/systems7010007 23. Schroeder, G.N., Steinmetz, C., Pereira, C.E., Espindola, D.B.: Digital Twin data modeling with automationML and a communication methodology for data exchange. IFACPapersOnLine 49(30), 12–17 (2016). https://doi.org/10.1016/j.ifacol.2016.11.115 24. Segura, Á., et al.: Visual computing technologies to support the operator 4.0. Comput. Ind. Eng. 139, 105550 (2020). https://doi.org/10.1016/j.cie.2018.11.060

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25. Qi, Q., et al.: Enabling technologies and tools for Digital Twin. J. Manuf. Syst. 58, 3–21 (2021). https://doi.org/10.1016/j.jmsy.2019.10.001 26. Zhu, Z., Liu, C., Xu, X.: Visualisation of the Digital Twin data in manufacturing by using augmented reality. Procedia Cirp 81, 898–903 (2019). https://doi.org/10.1016/j.procir.2019. 03.223 27. Marriott, K., et al.: Immersive analytics: time to reconsider the value of 3D for information visualisation. In: Immersive Analytics. Lecture Notes in Computer Science(), vol. 11190, pp. 25–55. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01388-2_2 28. Bratchikov, S., Abdullin, A., Demidova, G.L., Lukichev, D.V.: Development of digital twin for robotic arm. In: Presented at the 2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC) (2021). https://doi.org/10.1109/pemc48073.2021.943 2535 29. Zhang, Z., Lu, J., Xia, L., Wang, S., Zhang, H., Zhao, R.: Digital twin system design for dual-manipulator cooperation unit. Presented at the 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) (2020). https://doi. org/10.1109/itnec48623.2020.9084652 30. Huynh, B.H., Akhtar, H., Sett, M.K.: A universal methodology to create digital twins for serial and parallel manipulators. Presented at the 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) (2019). https://doi.org/10.1109/smc.2019.8914195 31. Kaigom, E. G., Rossmann, J.: Toward physics-based virtual reality testbeds for intelligent robot manipulators - an eRobotics approach. Presented at the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2016). https://doi.org/10.1109/iros. 2016.7759171 32. Peruzzini, M., Grandi, F., Pellicciari, M.: Exploring the potential of operator interface and monitoring. Comput. Ind. Eng. 139, 105600 (2020). https://doi.org/10.1016/j.cie.2018.12.047 33. Markowitz, D.M., Bailenson, J.: Virtual Reality and Emotion: A 5-Year Systematic Review of Empirical Research (2015–2019). Center for Open Science, USA (2021). https://doi.org/ 10.31234/osf.io/tpsmr 34. Carrillo Quiroga, P., Chacón Hernández, J.C.: The perception of space in virtual reality, correlation between affordances and spatial presence. Entreciencias: diálogos en la sociedad del conocimiento 9, 1–22 (2021). https://doi.org/10.22201/enesl.20078064e.2021.23.77858 35. Lithoxoidou, E., et al.: A novel social gamified collaboration platform enriched with shopfloor data and feedback for the improvement of the productivity, safety and engagement in factories. Comput. Ind. Eng. 139, 105691 (2020). https://doi.org/10.1016/j.cie.2019.02.005

Machine Learning Model for Student Drop-Out Prediction Based on Student Engagement Lucija Brezoˇcnik1(B) , Giacomo Nalli2 , Renato De Leone2 , Sonia Val3 , Vili Podgorelec1 , and Sašo Karakatiˇc1 1 Intelligent Systems Laboratory, Faculty of Electrical Engineering and Computer Science,

University of Maribor, Koroška cesta 46, 2000 Maribor, Slovenia [email protected] 2 School of Science and Technology, University of Camerino, Camerino, Italy 3 School of Engineering and Architecture, University of Zaragoza, Zaragoza, Spain

Abstract. Nowadays, the issue of student drop-out is addressed not only through the prism of pedagogy, but also by technological practices. In this paper, we demonstrate how a student drop-out could be predicted through a student’s performance using different Machine Learning techniques, i.e., supervised learning and unsupervised learning. The results show that various types of student engagement are essential factors in predicting drop-out and the final ECTS points achievements. Keywords: Machine Learning · Student Drop-out · Academic Drop-out · Student Engagement · Student Drop-out Prediction

1 Introduction The problem of student drop-out has been raising concern increasingly because of the complexity of the issue [1]. It is relevant not only for the professors who want to minimize the number of students that do not complete their studies, but also to the tutors who work with students and, clearly, to the students themselves. Many papers have been written in the mentioned problem domain, but mainly from the pedagogical point of view [2–4]. For this research, one of the most meaningful results from their studies was the proven correlation between overall student engagement (behavioral, emotional, and cognitive) and academic achievement [5]. It is vital to emphasize that some student engagements can be tracked easily, e.g., demographic and academic background, but behavioral ones can be trickier. Usually, they are being tracked by Faculties Student ID cards, but the Faculty or University must provide them. However, this is not a norm for EU Universities. A few attempts at applying different Machine Learning (ML) techniques to the student drop-out prevention have been made [6–10]. Usually, the used datasets have been comprised of a few features being collected from one Faculty. Because of that, the aims of this paper are: – to define a set of features relevant to be collected for the later student drop-out identification; © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 486–496, 2023. https://doi.org/10.1007/978-3-031-31066-9_54

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– to define ML models able to predict student drop-out based on the students‘ performance; – to provide a list of the most informative features for student drop-out.

2 Machine Learning Algorithms The prediction of students’ drop-out based on their performance can be tackled through different approaches. For this reason, Sects. 2.1 and 2.2 present a brief overview of the most prominent learning approaches that were also used in our proposed method. 2.1 Supervised Learning In Supervised Learning [11], the training set is made of P input vectors x with corresponding P output vectors y (labels). Therefore, data and their corresponding “correct” answers are available in this paradigm. The aim is to learn a rule linking the inputs to their corresponding output values: f : x ∈ RN → y ∈ RM

(1)

Moreover, the machine must then be able to predict the output for never seen input values. The two main problems that fall into this category are Classification problems and Regression problems. In Classification problems, the goal is to classify data into a finite number of categories. In general, unless some specific encoding is utilized, M = 1 (there is only a single output value) and yp ∈ {1, . . . , K}. A special case is a binary classification, where it is customary to have yp ∈ {0, 1} or, even more often, yp ∈ {−1, +1}. In Regression problems, the output value is a real value (in this case M = 1, again), that is yp ∈ R. Similarly, the aim is to determine a function as in Eq. 1 that, for the given x, predicts the corresponding value y. 2.2 Unsupervised Learning In Unsupervised Learning [12], the training set is made of only the P input vectors, with no corresponding labels: p⎤ x1 ⎢ xp ⎥ ⎢ 2⎥ xp = ⎢ . ⎥ ∈ RN , p = 1, . . . , P ⎣ .. ⎦

⎡

(2)

p

xN Two main problems are being tackled in this domain: Clustering and Dimensionality Reduction. In clustering problems [13, 14], the aim is to identify similarities among the elements in the training set. Objects must be organized in clusters, so that the objects in a particular cluster are as similar as possible, and clusters themselves as different as possible. Therefore, the main aim is to maximize the similarity within clusters and

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the dissimilarity between clusters. Usually, clustering is conducted based on similarity measures (e.g., Euclidean distance) [15], which requires finding a structure in a collection of unlabeled data. Most clustering algorithms are based on two popular techniques, known as Hierarchical and Partitioned clustering [14]. In the Dimensionality Reduction problems [16–20] the goal is to transform the data from a high-dimensional space into a low-dimensional space. However, such lowdimensional representation must retain all the informative properties of the original data. The Principal Component Analysis (PCA) is the most utilized technique for this problem.

3 Student Engagement Data Data are valuable, but cannot be used if they are unrefined. Therefore, we first analyzed all the contributed student engagement data from the universities in Italy, Slovenia, Spain, Cyprus, and Lithuania. After a quick review of the shared data, we realized that the data collected by most universities are very sparse. Not only that, the data are usually too anonymized, and thus not usable. Both reasons could be attributed mainly to the GDPR law. On the other hand, sometimes the data are collected well, i.e., many parameters are being tracked per student, but are stored in multiple separated systems which cannot be linked. Lastly, even if universities collect data, they are very reluctant to share or use these data, even for research purposes. In our research, we tackled the following challenges while trying to make data fusion: – – – –

Heterogeneous data, Unstructured data, Insufficient amounts of collected parameters, Collected data differ across different universities.

In the preprocessing phase we defined the final set of features which can be grouped into four main areas that play a vital role in a student’s academic career. The main areas are: – Demographic characteristics (e.g., age, gender, and distance from the university); – Financial aspects (e.g., income, presence of a scholarship, and assigned free accommodation); – Cognitive and academic aspects (e.g., educational background, the study progress – in the university, and academic results); – Engagement level in university life (e.g., use of the students’ services and facilities). The final dataset comprises the following list of features: Numeric ID, Student’s gender; Name of the degree course; A binary value that determines if the student is active or not; First year of enrollment in the University; Actual year of enrollment (first, second or third); The status of the enrollment (if the student has to repeat the year); A binary value that indicates the student’s room on campus; the Number of meals per student at the University Canteen; A binary value that indicates if the student earned

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the scholarship; A binary value that determines if the student filled out the survey; an ID that indicates the interest of the student; A binary value that indicates if a student attended less than 50% of the total lectures; A binary value that indicates if a student never attended lectures; A binary value that indicates if a student attended more than 50% of the total lectures; the Number of acquired ECTS per student in the current year; and the Number of acquired ECTS per student from the first year degree. Those features have been collected for 412 students, 182 of them women and 230 men.

4 Proposed Model Prior to defining the most suitable ML model, we first had to address the main challenge: there is no direct measurement of student engagement. The solution was found in the student’s final grade feature, which we took as a proxy. Before deciding on the best model, we conducted multiple experiments. Firstly, we performed a regression analysis and treated the dependent variable (the student’s final ECTS grade) as a ratio. Equation 3 presents the calculation of the dependent variable denoted by y between the acquired credits and expected credits per study year. y=

total_credits number_of _study_years × 60

(3)

The aim was to predict the student’s performance based on our engagement data. Similarly, we conducted a classification analysis, but treated the dependent variable as nominal this time. Accordingly, we performed a discretization step. The latter converts a continuous range of y according to a (4):  1 if y ≥ 1, student_group = (4) 0 if y < 1 The student group 1 corresponds to students passing all obligations, and 0 represents the opposite. The following regression and classification algorithms were utilized for Supervised Learning: – – – –

CART decision trees; Random Forest ensembles; Gradient Boosting ensembles; Support Vector Machines.

In order to obtain the best clustering algorithm, an experiment was carried out in which we selected the algorithm that best determined the students’ different levels of engagement. The following four clustering algorithms were tested: – – – –

K-means; Agglomerative Cluster; Density-based spatial clustering of applications with noise (DBScan); Gaussian Mixture Models Clustering.

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5 Results All the tested methods were implemented in the Python programming language. The experiment was run on a computer with a Windows operating system and an Intel Core i7 processor with 16 GB of RAM. The Regression, Classification, and Clustering results are presented in the following sections. 5.1 Regression Results For Regression we utilized the five regressors mentioned in Sect. 4, and used the following performance evaluation metrics: Mean Squared Error (MSE), Mean Absolute Error (MAE), and Explained variance score (EVAR). Table 1 summarizes the obtained results. Table 1. Results of the regression analysis. Regressor

MSE

MAE

EVAR

Decision Tree Regressor

0.108

0.218

0.277

Random Forest Regressor

0.045

0.156

0.703

Gradient Boosting Regressor

0.041

0.157

0.726

Histogram-based Gradient Boosting Regression

0.045

0.167

0.701

SVR

0.045

0.159

0.706

The decision tree performed the worst out of all the regressors, with the highest errors and the lowest explainer variance. In the mean absolute percentage error it is evident that support vector regressors (SVR) are slightly worse than others. In general, we can observe that Gradient boosting, Histogram based Gradient boosting, and Random Forest performed the best.

Fig. 1. Features’ importance by the Random Forest Regressor.

Figure 1 shows the features’ importance of the Random Forest regression model. The feature surveys_completed, i.e., the percentages of the completed final subjects’ surveys,

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is the most important feature in the prediction made with Random Forest. This is followed by features att_more50 (more than 50% lecture attendance), level_topics_interest (interest in the topic of the lectures), and graduation_year_2018 (graduating successfully in the previous academic year). It is encouraging that gender and courses chosen do not play an essential role in the predictions. Otherwise, the model would show the biasness of predictions to some gender or courses and, therefore, present a severe case of the unfairness of the decisions.

Fig. 2. SHAP results for Random Forest Regressor.

Similar results of the most important features are also demonstrated in Fig. 2 with the SHAP value horizontal scatter plot. The latter plots each student (one dot) either more to the left, i.e., when the instance influenced the prediction in predicting the lesser values, or right, i.e., when the instance influenced the prediction in predicting the higher values. The color of the dots/instances represents the feature values. 5.2 Classification Results As mentioned in Sect. 4, the seven classifiers presented were implemented and evaluated using the following performance metrics: Classification Accuracy (ACC), F1-score, Precision, and Recall. Table 2 demonstrates the summarized results.

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Classifier

ACC

F1-score

Precision

Decision Tree Classifier Random Forest Classifier

Recall

0.897

0.794

0.818

0.771

0.904

0.787

0.923

0.686

Gradient Boosting Classifier

0.919

0.825

0.929

0.743

Hist Gradient Boosting Classifier

0.934

0.862

0.933

0.800

SVC

0.882

0.714

0.952

0.571

SGD Classifier

0.875

0.730

0.821

0.657

LGBM Classifier

0.956

0.912

0.939

0.886

The highest classification accuracy was obtained by the LGBM classifier (96%), followed by the Hist Gradient Boosting Classifier (93%), the Gradient Boosting Classifier (92%), and the Random Forest Classifier (90%). Similar results were also obtained for the F1-score.

Fig. 3. Features’ importance by the Random Forest Classifier.

In order to compare the results with those obtained by the regression analysis, we similarly first examined the Random Forest Classifier results in detail. Figure 3 shows the most important features, which are, once again, surveys_completed, att_more50, level_topics_interest, graduation_year_2018, meal_no, and status_reason_TIT. It is clear that both algorithms utilized in practice the same informative features, which are visible in Fig. 4.

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Fig. 4. SHAP results for the Random Forest Classifier.

5.3 Clustering Results After applying different ML algorithms, the next step was the cluster performance evaluation using Silhouette Analysis [21], which provides an insight into how the clusters change depending on the algorithm, and returns the natural trend of the grouped data. This was applied to each algorithm, to interpret and validate the consistency within the data. The range of the silhouette value S(i) is between [−1, 1]: – If S(i) is close to 1, the sample is far away from the neighboring clusters. Hence, the sample is well-clustered, and already assigned to a very appropriate cluster; – If S(i) is around 0, the sample is very close to the neighboring clusters and could be assigned to another closest cluster. Also, this indicates an overlapping cluster; – If S(i) is close to −1, the sample is assigned to the wrong cluster and placed somewhere between the clusters. Therefore, we need the coefficients to be as high as possible, in order to have good clusters. Comparison of different algorithms with the calculated silhouette values demonstrated that Agglomerative Cluster was the best algorithm compared to the others, and obtained the most accurate clusters, as Fig. 5 also shows.

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Fig. 5. Silhouette values of the clustering algorithms.

Table 3 depicts the differences between clusters of students’ profiles in terms of engagement. In particular, Cluster 0 represents students with meager participation in University activities, i.e., low attendance at lectures, a high number of repeating students (57%), low value of meals eaten at the University, and a low level of scholarships won (4%). Even if Cluster 1 has no students with scholarships, it comprises an average level of engagement, with an improvement in all categories. For example, attendance at lectures has a value of 142, which is also reflected in the number of repeating students (0%), and more meals eaten at the University. Cluster 2 represents highly engaged students at the University. These students have a high value for each feature, starting from the value of the high lecture attendance (349) that is related to the high average number of meals eaten (178). However, such behavior may reflect the students’ presence during the year at the University’s campus, not specifically to attend lectures. The high level of attendance benefits students, highlighted by the number of scholarships obtained (100%) and the 0% of repeated students. Table 3. Differences between clusters. Feature

Cluster 0

Cluster 1

Cluster 2

N° Students

176

172

68

N° Men

100 (57%)

88 (51%)

46 (68%)

N° Women

76 (43%)

84 (49%)

22 (32%)

N° Repeating students

101 (57%)

0 (0%)

0 (0%) (continued)

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Table 3. (continued) Attendance to lectures > 50%

0

142

349

Scholarship

8 (4%)

0 (0%)

68 (100%)

Average meals eaten by students

5

25

178

There is also a notable difference between clusters based on the acquired ECTS credits. The level of students’ engagement reflects the average ECTS points achieved. Thus, Cluster 0 represents the students most at risk, not only for the low value related to ECTS credits achieved (average of 67 credits), but also for the number of students that did not get any credits for a year. Into the latter group falls 25% of students, meaning that they found some difficulties in the study that affected their learning process. On the contrary, Cluster 1 and Cluster 2, characterized by good social interactions in the University, comprised a meager percentage of students who did not get credits (2% and 0% per Cluster 1 and 2, respectively) and higher ECTS points achieved, i.e., 79 and 85, respectively.

6 Conclusion This paper shows that Machine Learning can be used successfully to predict students’ academic performance. The latter plays a vital role in the educational system, because analyzing the students’ status helps to improve their services, and, consequently, academic performances, preventing drop-out and increasing motivation. Creating a robust model considering students’ demographic, family, and social aspects, along with academic attributes and behaviors, is a very challenging task. Making predictions needs a suitable source of information that can be utilized in multiple ways to improve the quality of education and services. The prediction of students’ engagement from academic data and personal habits, along with other features, is also a valuable tool for defining strategies for improving students’ services like tutoring, career guidance, didactics, and others. Universities must, primarily, join forces to achieve this goal, by standardizing features collected between institutions and countries. Acknowledgements. The authors acknowledge the financial support from the Slovenian Research Agency (Research Core Funding No. P2-0057), and the European Commission (Project Code 2020-1-ES01-KA203-082090).

References 1. Truta, C., Parv, L., Topala, I.: Academic engagement and intention to drop out: levers for sustainability in higher education. Sustainability 10(12), 4637 (2018) 2. Ruiz, N., Fandos, M.: The role of tutoring in higher education: improving the student’s academic success and professional goals. Revista Internacional de Organizaciones (12), 89– 100 (2014)

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3. Hellas, A., et al.: Predicting academic performance: a systematic literature review. In: Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, pp. 175–199 (2018) 4. Nicoletti, M.C.: Revisiting the tinto’s theoretical dropout model. High. Educ. Stud. 9(3), 52–64 (2019) 5. Lei, H., Cui, Y., Zhou, W.: Relationships between student engagement and academic achievement: a meta-analysis. Soc. Behav. Personal. Int. J. 46(3), 517–528 (2018) 6. Nalli, G., Amendola, D., Smith, S.: Artificial intelligence to improve learning outcomes through online collaborative activities. In: European Conference on e-Learning, vol. 21, pp. 475–479 (2022) 7. Lee, S., Chung, J.Y.: The machine learning-based dropout early warning system for improving the performance of dropout prediction. Appl. Sci. 9(15), 3093 (2019) 8. Burgos, C., Campanario, M.L., de la Peña, D., Lara, J.A., Lizcano, D., Martínez, M.A.: Data mining for modeling students’ performance: a tutoring action plan to prevent academic dropout. Comput. Electr. Eng. 66, 541–556 (2018) 9. Bedregal-Alpaca, N., Cornejo-Aparicio, V., Zárate-Valderrama, J., Yanque-Churo, P.: Classification models for determining types of academic risk and predicting dropout in university students. Int. J. Adv. Comput. Sci. Appl. 11(1), 266–272 (2020) 10. Oloruntoba, S., Akinode, J.: Student academic performance prediction using support vector machine. Int. J. Eng. Sci. Res. Technol. 6(12), 588–597 (2017) 11. Cunningham, P., Cord, M., Delany, S.J.: Supervised learning. In: Cord, M., Cunningham, P. (eds.) Machine Learning Techniques for Multimedia. Cognitive Technologies, pp. 21–49. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-75171-7_2 12. Barlow, H.B.: Unsupervised learning. Neural Comput. 1(3), 295–311 (1989) 13. Äyrämö, S., Kärkkäinen, T.: Introduction to partitioning-based clustering methods with a robust example. Reports of the Department of Mathematical Information Technology. Series C, Software engineering and computational intelligence, no. 1/2006 (2006) 14. Leung, Y., Zhang, J.-S., Xu, Z.-B.: Clustering by scale-space filtering. IEEE Trans. Pattern Anal. Mach. Intell. 22(12), 1396–1410 (2000) 15. Jain, A.K., Duin, R.P.W., Mao, J.: Statistical pattern recognition: a review. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 4–37 (2000) 16. Brezoˇcnik, L., Fister, I., Podgorelec, V.: Swarm intelligence algorithms for feature selection: a review. Appl. Sci. 8(9), 1521 (2018) 17. Brezoˇcnik, L.: Feature selection for classification using particle swarm optimization. In: IEEE EUROCON 2017–17th International Conference on Smart Technologies, pp. 966–971. IEEE (2017) 18. Karakatiˇc, S., Fister, I., Fister, D.: Dynamic genotype reduction for narrowing the feature selection search space. In: 2020 IEEE 20th International Symposium on Computational Intelligence and Informatics (CINTI), pp. 35–38. IEEE (2020) 19. Fister, D., Fister, I., Karakatiˇc, S.: Dynfs: dynamic genotype cutting feature selection algorithm. J. Ambient Intell. Humaniz. Comput. 1–14 (2022) 20. Karakatiˇc, S.: Evopreprocess—data preprocessing framework with nature-inspired optimization algorithms. Mathematics 8(6), 900 (2020) 21. Shutaywi, M., Kachouie, N.N.: Silhouette analysis for performance evaluation in machine learning with applications to clustering. Entropy 23(6), 759 (2021)

Prototyping IoT Technology Solutions Using LoRaWAN Infrastructure Amir Hajdar1(B) and Samim Konjicija2 1 Institute for Geodesy and Geoinformatics, University of Sarajevo, Patriotskelige 30, 71000

Sarajevo, Bosnia and Herzegovina [email protected] 2 Faculty of Electrical Engineering, University of Sarajevo, Kampus Univerziteta u Sarajevu, 71000 Sarajevo, Bosnia and Herzegovina

Abstract. IoT solutions are rapidly finding ways into our lives. They are gaining popularity not only for small scale home applications, but also for large scale industrial applications. We generally have a problem of managing and monitoring multiple devices so we have to automate our processes. This is especially true for large scale industrial applications. In order to learn how this automation can benefit us as well as find potential failures and bottle-necks, we often have to develop prototypes. These prototypes help us analyze potential problems and further improve our final, most efficient, solutions. The purpose of this paper is to present a prototype developed utilizing Long Range Wide Area Network (LoRaWAN) to communicate with IoT devices that can be used for many different types of home and industrial applications. Typical LoRaWAN architecture will be presented, and use of data collected from a water meter device and a prototype device for measuring air temperature will be demonstrated. Keywords: IoT · LoRaWAN · prototype · MQTT · TTN · InfluxDB · networking

1 Introduction In the late 90’s, the term “Internet of Things” (IoT) was first introduced by computer scientist Kevin Ashton. He proposed putting the radio-frequency identification (RFID) chips on products to track them through a supply chain [1]. During the coming years, more and more companies are introducing their own implementation of IoT devices such that almost every one of us is carrying and using at least one of those devices everyday (smart phones, bikes, vacuum cleaners and such). It is not only the consumer who is benefiting from IoT, but there are many enterprise level solutions that have been implemented in the past couple of decades including smart city implementations (power, traffic, water and waste management, etc.). Along with IoT, new network infrastructure specification was introduced in 2015 – Long Range Wide Area Network (LoRaWAN) [2]. This low-power wide area networking protocol is built on top of LoRa radio modulation to wirelessly © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 497–503, 2023. https://doi.org/10.1007/978-3-031-31066-9_55

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connect (LoRa) devices to the internet and provide management capabilities of those devices and gateways. LoRaWAN has multiple benefits such as: ultra-low power, long range, indoor penetration, license free spectrum, geolocation, high capacity, end-to-end security, low cost and many others [3]. With all these new possibilities, we are faced with managing our ideas and constantly trying to implement new ones [4]. Experience shows that everything works great in theory, but in practice, we face many challenges. Therefore, prototyping is necessary to help us analyse our idea better and foresee potential issues with our final product. The prototype will result in better designed product as it also gives us feedback from end users. Furthermore, it will reduce development time as we will be able to better manage project risks. Skills needed to properly develop an IoT prototype are both hardware and software full-stack development skills, as well as networking and connectivity troubleshooting skills.

2 Prototype Components The IEEE defines prototyping as a development approach promoting the implementation of a pilot version of the intended product. Therefore, prototyping is a development approach of a pilot product which will lead to final solution. Final solution will then be focused more on specifications than on actual implementation [5]. While designing a prototype, it is important to identify all of the components necessary for implementing a solution. For our prototypes, we were able to classify components in the following way (Fig. 1):

Fig. 1. Main components of our prototypes’ architecture

2.1 LoRaWAN Water Meter Prototype Currently, there is a growing demand for water resources, which means that monitoring these resources is highly important. If we are able to collect this data, we can first

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calculate and then do quantitative and qualitative analysis. So, we can conclude that there is a need for implementation of water meters in general public to monitor this activity. Systems are currently being developed to justify these needs and even AI-based systems are available [6]. For our purpose of developing a prototype, we have chosen QALCOSONIC W1 water meter and decided on the following architecture as it is stable and well passed the development stage (Fig. 2):

Fig. 2. LoraWAN water meter prototype architecture

Water meter QALCOSONIC W1 is an ultrasonic device often used in industrial applications. It utilizes several communication protocols: LoRaWAN, M-Bus, and NBIoT. Since it is ultrasonic device, it is highly accurate while providing information about water consumption. It has additional capabilities but they were not considered while analysing payload information as that was outside of the scope of this prototype. We used a MikrotikwAP LR2 kit LoRa gateway on-site in order to connect the device to LoRaWAN infrastructure. This gateway is also connected to the internet to enable configuration and monitoring of all traffic communications. Further, the Mikrotik gateway is connected to the global LoRaWAN network (The Things Network - TTN) which provides all needed tools to easily build IoT applications including MQTT server which we used to forward water meter payload messages to our server (Raspberry Pi 3) over internet. Our Raspberry Pi is used as both database and application server where applications are installed to properly process received data (Node-RED), store it in a time series database (InfluxDB) and present it (Grafana). All of these applications are open-source tools and can easily be downloaded from the internet. Since LoRa is RF modulation technology for low-power wide area network, it is enabling LoRa device (water meter) to send payload messages via Mikrotik gateway to The Things Network which acts as a gateway to forward these messages to our server for further processing. QALCOSONIC W1 water meter sends 48 bytes of data including current date and time, status code, current volume, logged date and time, volume at logged date and time and other historical values of water flow. TTN has a role to register this water meter using LoRa activation keys. These keys are stored directly

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on the water meter, and device and server start the communication when keys inside the device and TTN server are matching. TTN also provides a handy tool to split the payload information into bytes and sends it to our server as a JSON object. We further used a JavaScript function to decode the payload and insert information into our time series database. Finally, Grafana, as an interactive data-visualization platform, is used to present the data. Grafana allows users to create dashboards to visualize data. We created two panels in our dashboard to display water flow information of a water machine being used during hours of 10:30 and 12:00, and second one to display the geospatial data of our water meter (Fig. 3).

Fig. 3. Water meter dashboard

2.2 DHT11 Temperature Measurement Prototype Developers of IoT devices typically use microcontrollers as main component of a device. By connecting one or more sensors and a LoRa transceiver to a microcontroller, the device can be programmed to forward measurements through a LoRaWAN network to an application which processes the acquired data. As an example, we used a popular ESP32-based board with integrated LoRa transceiver to forward temperature measurements from temperature and humidity sensor DHT11 to The Things Network (Fig. 4). The application for ESP32 was developed in

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Micropython, a popular implementation of subset of Python 3 programming language for microcontrollers.

Fig. 4. Prototype of IoT device for temperature measurement

Flowchart on Fig. 5 represents the application which executes on the IoT device.

Fig. 5. Diagram of application running on the prototype device

After powering up the device, an initialization of all necessary modules is executed. The I2 C connection to the DHT11 sensor is initialized, as well as the SPI connection to the LoRa transceiver module. The transceiver module is configured according to the regional

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parameter settings (EU868), and initial spread factor (SF7), bandwidth (125 kHz), and initial LoRaWAN channel frequency (868.100 MHz) are written to the module. Since the used ESP32 module has OLED display, it is also initialized, so that information on the current measurements and result of data transmission can be displayed. Then the application enters an infinite loop: • Temperature value is acquired from the DHT11 sensor. • A LoRaWAN data frame is generated, with payload which carries timestamp of the measurement and value of the temperature. The payload is encoded using Base64 encoding. The data frame is transmitted, and information about measurement and result of transmission (successful, unsuccessful) is presented on OLED display. • The device enters a sleep state with predefined duration. When the device wakes up, the loops starts from the beginning. It is important to know that LoRaWAN network, as well as the state regulator define allowed duty cycle, i.e. total on-air time during 24-h period. The device should be configured taking this limit into account. Information on the received data frame is displayed in the TTN administrative console (Fig. 6).

Fig. 6. Received data frames are displayed in the administrative console

Data received by the TTN is then available using supported integrations, which enables access by third-party user applications. Beside the above-mentioned approach which uses MQTT protocol, another very simple and frequently used API is REST. The TTN network server can also send a downlink message to the device, which can either contain a command to the device (changing data rate, changing frequency, etc.), or can contain a payload with data sent to the application which is running on the device.

3 Conclusion So as the world continues to be connected, data and systems within it must evolve to handle new types of IoT devices. In this paper, we presented examples of technology infrastructure needed to build a project utilizing LoRaWAN network infrastructure by developing two working prototypes. We used small IoT devices, water meter and temperature sensor, within TTN to collect data. We described theoretical background of our work, discussed the choices made during the implementation phase, and also provided results of our simulations, identifying potential failures and bottlenecks. Of course, this is just the beginning of next steps where we can utilize these technologies to implement solutions in smart cities.

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References 1. Zhang, M., Sun, F., Cheng, X.: Architecture of Internet of Things and its key technology integration based-on RFID. In: 2012 Fifth International Symposium on Computational Intelligence and Design, pp. 294–297 (2012) 2. LoRa Alliance Technical Committee: LoRaWAN Link Layer Specification 1.0.4 (TS001– 1.0.4), LoRa Alliance (2020) 3. Haxhibeqiri, J., De Poorter, E., Moerman, I., Hoebeke, J.: A survey of LoRaWAN for IoT: from technology to application. Sensors 18(11), 3995 (2018) 4. Semtech Corporation: LoRa Devices – Smart Utilities – Use Case Collection, Semtech (2018) 5. Kordon, F., Luqi: An introduction to rapid system prototyping. IEEE Trans. Softw. Eng. 28(9), 817–821 (2002) 6. Ayman, N., Abdessadek, A., Khalid, A., Chouaib, E.H.: A fully AI-based system to automate water meter data collection in Morocco country. Array 10, 100056 (2021)

A Review of Research Progress and Application of Wavelet Neural Networks Tonghao Wang1 , Vincenzo Guercio2 , Piercarlo Cattani3 , and Francesco Villecco4(B) 1 College of Information and Electrical Engineering, China Agricultural University,

No. 17 Tsinghua East Road, Haidian District, Beijing 100083, China 2 Engineering School, Deim University of Tuscia, Largo dell’Università, 01100 Viterbo, Italy 3 Department of Computer, Control and Management Engineering,

University of Rome “La Sapienza”, via Ariosto 25, 00185 Roma, Italy 4 Department of Industrial Engineering, University of Salerno, via Giovanni Paolo II 132,

84084 Fisciano, Italy [email protected]

Abstract. Artificial Neural Network (ANN) has been used extensively and constantly developed. The combination of wavelet transform theory and the neural network has become an important branch to explore the optimization of neural network structure, and Wavelet Neural Network (WNN), a special network structure, was born. This paper reviews WNN’s development and summarizes the system structure and algorithm implementation and presents derivative models and cutting-edge applications with obvious characteristics. The sorting and analysis of the above contents show that the combination of wavelet theory and neural network algorithm can make the network model have the advantages of fast convergence speed and high model accuracy, and has a rapid development trend in many fields such as audio signal and image processing. The work of this paper is intended to provide a reference for potential applications based on WNN and new network model design ideas. Keywords: Wavelet Transform · Wavelet Neural Network

1 Introduction The Artificial Neural Network (ANN) is a nonlinear network system formed by simulating the information processing mode of the neural system in the human brain, taking neurons as the basic structural unit, and connecting and combining the neurons. In ANN, the interconnection between neurons enables the neural network to process large-scale information. The methods of error back propagation and parallel distributed processing enable ANN to have a variety of excellent characteristics, such as fast computing ability and self-learning ability, reasoning ability, nonlinear mapping, as well as adaptive and fault-tolerant capabilities, which can solve large-scale complex nonlinear problems. The Wavelet has been studied on a large scale and developed rapidly since it was formally proposed in the 1980s. Wavelet is a waveform with an effective finite duration, which is good at representing piecewise regular signals and images sparsely. Wavelet © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 504–515, 2023. https://doi.org/10.1007/978-3-031-31066-9_56

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transform is to obtain a series of wavelet bases with different resolutions by scaling and translating the basis function using a specific wavelet generating function, and use them to approximate the signal. The appearance of wavelet solves the problem that the Fourier transform can only localize time and frequency at constant and equal intervals. It can adaptively provide more precise frequency information in low frequency and more precise time information in high frequency. With the deepening of theoretical research on ANNs, one of its important development directions is to combine it with fuzzy logic [1, 2], genetic algorithm [3, 4], wavelet analysis, rough set theory [5, 6], grey system [7, 8], and other theories. The neural network has self-learning and adaptive capabilities, while wavelet transform has time-frequency localization and multi-resolution characteristics. Some researches have begun to try to integrate the good properties of wavelet into ANNs. In the past, the simple combination method was to preprocess the signal with wavelet analysis, that is, through wavelet transform, the signal is decomposed into a series of wavelet coefficients as features, which are input into the neural network for subsequent processing. The wavelet space is used as the feature space of the network input, but this combination is obviously loose. The Wavelet Neural Network (WNN) integrates the wavelet transform into the deeper level of the neural network, fully inheriting the advantages of both. This idea was first proposed by Pati and Krishnaprasad [9, 10], who proposed a discrete affine wavelet network model to truly link the neural network and wavelet transform; However, WNN was formally proposed as a concept in the work of Zhang and Benveniste [11, 12] in 1992; Szu et al. [13, 14] gave WNN based on continuous wavelet transform, and constructed WNN models for signal representation and feature extraction; Kugarajah and Zhang [15, 16] proposed a single scale multidimensional wavelet framework, which extends the application scope of WNN to a higher dimension. Zhang [17, 18] later proposed a wavelet network construction algorithm for nonparametric regression estimation. In the framework of nonlinear process modeling, Oussar et al. [19, 20] proposed a training algorithm for a feedforward wavelet network, which was used as a nonlinear dynamic model; and in the subsequent work, and the initial initialization process of the parameters of the feedforward wavelet network was given. The basic unit and overall structure of the network are determined according to the wavelet analysis theory, which can reduce the experimental and blindness in the design of traditional ANN structure. Compared with other neural networks, the WNN model is more interpretable and has stronger learning ability. It has higher accuracy, higher accuracy and faster convergence speed for the same learning task, and has great application research value.

2 Basic Model of WNN The basic idea of WNN is to replace the hidden layer neurons of neural network with wavelet, specifically, to set the activation function of hidden layer as wavelet function. The basic network structure of WNN is shown in Fig. 1, where Xi , (i = 1, 2, 3, . . . , L) is the input data, ψj , (j = 1, 2, 3, . . . , M ) is the wavelet basis function, Fk , (k = (1) 1, 2, . . . , N ) is the output of the network, ωi,j is the connection weight between the

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i-th neuron in the input layer and the j-th neuron in the wavelet layer (i.e. the hidden (2) layer), and ωj,k is the connection weight between the j-th neuron in the wavelet layer and the k-th neuron in the output layer (i.e. the hidden layer) [21, 22].

Fig. 1. The basic structure of the WNN

According to the definition of continuous wavelet transform (CWT), for WNN with continuous parameters, the wavelet function can be expressed as: ψj (t) = ψ(

t − bj ), (j = 1, 2, 3, . . . , M ) aj

(1)

where aj is the scale parameter, and bj is the displacement parameter. At this point, the output of the neural network is: ⎤ ⎡ L  (1) M M ⎢ ωi,j xi − bj ⎥   ⎥ (2) (2) ⎢ i=1 (2) Fk = ωj,k ψj = ωj,k ψ ⎢ ⎥(k = 1, 2, . . . , N ) ⎦ ⎣ aj j=1

j=1

For continuous wavelet transform, its basis function can process continuous signals and discrete signals, but this will also lead to high redundancy. The correspondence between wavelet parameters and functions is not fixed, which involves nonlinear optimization, similar to traditional BP neural networks. But the addition of wavelet theory can help the initialization of the network and make the loss in the training process of the network converge faster. Based on WNN in the wavelet framework, the wavelet basis function in the wavelet function can be expressed as: −mj

ψj (t) = ψ(a0

t − nj b0 ), (j = 1, 2, 3, . . . , M )

(3)

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where a0 is the scale parameter, and b0 is the displacement parameter [23, 24]. For Fig. 1, the output of a simple three-layer WNN can be expressed as:

L  M M    (1) −mj (2) (2) Fk = ωj,k ψj = ωj,k ψ ωi,j a0 xi − nj b0 (k = 1, 2, . . . , N ) (4) j=1

j=1

i=1

WNN allow a deterministic network hierarchy and have a highly interpretable explicit method for the construction and initialization of thresholds and the number of hidden nodes. A “wavelet library” can be constructed by using wavelet decomposition. On the contrary, each neuron in the WNN can also be constructed using the most suitable wavelet selected from the “wavelet library”. Generally, the wavelet library can be constructed by orthogonal wavelet or wavelet frame. But for orthogonal wavelets, if orthogonal wavelet bases are generated, the restrictions on wavelet functions will be very strict [25, 26], which will bring difficulties to the construction of wavelet libraries and even WNN. The wavelet frame can be realized by translating and expanding the selected parent wavelet, which is much simpler than the former. Gao et al. [27] demonstrated that compactly supported non orthogonal wavelet family is an ideal choice in function approximation; In WNN, due to the input data, the wavelet family is likely to contain a large number of wavelets, so it is more convenient to choose to use truncated wavelet family. However, arbitrary truncation will lead to large errors [28], so in order to construct the WNN with the best performance, we must choose the wavelet that is most suitable for WNN. Cannon and Slotine [29] used an amplitude-based method to eliminate wavelets with small coefficients. The remaining wavelets are sorted after elimination, and the wavelet with the highest ranking is utilized to construct the WNN. Zhang [17] proposed three alternative methods, Residual Based Selection (RBS), Orthogonalized Stepwise Selection (SSO), and Backward Elimination (BE) to reduce and rank wavelets in the wavelet library.

3 Derivative Model of Wavelet Neural Network 3.1 Recurrent Wavelet Neural Network Some researchers combine the ideas of Recurrent Neural Network (RNN) and WNN, and propose a Recurrent Wavelet Neural Network (RWNN). The simple RWNN is similar to the traditional recurrent neural network. The value of the hidden layer neuron of the RNN is not only determined by the current input, but also affected by its own or the output value of other neurons in the hidden layer. Zhao et al. [30] constructed a simple RWNN, which is very similar to the basic WNN in structure, but the input of the wavelet layer comes from the input layer and its own output. Becerikli [31] proposed a type 2-fuzzy RWNN. This new structure has excellent performance in modeling nonlinear systems, and has faster convergence speed, higher accuracy and faster response than other models. Figure 2 is the basic architecture of its designed RWNN. Deng et al. [32] proposed an autoregressive wavelet neural network (SRWNN) for multi-dimensional data, which splits the multi-dimensional data and adds a product layer after the hidden

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layer, so that each dimension of data passes through the hidden layer and then passes through the hidden layer. The product layer is processed and then output; it avoids the complexity problem caused by constructing multi-dimensional wavelets, and its structure is presented in Fig. 3. The solution proposed by Alarcon-Aquino et al. [33] is similar to Deng’s idea, and proposes an autoregressive wavelet neural network based on multi-dimensional radial wavelets named MRW-RNN, and gives the network structure as shown in Fig. 4. The input vectors are processed by the radial function of the MRW unit as shown so that they can be used for 1D wavelet functions, reducing the complexity of the network.

Fig. 2. Structure of Type 2-Fuzzy RWNN

Fig. 3. Structure of SRWNN

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Fig. 4. Structure of MRW-RNN

3.2 Wavelet Convolutional Neural Network The MALLAT algorithm proposed by Mallat [34, 35] associates wavelets with filters, and its core idea is to convolve the input signal vector with low-frequency and high-frequency filters, and finally obtain low-frequency signals and a series of high-frequency details. The CNN kernel can also be regarded as a filter. The initialization of the CNN kernel will play an important role in the convergence speed of the network training and the overall performance of the network. A good initialization method will make the network have less training time and more good performance. Therefore, wavelet kernels are a good way to initialize CNN convolution kernels. Based on this idea, the wavelet can be replaced by the convolution kernel in the CNN, which is called the wavelet kernel to initialize CNN. The use of wavelet kernel will produce a useful approximation of the signal after convolution operation in a short time [36]. However, there are few researches on wavelet convolution neural networks. Ray et al. [37] designed a network model called WKNet, which replaces the convolution kernel of the first convolution layer of standard CNN with a series of wavelet functions, the basic model of which is shown in Fig. 5. However, similar to the initial loose combination of WNN structure, the study did not further combine wavelet transform and CNN.

Fig. 5. Convolution neural network with wavelet kernel added

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Some researchers [38] replaced the convolution kernel with a wavelet kernel, and the network structure is shown in Fig. 6. The selection of the wavelet kernel and the determination of the network size are based on the experimental test results. Using the proposed model for acoustic sensor data analysis, compared with the original network model before improvement, their proposed network has less training time and achieves higher output accuracy.

Fig. 6. Wavelet Convolutional Neural Network

Focusing on the similarities between the MALLAT algorithm and the convolutional neural network in terms of convolution operations, the structure of CNN can be used to obtain wavelets in a way of learning rather than mathematical reasoning, and the obtained wavelets can be made to belong to the original input. The representation of the type of data is more sparse and precise, and the learned wavelet can be put into the network model mentioned above in the follow-up work, which can further improve the network performance. Combining the cascade idea of the wavelet transform, Recoskie and Mann [39, 40] designed a convolutional neural network that learns wavelets from data, which can learn wavelets in a targeted manner. The basic structure is shown in Fig. 7.

Fig. 7. Learning wavelet by using CNN structure

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3.3 Combination of WNN and Other Algorithms Some researchers take the above network model as a part of the overall design model and give some derivative models of wavelet neural networks according to different application situations. Lei et al. [41] used rough sets to optimize the wavelet neural network structure on the initial input of the network to reduce the redundant properties of the data; Jafarzadeh Ghoushchi et al. [42] used an extended Fuzzy Wavelet Neural Network (FWNN), both fuzzy set rules use different fuzzy wavelet functions to transform the input space into subspaces. A unified hybrid learning algorithm is used in the extended FWNN method to obtain the optimal scale of parameters. Xu et al. [43] proposed a Graph Wavelet Neural Network (GWNN), which is a multi-layer convolutional neural network, which defines a convolution operator through wavelet transform and convolution theorem [44]; separates feature transformation from convolution and learns in all features Unique convolution kernel, which greatly reduces the number of parameters. Liu et al. [45] replaced the activation function of the convolution layer in CNN with the wavelet scaling function, and made a further improvement - replacing the full connection layer of CNN with WNN and the experiment proves that the training accuracy and classification ability of this model are superior to CNN.

4 Frontier Applications of Wavelet Neural Networks WNN has been successfully applied in various research fields. Liu [46, 47] proposed a dense self guided wavelet network (DSWN) for real world image denoising; Zhu [48] proposed a new video super-resolution new spatio-temporal matching network (STMN) working in the wavelet domain, reducing the dependence on motion estimation; Zhao [49, 50] proposed a multi-scale wavelet network (MS Net) for pediatric echocardiography segmentation, which solves the problems of information loss and low detail utilization of existing neural network based image segmentation algorithms; Tiddeman [51] proposed a learning based wavelet transform and proved its practicability in solving many linear inverse problems; Wei [52] proposed a multi-scale wavelet residual network (MWResNet) to restore sparse view CT images, which solves the problem of stripe artifacts and noise that may be generated in sparse image reconstruction; Ding [53, 54] combines the ideas of wavelet and network topology analysis to provide a new method to identify the relationship between non random species across scales and along gradients using continuous or missing ecological data. WNN has also been applied in pavement crack detection [55, 56], hydrological prediction [57, 58], and price prediction [59] and other fields [60].

5 Conclusion One of the development directions of the ANN is to combine it with some interdisciplinary algorithms, to obtain a better way of model building and training. Many studies have integrated the wavelet theory into the neural network, and the network model of the WNN was born. This paper takes the development and improvement of WNN model as

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the main context, summarizes the common structure of WNN, and combines the examples of the WNN structure to give CNN and The network model and other derivative models that combine RNN and wavelet theory; the choice of connection mode with RNN, and how to design a suitable wavelet kernel in CNN are directions worthy of further research. WNN can avoid the blindness of traditional neural network design, and compared with the basic network, the performance of wavelet neural network in terms of training speed, feature extraction ability, and model accuracy can be significantly improved value.

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Motion Synchronization for Bilateral Control Systems - Viteški´c, Amel Ramdedovi´c, Šejla Džakmi´c(B) , Nada and Mohammad Adnan Diab Alrefaee Electrical and Electronics Engineering, International University of Sarajevo, Hrasniˇcka Cesta 15, 71 000 Sarajevo, Bosnia and Herzegovina [email protected]

Abstract. This paper describes motion synchronization as essential problem in bilateral control systems. The proposed motion synchronization method is defined as a constrained motion in which generalized control errors are function of position and velocity of synchronized systems. Transformation from operation to configuration space is applied to define the generalized error such that it constraints the output of closed loop system by desired dynamics. Local controllers are implemented to ensure the stability of the system and enforce desired convergence rate with short time response. The obtained results prove fast response and fully synchronized motion control. The application of the proposed system is described in detail and evaluated by simulation and experiments. The experimental results will serve as a basis for the next stage of research, which is Cyber Physical Systems and teleoperations. Keywords: Bilateral control · synchronization · motion control

1 Introduction The advances in motion control systems push the boundaries and bring new challenges to researchers in development of real world haptics, robotic teleoperation and motion control theory. The application field is growing from medicine to manufacturing and construction, especially with the improvement of haptic transmission tehcnologies that includes recent development of 5G wireless technology [1–3]. Based on the application, motion control implies position, velocity and force control of mechanical systems. In trajectory tracking problems, where robot should follow a specific path, fast and precise position and velocity control should be implemented. If interaction with the environment is established, haptic information is involved into control design and force control problem needs to be solved. Transmission of haptic information in robotic teleoperation attracts a lot of attention as it helps to improve the manipulation of remote objects and conduct different tasks. Bilateral control [4–6] is one of the essential technologies for haptic transmission that enables transfer of sense of touch to remote places. This means that operator that controlls the master device feels © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 516–523, 2023. https://doi.org/10.1007/978-3-031-31066-9_57

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the enviroment and interaction force like he is touching directly. The authors in [6, 7] describe the smooth position and interaction force control in such systems. Bilateral control system consists of master and slave robot. When (human) operator controlls the master robot, slave robot is tracking the master’s trajectory. The main objective of bilateral teleoperation systems is to establish stability and synhronization of two systems. Two systems are functionally related in such a way that master is controlled by the operator and slave follows master’s state so they achieve fully synchronized motion and to accomplish the action-reaction law between them [8]. Several authors proposed control aglorithms to solve this control problem [9, 10]. The authors in [9] propose position and velocity based state feedback algorithms, obtaining passive coordination control to synchronize robots in free motion. In [11] synchronization based on vector bounded input saturation analysis is described. Synchronization in [12] is established by velocity feedback filter and compensation method. This paper describes motion control algorithm for synchronization of velocity of two systems with possible extension to the position synchronization. As example two DC motors are considered. The basic idea consists in setting the control error as a function of the motion of both systems, thus establishing clear relationship with operational requirements. The control is then designed to make stable a zero solution of established errors. The presentation is organized as follows: in Sect. 2 the problem statement, design and simulation results are shown, in Sect. 3 the experimental verification is shown and in Sect. 4 the conclusion is presented.

2 Problems Statement and Simulation Results Work in this paper is established on two DC rotational motors, master and slave. DC motor control is implemented through cascade control which is based on inner and outer loops. Inner loop is the current loop and the outer loop is designed to establish a desired functional relationship – the synchronization of the two systems. The dynamics of single-DOF systems used in this paper can be described by the following:  J1 d ω1 dis dt = Kt1 i1 − T1 (1) J2 d ω2 dis dt = Kt2 i2 − T2  V1 = L1dtdi1 + R1 i1 + Ke1 ω1 (2) V2 = L2dtdi2 + R2 i2 + Ke2 ω2  d θ1 dt = ω1 (3) d θ2 dt = ω2 where θ and ω stand for the position and velocity respectively; V is input voltage, Ke stands for the back emf constant and Kt stands for the torque constant, J describes the system inertia and T dis is generalized system disturbance. A system from (1) can be di = V − Ri − Ke ω. rearranged as: L dt

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2.1 Synchronization The goal is to establish a synchronized motion of the master and slave systems each described by a dynamical model given in (1)–(3). The variables on the motor 1 and motor 2 are labeled with subscripts m and s respectively. The operational requirement is to that both systems maintain synchonized motion constrained to follow the reference velocity ωref . These requirements could be stated as a design of a control algorithm that enforce the converging and stability of the zero solution of the operation tracking errors e− → 0 and e+ → 0: e− = ω1 − ω2

(4a)

e+ = ω1 + ω2 − 2ωref

(4b)

 The control error vector is defined as eT = e+ e− . From description of the plants (1)–(3) the dynamics of the control error can be expressed as:   T1dis T2dis Kt1 Kt2 − e˙ = i1 − i2 − − (5a) J1 J2 J1 J2   T1dis T2dis Kt1 Kt2 d ωref + i1 + i2 − + +2 e˙ = (5b) J1 J2 J1 J2 dt 

T dis

If total disturbance value is defined as: d + = J11 + then the dynamics of tracking error is obtained by: 

e˙ − e˙ +



T2dis J2

˙ and d − = +2ωref

  −  −  Kt1 Kt2 ref

− i1 i− d i = + + with = KJt1 KtJ2 ref + + 1 2 i d i i 2 J J

T1dis T2dis J1 − J2 ,



1

(6)

2

The d + and d − could be compensated using intergral control. The resulting description is given by two decoupled first order dynamical systems with unknown but matching disturbances. The selection of control for such systems is a straight-forward task. Here PI controller are used but combination of a proportional controller and disturbance observer is also applicable. Let the control inputs i− and i+ are obtained by PI controllers of the tracking error (e− and e+ ):  t i− = Ki e− (τ )d τ + Kp e− (t) (7a) 0

i+ = Ki



t

e+ (τ )d τ + Kp e+ (t)

(7b)

0

Implementing closed loop dynamics of Eqs. (7a) and (7b) into (5a) and (5a) results into second order tracking error dynamics: e¨ − − Kp e˙ − (t) − Ki e− (t) → 0 ∴ d˙ − → 0

(8a)

Motion Synchronization for Bilateral Control Systems

e¨ + − Kp e˙ + (t) − Ki e+ (t) → 0 ∴ d˙ + → 0

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(8b)

These dynamics for Ki < 0 and Kp < 0 will ensure the convergence of the synref ref cronization error to zero. From selected i+ and i− one can determine i1 and i2 which will pass through the second (inner PI controller) such that cascaded structure compensates for the disturbace of the system. Park’s transformation will result into reference current values:

− i + i+ J1 ref (9a) i1 = · Kt1 2

+ i − i− J2 ref i2 = · (9b) Kt2 2

2.2 Simulation Results Described system is designed in Simulink. A Fig. 1 shows block diagram of simulated system, with synchronization obtained by tracking error and velocity. PI controllers are implemented to controll the inputs to the systems.

Fig. 1. Block diagram of simulated synchronized systems

The simulation results for tracking error and angular velocity are presented in Fig. 2. It is visible that velocity signals, both ω1 and ω2 have fast and stable response, reaching the reference value in 0.06 s. Similarly for the tracking error that go to zero either immediately or in about 0.06 s.

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Fig. 2. Tracking error and velocity for master and slave device

3 Experimental Evaluation The experiment was conducted in order to corroborate the simulated results presented in the previous section. It can be stated that the reference angular velocity tracking for the constant input has been achieved with the appropriate asymptotic convergence of the error. The experimental set up consists of the following devices that are utilized in obtaining the results presented in the following figures: 1. TMS320F2837xD, Texas Instruments DSP module. 2. 2x BOOSTXL-3PhGaNInv, Texas Instruments Inverters (used as 2 × H bridge modules, includes highly precise current measurment). 3. 2x DC motors (stepping motor and brushed permanent magnet DC motor) 4. Picoscope 2000 Series Oscilloscope 5. 2x VoltCraft (VLP-1303 PRO) and Mechatro Lab II (0–60 V DC) power supplies. 6. 2x Encoders WDG 50B (Fig. 3).

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Fig. 3. Experimental setup utilized for the synchronization of the two DC motors

Based on the mathematical derivation and simulated results, the depiction of angular velocity tracking is done for the constant 4 rev/s reference value (taken as a float 32-bit variable in DSP) and implementing the cascaded structure of PI control. Given reference value is reached deeming the overall implementation as means to validate the previously mentioned simulated outcomes. Moreover, the sampling rate of the measured currents (i1 , i2 ) and velocities of each motor is taken to be 10 kHz. However, sampling rate used for plotting of the measured data obtained for the velocities (ω1 and ω2 ) is 1000 times slower (10 Hz), implying that for each 1000th sample utilized for control, we are plotting one on the graph. The overall plotting was accomplished through dsp in real-time and

Fig. 4. Measured synchronized angular velocities w.r.t their reference value

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converted to.csv file after 80 samples. It should be noted that each sample is taken every 0.1 s and the time interval plotted on the following graph is 4 s (Figs. 4 and 5).

Fig. 5. Measurement of the errors e1 , e2 for the synchronized DC Machines

The experiment is idle until 47th sample such that one may observe the transient and steady states of the synchronized DC machines. Additionally, since e1 = ω1 − ω2 the initial conditions for both angular velocities are zero, which would explain why the graph is constant in the pre-experiment stage and given that e2 = ω1 + ω2 − 2ωref rev and ωref = 4rev s the initial condition for the second error is expected to be −8 s . It is important to mention that the inner current loops are taken to have 5000 times faster response than the outer loop upon which the overall control resides and influences the outer control loop such that both errors converge to zero leading to establishment of the synchronization of the angular velocities. The minor ripple is observed on both graphs due to the limitation of the equipment and the presence of noise in the system which reaches maximum of 5% of variation at the peak of the ripple’s value.

4 Discussion and Conclusion To summarize, the synchronization of two DC motors is demostrated through both simulation and real life experiment. Moreover, the tracking of the reference was achieved and e− and e+ responses were converging to zero in both simulation and experiment, implying that synchronization of two different DC motors was attained. The cascaded structure with PI controllers (inner and outer loops) compensated the disturbance of the system and one major drawback to its implementation is the tuning of the Kp and Ki parameters of each PI controller. In the future work, we are planning to utilize disturbance observer method instead of the PI controller to estimate the disturbance and eliminate it such that appropriate tracking of the reference value is obtained. Finally, the utilization of the given project may serve as a starting point to Cyber Physical Systems and telerobotics.

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Ackonwledgement. This work is partially supported by Ministry of Science, High Education and Youth, Sarajevo, Bosnia and Herzegovina. Project number 22 on the following link: https://mon.ks.gov.ba/sites/mon.ks.gov.ba/files/2022-08/Odluka%20o%20utvr%C4% 91ivanju%20kona%C4%8Dne%20liste%20dobitnika%20sredstava_Program%20B.1.pdf.

References 1. Hangai, S., Nozaki, T.: Haptic data prediction and extrapolation for communication traffic reduction of four-channel bilateral control system. IEEE Trans. Ind. Inform. 17(4), 2611–2620 (2021). https://doi.org/10.1109/TII.2020.2995627 2. Wang, Z., Chen, Z., Zhang, Y., Yu, X., Wang, X., Liang, B.: Adaptive finite-time control for bilateral teleoperation systems with jittering time delays. Int. J. Robust Nonlinear Control 29(4), 1007–1030 (2019). https://doi.org/10.1002/rnc.4423 3. Condoluci, M., Mahmoodi, T., Steinbach, E., Dohler, M.: Soft resource reservation for lowdelayed teleoperation over mobile networks. IEEE Access 5, 10445–10455 (2017). https:// doi.org/10.1109/ACCESS.2017.2707319 4. Forouzantabar, A., Talebi, H.A., Sedigh, A.K.: Bilateral control of master slave manipulators with constant time delay. ISA Trans. 51(1), 74–80 (2012). https://doi.org/10.1016/j.isatra. 2011.07.005 5. Hasegawa, Y., Kitamura, T., Sakaino, S., Tsuji, T.: Bilateral control of elbow and shoulder joints using functional electrical stimulation between humans and robots. IEEE Access 8, 15792–15799 (2020). https://doi.org/10.1109/ACCESS.2020.2967466 6. Oztoprak, B., Baran, E.A., Sabanovic, A.: Bilateral control with continuously variable scaling (2018) 7. Uzunovic, T., Sabanovic, A., Yokoyama, M., Shimono, T.: Novel algorithm for position/force control of multi-DOF robotic systems, pp. 273–278 (November 2020). https://doi.org/10. 1109/amc44022.2020.9244337 8. Mizoguchi, T., et al.: Experimental study on bilateral control system under different wireless communication methods (2019) 9. Chopra, N., Spong, M.W., Lozano, R.: Synchronization of bilateral teleoperators with time delay. Automatica 44(8), 2142–2148 (2008). https://doi.org/10.1016/j.automatica.2007. 12.002 10. Chopra, N., Spong, M.W.: Output synchronization of nonlinear systems with time delay in communication (2006) 11. Lee, S.-J., Ahn, H.-S.: Synchronization of bilateral teleoperation systems with input saturation. IEEE (2010) 12. Chen, K., Zhang, H.: Design of synchronization tracking adaptive control for bilateral teleoperation system with time-varying delays. Sensors (Basel) 22(20), 7798 (2022). https://doi. org/10.3390/s22207798

Edge Detection Algorithm for Biological Slice Images Based on Empirical Wavelet Transform and Morphology Yafei Liu1 , Vincenzo Guercio2 , Piercarlo Cattani3 , and Francesco Villecco4(B) 1 College of Information and Electrical Engineering, China Agricultural University,

No. 17 Tsinghua East Road, Haidian District, Beijing 100083, China 2 Engineering School, Deim, University of Tuscia, Largo dell’Università, 01100 Viterbo, Italy 3 Department of Computer, Control and Management Engineering,

University of Rome “La Sapienza”, via Ariosto 25, 00185 Roma, Italy 4 Department of Industrial Engineering, University of Salerno, via Giovanni Paolo II 132,

84084 Fisciano, Italy [email protected]

Abstract. Edge detection is important in extracting image features, and microscopic slice images consist of closed-loop structures and complex internal textures, and extracting the corresponding features has an important role in biology, epidemiology, pathology and other fields. In this study, an edge detection algorithm for slice images based on empirical wavelet transform (EWT) and morphology is proposed. The empirical wavelet divides the Fourier spectrum of the signal into successive intervals, and then constructs a wavelet filter bank for filtering in the corresponding interval segments, and finally obtains the amplitude modulation frequency components by signal reconstruction. The empirical wavelet transform overcomes the modal aliasing problem caused by the scale discontinuity in the time domain, which reflects the characteristics of the empirical wavelet transform. The image components extracted by the empirical wavelet are then enhanced using a morphological algorithm, which can effectively extract the closed-loop edges of the sliced image as well as the significant textures inside. In this paper, the proposed method is tested on locust slice images as an example. The proposed algorithm can also be effectively applied to other biological cross-sectional images. Keywords: biological slice images · empirical wavelet transform · morphology · edge detection

1 Introduction Biological section images are generally made from biological tissues. As biological cross-sectional images, it is an indispensable tool in biological histology. Biological section images are widely used in biology, epidemiology, and pathology. It has important analytical value in the fields of quantification and measurement of biological tissue volume and pathology localization [1, 2]. Biological section images obtained under the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 524–533, 2023. https://doi.org/10.1007/978-3-031-31066-9_58

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microscope have a rich closed-loop structure, with organs and tissues showing smooth contours as well as regular textures, and play a significant role in the observation and analysis of the internal tissue structure of organisms [3, 4]. Some of the texture features of the slice image are shown in Fig. 1, such as linear textures, fractal structures, and curved contours [5, 6].

Fig. 1. Locust slice image, ➀ linear textures, ➁ fractal structures, ➂ curved contours.

Empirical Mode Decomposition (EMD) [7, 8] is a signal decomposition approach, which decomposes a signal into the sum of a series of Intrinsic Mode Functions (IMFs). Since EMD does not use any prescribed basis functions and only performs adaptive decomposition of the data signal according to a specific formula, it is basically applicable to arbitrary types of signals. Its characteristics are different from those of Fourier transform and wavelet transform for signal decomposition. Fourier and wavelet transforms are better at dealing with smooth and linear data, but in practice, most signals carry non-smooth and non-linear deviations. Therefore, when the Fourier transform performs linear superposition of trigonometric functions on non-smooth signals, the spurious harmonic components due to non-smooth and non-linear signals make the signal energy diffuse and thus cannot be accurately represented. The difference between EMD and Fourier and wavelet is that Fourier and wavelet are only represented in the frequency domain, while EMD results in a Hilbert spectrum of “energy-frequency-time” distribution, which is a decomposition of a complex vibrating system into the sum of a finite and simpler systems. In conclusion, EMD has obvious advantages in signal processing. In 2003, J.C. Nunes proposed the two-dimensional empirical mode decomposition [9–11] algorithm (BEMD) that can be used for image processing, which can decompose an image into multiple two-dimensional eigenmodal functions (BIMFs) as well as residual components in the form of BIMFs, where the BIMF contains the detailed information of the image and the residual component table contains the image edge information, BEMD is mainly used for multi-scale analysis of image signals. Thus BEMD is widely used in the field of image processing, including image fusion [12, 13], feature recognition, image noise reduction, etc. However, due to the lack of mathematical theory for empirical modal decomposition and its elusiveness due to its nonlinear characteristics, Gilles proposed the empirical wavelet transform (EWT) in 2013 [14, 15]. It does this by dividing the Fourier spectrum of the signal, then applying wavelet filtering to each Fourier spectrum segment, and finally

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reconstructing the signal to obtain a set of amplitude modulated frequency components. The construction of the empirical wavelet transform successfully solves the problem that the empirical modal decomposition algorithm is not supported by theoretical knowledge and has low computational complexity, and at the same time, it overcomes the problems of over- and under-envelopment in the EMD decomposition process. In 2014, Gilles proposed an image-based 2D empirical wavelet transform [16, 17] in combination with a multiscale geometric analysis method, which combined tensor wavelets, Littlewood-Paley wavelets, and super-wavelets to construct the corresponding 2D empirical wavelets, it decomposes the image in the spatial domain during the processing of the image and can effectively protect the image texture, and according to relevant studies, it is effective in image denoising as well as feature extraction. In 2017 Kirar and K. Agrawal used 2D empirical wavelets to extract entropic features and applied it to the field of glaucoma research [18–20]. This method states that EWT is superior to DWT in terms of preprocessing and regularization. And the method can also be used to extract features for other diseases such as diabetic retinopathy, ovarian cancer, and fatty liver. In the same year, Maheshwari et al. also proposed a method for glaucoma diagnosis based on empirical wavelet transform [21, 22]. The entropy features were extracted and then least squares SVM was used to perform the classification operation of normal and glaucoma images. After experimental validation, the classification accuracy of the method was as high as 98.33% and 96.67%. In 2020 a dynamic weighing algorithm for cows based on a support vector machine (SVM) and empirical wavelet transform (EWT) is proposed by Feng and Mei et al. [23, 24] for the weighing of classification and analysis of cows. This study is organized as follows: Sect. 2 briefly describes the basic flow of the algorithm in this paper; Sect. 3 describes the application of empirical wavelets in image representation and the details of the algorithm in this paper; Sect. 4 analyzes in detail the effect of this study on different biological slice images; finally, Sect. 5 draws the conclusion of this paper.

2 Methods The overall workflow of the edge detection algorithm proposed in this paper is shown in Fig. 2. The proposed method can be divided into the following steps: First, the empirical wavelet transform is applied to the original image, and the 2D empirical wavelet transform can be subdivided into the following steps: The pseudo-polar Fourier transform [25, 26] of the original image is performed first, then the average spectrum based on each angle is extracted. After that, boundary detection is performed, followed by mirror transformation, followed by 2D wavelet filter construction of the image and Fourier transform, and finally sub-band component extraction is performed. Finally, the corresponding sub-images are selected for morphological erosion operation for image enhancement, thus completing edge detection.

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Fig. 2. The framework of the proposed method

3 Materials and Detailed Scheme 3.1 Image Sub-band Components Extraction The proposed one-dimensional empirical wavelet EWT solves the problem that the EMD algorithm has no theoretical background support, and its purpose is the same as EMD, for extracting AM-FM components from the signal [27]. The empirical wavelet transform consists of two steps: detecting the Fourier supports and building the corresponding wavelets according to these supports; and filtering to obtain the different components. Fourier boundary sets are detected using the local maxima method [28, 29]. As shown in Fig. 3, the Fourier transform is performed on the signal f (t) and the signal characteristics of the interval [0, π ] are discussed. Suppose the Fourier interval [0, π ] is partitioned into N segments. We denote ω_n as the limit between the segments (ω_0 = 0, ω_n = π ) and each segment as _n = [ω_n − 1, ω_n]. The transition segment of width 2τ _n is defined with ω_n as the center [29, 30].

Fig. 3. Delineate the Fourier axis

Suppose there are M maxima in the Fourier spectrum of the signal f (t), and there are two cases of descending order: 1) M >= N : the number of selected maxima is more than the actual demand, so the first N − 1 maxima are kept and the other maxima are discarded; 2) M < N : the current number of maxima of the signal does not meet the requirement of decomposition, then the parameter N needs to be readjusted so that N = M.

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However, such approaches have limitations [31]. As shown in Fig. 4. Assuming N = 4, the Fourier boundary set can be calculated according to the formula ωn = (ω_n + ω_(n − 1))/2. In the case of wide support of Fig. 5(a), ω_n falls under the maximum support of the first mode; similarly, in the case of narrow support Fig. 5(b), multiple local maxima belong to the same mode, and this case cannot provide the best partition of the Fourier boundary [32]. This situation requires consideration of both global and local trends of the spectrum to avoid such problems.

Fig. 4. Principle of local maximum detection

(a)

(b)

Fig. 5. Anomalies in local maxima detection

Moreover, in image processing problems, the Fourier spectrum is not clearly distinguishable except for images with complex texture features, so it is necessary to use other criteria to detect Fourier boundaries. Four methods are proposed in the literature [16] to determine the global trend of the Fourier spectrum: 1) “praw”: approximation of the Fourier transform by an exponential function; 2) “poly”: approximation of the Fourier transform by an Nth order polynomial; 3) “morpho”: mathematical morphological method; 4) “tophat”: mathematical morphological method [33]. Combined with the current 2D empirical wavelet transform, this paper analyzes the processing results of different empirical wavelets for biological slice images. Take Fig. 6 for example, whose image sub-band components are shown in Figs. 7, 8, 9 and 10, respectively. According to Figs. 7, 8, 9 and 10, the corresponding wavelet characteristics can be seen from the corresponding BIMF components of the 2D empirical wavelet transform,

Edge Detection Algorithm for Biological Slice Images

Fig. 6. Original image

Fig. 7. Part of the BIMF of the 2D Littlewood-Paley EWT

Fig. 8. Part of the BIMF of the 2D tensor EWT

Fig. 9. Part of the BIMF of the 2D Empirical Ridgelet Transform

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Fig. 10. Part of the BIMF of the 2D Curvelet EWT

since Littlewood-Paley is supported in the Fourier domain by a ring, its BIMF components are spread from inside to outside in the form of a ring [34, 35]; Tensor wavelet [36] can only represent the information in the horizontal, vertical and diagonal directions of the image, and the expression direction is limited, so the BIMF component has a blank situation; Ridgelet is the image texture representation along the origin in the frequency domain, so the corresponding BIMF component is triangularly distributed from top to bottom; Curvelet refers to the representation using filter sets in the frequency domain, and the corresponding filter sets use “pole wedge”, so the BIMF component has Bar and block structure [37].

4 Experimental Results and Analysis In this paper, biological slice images are used for experimental verification. See Fig. 11.And the edge detection effect of other algorithms is shown in Fig. 12.

(a)

(b)

(c)

Fig. 11. Experimental result. (a) Original image; (b) Littlewood-Paley EWT processed Results. (c) Proposed method.

Figure 12 shows the results of classical edge detection algorithms for biological slice images. From Fig. 12, we can see that most edge detection algorithms can effectively extract the line edges of sliced images, but due to the complex texture of slice images, the running results are messy and unclear, so we need to explore other algorithms to

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(b)

(c)

(d)

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(e)

Fig. 12. Other algorithms. (a) Roberts; (b) Prewitt; (c) Sobel; (d) Canny; (e) Log.

extract important textures of images adaptively. From the Fig. 11(c), we can find that the Littlewood-Paley EWT can effectively extract the clear edges and textures of the slice images, but there are also some ripple-like artifacts around the image edges that need to be removed, and this part also needs to be improved.

5 Conclusion In this paper, a new edge detection algorithm is proposed. This algorithm uses twodimensional empirical wavelets for image component extraction, which have been newly proposed in recent years. First, the Littlewood-Paley wavelet is used to extract the edges of the slice images, and then the edge enhancement is performed using the morphological algorithm to complete the edge feature extraction. The experimental results show that the Littlewood-Paley wavelet is more effective in edge extraction compared with other empirical wavelets. In addition, the method in this paper also extends the application area of empirical wavelets to a certain extent, but the ripple artifacts of external contours in the edge detection results still need to be removed, so this experiment needs further in-depth study.

References 1. Wang, H., Liu, J., Liu, L., Zhao, M., Mei, S.: Coupling technology of OpenSURF and ShannonCosine wavelet interpolation for locust slice images inpainting. Comput. Electron. Agric. 198, 107110 (2022) 2. De Simone, M.C., Veneziano, S., Guida, D.: Design of a non-back-drivable screw jack mechanism for the hitch lifting arms of electric-powered tractors. Actuators 11(12), 358 (2022) 3. Mei, S., Liu, M., Kudreyko, A., Cattani, P., Baikov, D., Villecco, F.: Bendlet transform based adaptive denoising method for microsection images. Entropy 24(7), 869 (2022) 4. Pappalardo, C.M., La Regina, R., Guida, D.: Multibody modeling and nonlinear control of a pantograph scissor lift mechanism. J. Appl. Comput. Mech. 9(1), 129–167 (2023) 5. Liu, L., Liu, M., Meng, K., Yang, L., Zhao, M., Mei, S.: Camouflaged locust segmentation based on PraNet. Comput. Electron. Agric. 198, 107061 (2022) 6. De Simone, M.C., Celenta, G., Rivera, Z.B., Guida, D.: Mechanism design for a low-cost automatic breathing applications for developing countries. Lecture Notes in Networks and Systems (LNNS), vol. 472, pp. 345–352 (2022). https://doi.org/10.1007/978-3-031-052309_40

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25. Jin, X., et al.: Brain medical image fusion using L2-norm-based features and fuzzy-weighted measurements in 2-D Littlewood-Paley EWT domain. IEEE Trans. Instrum. Meas. 69(8), 5900–5913 (2019) 26. Guida, R., De Simone, M.C., Daši´c, P., Guida, D.: Modeling techniques for kinematic analysis of a six-axis robotic arm. IOP Conf. Ser. Mater. Sci. Eng. 568(1) (2019). Article no. 012115. https://doi.org/10.1088/1757-899X/568/1/012115 27. El-Dahshan, E.S.A., Bassiouni, M.M., Hagag, A., Chakrabortty, R.K., Loh, H., Acharya, U.R.: RESCOVIDTCNnet: a residual neural network-based framework for COVID-19 detection using TCN and EWT with chest X-ray images. Expert Syst. Appl. 204, 117410 (2022) 28. Manrique-Escobar, C.A., Pappalardo, C.M., Guida, D.: A multibody system approach for the systematic development of a closed-chain kinematic model for two-wheeled vehicles. Machines 9(11), 245 (2021) 29. Parashar, D., Agrawal, D.K.: Automatic classification of glaucoma stages using twodimensional tensor empirical wavelet transform. IEEE Signal Process. Lett. 28, 66–70 (2020) 30. Pappalardo, C.M., Lettieri, A., Guida, D.: Identification of a dynamical model of the latching mechanism of an aircraft hatch door using the numerical algorithms for subspace state-space system identification. IAENG Int. J. Appl. Math. 51(2), 346–359 (2021) 31. Polinati, S., Dhuli, R.: Multimodal medical image fusion using empirical wavelet decomposition and local energy maxima. Optik 205, 163947 (2020) 32. Rivera, Z.B., De Simone, M.C., Guida, D.: Unmanned ground vehicle modelling in Gazebo/ROS-based environments. Machines 7(2) (2019). Article no. 42. https://doi.org/10. 3390/machines7020042 33. Chaudhary, P.K., Pachori, R.B.: Automatic diagnosis of glaucoma using two-dimensional Fourier-Bessel series expansion based empirical wavelet transform. Biomed. Signal Process. Control 64, 102237 (2021) 34. Pappalardo, C.M., Manca, A., Guida, D.: A combined use of the multibody system approach and the finite element analysis for the structural redesign and the topology optimization of the latching component of an aircraft hatch door. IAENG Int. J. Appl. Math. 51(1), 175–191 (2021) 35. De Simone, M.C., Rivera, Z.B., Guida, D.: Obstacle avoidance system for unmanned ground vehicles by using ultrasonic sensors. Machines 6(2) (2018). Article no. 18. https://doi.org/10. 3390/machines6020018 36. Qin, W., Zhao, M., Mei, S., Cattani, P., Guercio, V., Villecco, F.: Realization of single image super-resolution reconstruction based on wavelet transform and coupled dictionary. In: International Conference on New Technologies, Development and Applications, pp. 449–456. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-05230-9_53 37. Manrique Escobar, C.A., Pappalardo, C.M., Guida, D.: A parametric study of a deep reinforcement learning control system applied to the swing-up problem of the cart-pole. Appl. Sci. 10(24), 9013 (2020)

Cybersecurity Challenges in Modern Supply Chain ˇ cak Gordana Zeba(B) and Mirjana Ciˇ Mechanical Engineering Faculty, University of Slavonski Brod, 35 000 Slavonski Brod, Croatia [email protected]

Abstract. Industry 4.0 has fundamentally changed the business landscape in the world. Companies now operate in a complex environment under the influence of emerging Industry 4.0 technologies and complex networks with partner companies in supply chains to deliver products and services to customers on time, with the required quality, and at the lowest possible cost. The digital transformation of business has increased productivity, efficiency, and competitiveness, but supply chains are becoming more vulnerable concerning security. Supply chains face security risks, such as theft of business data and intellectual property, disruption of operations, and financial losses that threaten the vital functions of supply chain participants. Given the growing interest in cybersecurity, this paper aims to identify trends in cybersecurity research for supply chains and directions for future research. For this reason, the authors conducted a bibliometric analysis of relevant articles on cybersecurity in the supply chain represented in the citation databases of the Web of Science platform. The research findings improve understanding of cybersecurity challenges in supply chain management and provide insights into areas of cybersecurity that require further research. Keywords: Industry 4.0 · cybersecurity · supply chain · blockchain · bibliometric analysis

1 Introduction Industry 4.0 is a new paradigm that denotes the beginning of the digital age, bringing significant changes to the manufacturing industry and supply chains. Industry 4.0 technologies such as the Internet of Things, the Internet of Services, the Industrial Internet of Things, Big Data, cloud computing, artificial intelligence, autonomous robots, additive/3D manufacturing, augmented reality, virtual reality, simulation/digital twins, and cybersecurity are penetrating the core of the manufacturing process [1, 2]. Under the influence of these technologies on which Industry 4.0 is based, new business models are emerging, the physical and virtual worlds are becoming highly interconnected, and vertical and horizontal integration in manufacturing is significantly improved. Vertical integration refers to the connection of different levels of the information system within the company, from the lowest level (production floor) to the highest level (e.g. ERP system), and horizontal integration refers to the connection between departments within © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 534–541, 2023. https://doi.org/10.1007/978-3-031-31066-9_59

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the company and also the connection with all participants in the supply chain [3]. All resources in manufacturing are interconnected, independent communication between machines is possible, and communication between machines and people, information exchange within the manufacturing system and with members of the supply chain is also in real time. Thus, the digital transformation of the economy not only leads to positive effects, but also has negative effects. The ubiquitous connectivity of resources in enterprise systems, the interconnectedness of enterprise systems, the close connection between the real and virtual worlds make enterprise systems vulnerable and susceptible to various challenges and negative effects [4]. Productivity, efficiency, and competitiveness have increased, but supply chains are becoming more vulnerable in terms of cybersecurity. Cyberattacks on supply chains are becoming more frequent [5]. The vulnerability of supply chains is particularly pronounced because they encompass a whole range of partner organizations, not just a single business system or company. There are serious negative impacts on the supply chain, such as theft of business data and intellectual property, business disruption, competitive espionage, and financial losses that threaten the vital functions of supply chain participants [6]. Therefore, under today’s operating conditions and supply chain structure, it is necessary to develop cybersecurity because the efficiency of the supply chain and the security of the global economy depend on it [7]. The goal of this paper is to provide a clearer picture of cybersecurity in supply chains that could assist practitioners and legislators in setting policies and actions, and to provide guidance to researchers for future research. Consistent with the research objectives, the research questions are: RQ1 – What is the trend in publishing research on cybersecurity in the context of supply chains?; RQ2 – Which countries are most productive?; RQ3 – Which research areas are most important for cybersecurity research in the context of supply chains?; RQ4 – Which topics are trending in cybersecurity research in the context of supply chains?; and RQ5 – What are the directions of future research?

2 Research Methodology The bibliometric method of performance analysis and science mapping using VOSviewer software (version 1.6.18) [8] were used to answer the research questions. Science mapping includes methods to visually represent the structure and dynamics of research knowledge (keyword co-occurrence analysis and bibliographic coupling were performed). Data were collected through the Web of Science platform using the Core Collection citation databases. The search query was defined for topic with the keywords (“supply chain*” OR “modern supply chain*” OR “smart supply chain*” OR “digital supply chain*” OR “cyber supply chain*” OR “cyber-supply chain*”) AND (“industry 4.0” OR “digital transformation” OR digitalization OR “internet of things” OR “blockchain” OR “big data” OR “artificial intelligence” OR “cloud computing”) AND (security OR cybersecurity OR cyber-security OR “cyber security”). Time frame covers the last 10 years. Only journal articles and early access articles are included in the analysis. Other document types (e.g., proceedings papers, review articles, book chapters, editorial material, and retracted publication) are excluded from the analysis. The search includes

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only English-language articles because the VOSviewer software supports only English. VOSviewer was selected because it is widely used in the academic community. A sample of 707 articles was obtained from the Web of Science Core Collection citation databases.

3 Bibliometric Analysis, Results and Discussion In this paper, a bibliometric analysis was performed, namely: performance analysis and scientific mapping, with the aim of identifying research trends and research fronts to discover current research topics and future research directions in the field of cybersecurity in the context of supply chains. 3.1 Performance Analysis The performance analysis was conducted with the goal of answering research questions RQ1, RQ2, and RQ3. Figure 1 shows the number of published research articles in the field of cybersecurity in the supply chain context over the last 10 years. Based on the number of publications, we can see a continuous increase in research interest since 2017. The number of citations started to increase slightly in 2018, and a particularly significant increase in citations can be observed from 2020 onwards.

Fig. 1. Number of publications and citations by years, period 2013–2022

Figure 2 shows the number of published research papers by country, listing those countries where more than 30 research articles have been published. The People’s Republic of China has published the most research articles in the area of cybersecurity in the supply chain context, accounting for 25.32% of the total number of published articles, followed by India with 21.08%, the United States of America with 15.86%, and the United Kingdom with 10.47%. Among European countries, only the United Kingdom and Italy (4.52%) are represented in the top 10 countries.

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Regarding the research areas in which publications on cybersecurity and supply chains appear, most articles were published in computer science (41.30% of the total number of articles), followed by engineering (38.47%). Other disciplines such as business economics, telecommunications, and science technology are represented by half as many articles.

Fig. 2. Number of articles per countries

3.2 Science Mapping A. Identifying research trends To identify the most important research trends, a keyword co-occurrence analysis was performed using the VOSviewer software. The analysis covers two periods, from 2013 to 2017 and from 2018 to 2022, as from 2018 to 2022 there is a significant increase in the number of published articles and the number of citations. For the period from 2013 to 2017, keywords with fewer than 2 occurrences were excluded (resulting in 28 words for analysis), and for the period from 2018 to 2022, keywords with fewer than 10 occurrences were excluded (resulting in 79 keywords for analysis). The size of the circles indicates the occurrence of words, and the thickness of the line indicates the link strength. Five clusters or five research themes were identified from 2013 to 2017, as shown in Fig. 3(a): Cluster 1 (red) - Information Systems and Risk Management; Cluster 2 (green) – Supply Chain Management; Cluster 3 (blue) - Internet of Things; Cluster 4 (yellow) – Cloud Computing; and Cluster 5 (purple) - Security. The link strength between the keywords, e.g., cybersecurity and supply chain management, is 0.70. Four clusters or four research themes can be identified for the period from 2018 to 2022, as shown in Fig. 3(b): Cluster 1 (red) – Supply Chain Management; Cluster 2 (green) – Internet of Things and security; Cluster 3 (blue) – Blockchain; and Cluster 4 (yellow) – Artificial Intelligence. The link strength between the keywords cybersecurity and supply chain management is 3.18. Figure 4 shows the overlay visualization network depicting the evolution of research topics over time (the analysis was performed for five-year periods, but only the last two

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years of each period are shown in the overlay network). It can be seen that new topics have emerged in the 2018–2022 period. It is also possible to observe the appearance of new terms in each time frame. The overlay map shows the occurrence of the keyword blockchain in the research topic Security at the end of the period 2013–2017 (Fig. 4(a)). The frequency of the keyword blockchain is 3, the linkage strength with the keyword e.g. supply chain management is 0.70 and with the keyword cybersecurity is 0.2. In the second time period (2018–2022), the keyword blockchain occurs 369 times and there are 78 linkages. A new research topic emerges: Blockchain (Fig. 4(b)). For example, the link strength between the keyword blockchain and the keyword cybersecurity is 5.60, so the linkage between these two terms has increased over time, which means that blockchain technology is increasingly important in the field of cybersecurity in the context of the supply chain. Between keywords blockchain and supply chain management link strength is 46.68. This is the highest link strength between two keywords in 2018–2022. The linkage keyword cybersecurity with the keyword supply chain management has also increased, and now the link strength is 3.18 compared to the previous period when it was 0.70.

Fig. 3. Network visualization of keyword co-occurrence – research themes in periods a) 2013– 2017 and b) 2018–2022

In 2018–2022, the most frequently used keywords were Industry 4.0, artificial intelligence, data privacy, and distributed ledger technology. Some less common words also appeared, including 5G, 6G, Industry 5.0, artificial intelligence of things, blockchain cloud of things, digital twin, machine learning, sustainability, healthcare, agricultural, food safety. These terms are highlighted in yellow and could represent potential future research topics. B. Identifying future research directions

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Fig. 4. Overlay visualization of keyword co-occurrence – evolution of research themes in a) 2013–2017 and b) 2018–2022

We can try to identify future research directions based on research fronts in the field of cybersecurity related to supply chain management. Research fronts are clusters of publications that represent the latest research in a particular research area. The bibliographic coupling method was used to identify research fronts because it provides the most accurate results [9]. The obtained result is shown in Fig. 5. The bibliographic coupling method links publications that cite the same group of cited publications. The analysis was performed for articles as the unit of analysis; for a five-year period (from 2018 to 2022), only articles with at least 20 citations were considered. The analysis was performed by total link strength. The results of the bibliographic coupling analysis for the most cited articles are three clusters that reveal research fronts that serve as guidelines for future research. By analyzing the titles, keywords, and abstracts of the most cited articles, the names of the research fronts were defined: (a) smart systems; (b) application of blockchain technology in supply chains; (c) supply chains based on the Internet of Things. The performance analysis revealed that interest in cybersecurity research related to the supply chain has increased in recent years (RQ1) and that the countries with the highest productivity in this sense are the People’s Republic of China, India, the United States of America, and the United Kingdom (RQ2). The research areas where cybersecurity and supply chains most often overlap are computer science and engineering (RQ3). Keyword co-occurrence was used to highlight current research trends such as supply chain management, Internet of Things and security, blockchain, and artificial intelligence (RQ4). Supply chain security is an important area, but in light of various challenges related to

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Fig. 5. Bibliographic coupling results: four research fronts

globalization, customer expectations, cost pressures, and various crises. Considering the importance of cybersecurity in the context of supply chain, there is a lack of research. The results of the documents bibliographic coupling highlight potential new research directions in cybersecurity and modern supply chains. Key directions include research on the potential of applying blockchain technology in supply chains, with a focus on the food and healthcare supply chain, and smart systems and supply chains based on the Internet of Things (RQ5). Research on the application of blockchain technology has the greatest potential. Most articles on this topic have been published recently, mostly on the opportunities and barriers to the application of blockchain technology. Keyword cooccurrence analysis shows that the leading keyword is blockchain and that the importance of blockchain technology for supply chain management is increasing.

4 Conclusion Modern supply chains are complex in structure and face significant challenges, with cyber threats playing an increasingly important role. With the use of advanced technologies and the transmission of large amounts of sensitive information in real time, supply chains are becoming increasingly vulnerable, and the consequences are becoming more severe. If the cybersecurity of a single member of the supply chain is compromised, the entire chain is disrupted, and the consequences are not only financial but can also cost lives. However, the issue of cybersecurity is currently underrepresented in the context of supply chains.

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This paper shows the dynamics of changing research topics on cybersecurity in supply chains over a ten-year period. Blockchain technology is a current research trend that has emerged over the last five years, but is also one of the directions for future research. The application of blockchain for cybersecurity is still in the early stage, and the research is only at the academic level so far, there is little research on practical application. The limitations of this study are that the sample included only journal articles and early access publications and only English-language articles, so some relevant articles may have been neglected. In any case, the results of this study provide insight into cybersecurity in the context of supply chains and may be useful to researchers in the field and policy makers.

References 1. Ghadge, A., et al.: The impact of Industry 4.0 implementation on supply chains. J. Manuf. Technol. Manage. 31(4), 669–686 (2020) 2. Rauch, E.: Industry 4.0+: the next level of intelligent and self-optimizing factories. In: Ivanov, V., Trojanowska, J., Pavlenko, I., Zajac, J., Perakovi´c, D. (eds.) DSMIE 2020. LNME, pp. 176– 186. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50794-7_18 3. Buer, S.: The digitalization of manufacturing: investigating the impact of production environment and company size. J. Manuf. Technol. Manage. 32(3), 621–645 (2021) 4. Yeboah-Ofori, A., et al.: Cyber threat predictive analytics for improving cyber supply chain security. IEEE Access 9, 94318–94337 (2021) 5. Boyson, S., et al.: Defending digital supply chains: Evidence from a decade-long research program. Technovation 118, 102380 (2022) 6. Khan, O., Estay, D.A.S.: Supply chain cyber-resilience: creating an Agenda for future research. Technol. Innov. Manag. Rev. 5(4), 6–12 (2015) 7. Barron, S., et al: Systems-based cyber security in the supply chain. In: Proceedings of the 2016 IEEE Systems and Information Engineering Design Symposium (SIEDS), pp. 20–25 (2016). https://doi.org/10.1109/SIEDS.2016.7489299 8. van Eck, N.J., Waltman, L.: Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84, 523–538 (2010) 9. Mazov, N.A., Gureev, V.N., Glinskikh, V.N.: The methodological basis of defining research trends and fronts. Sci. Tech. Inf. Process. 47(4), 221–231 (2020). https://doi.org/10.3103/S01 47688220040036

The Effect of Online Learning Setting on Motivation, Intended Effort, Emotional Engagement, and Language Learning Strategies Among Non-english Majors in Croatia – A Pilot Study Zrinka Fišer(B) University of Slavonski Brod EDUDpt, Trg Ivane Brlic Mazuranic 2, 35000 Slavonski Brod, Croatia [email protected]

Abstract. Online learning and teaching have become mandatory during the past several years due to the COVID-19 pandemic, and it has brought many changes to the educational process. The use of online learning platforms and applications possibly affected students’ motivation and engagement in different areas of studying. Following the findings of previous pre-pandemic research on students’ motivation and language learning strategies, a new pilot research was conducted among first- and second-year undergraduate students at the University of SlavonskiBrod in Croatia who are non-English majors with an aim to identify the effects of e-learning on their motivation and intended effort to learn English as a foreign language (EFL), as well as their emotional engagement and their choice of language learning strategies. The author used the L2 Motivational Self System (L2MSS), the Strategy Inventory for Language Learning (SILL) and the Emotional Engagement scales to identify the statistically significant relationships to students’ previous experiences in learning EFL. The research serves as a pilot study for the larger-scope investigation of those relationships among other students who are non-English majors, with variables of age and English for generic and specific purposes as possibly relevant factors. Keywords: e-learning · L2MSS · SILL · emotional engagement · EFL students

1 Introduction During COVID-19 pandemic, much has changed in education as we were forced to accept distance or online learning and teaching setting. Such setting requires the use of various programs and platforms (e.g., Microsoft Teams, Zoom, or Skype) with the focus often on the students’ self-regulatory learning which refers to how students metacognitively, motivationally, and behaviourally address their learning process. Much has been said and debated upon the effectiveness of online learning as opposed to the face-toface learning setting, but there is a growing need to understand how distance learning is affecting other variables controlling the learning process, and not just the outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 542–549, 2023. https://doi.org/10.1007/978-3-031-31066-9_60

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Motivation has been considered as one of the most influential factors in second and foreign language learning. Over past two decades, a shift from a socioeducational model of integrative motivation [8] to a more dynamic contextual model of motivation in second language (L2) learning led to considering the relationship between the individual and the context as complex and dynamic, meaning L2 motivation is considered in the context of a person’s self and identity [4, 23]. The L2MSS, developed by Dörnyei [4–6], has its ground point in the psychological theory of ‘possible selves’ and it is centred on learners’ vision of themselves in the future: Ideal self , Ought-to self , Instrumentality-promotion, Instrumentality-prevention and L2 learning experience. The central concept is the Ideal self which represents what the learners would ideally like to possess (referring to personal hopes or wishes). The second concept is the Ought-to self which represents what the learners believe they ought to possess (sense of duty, obligations, or responsibilities). The instrumentality concept is dual and consists of Instrumentality-promotion connected to the Ideal-self, and Instrumentality-prevention related to Ought-to self . The first one denotes motives focused on what promotes the learning (e.g., increasing the chances for better future employment), while the second one denotes motives focused on what prevents the learning (e.g., avoiding family and friends disapproving learner’s bad grades). The last component is the L2 learning experience related to how those two internal processes shape learners’ engagement in learning [23]. There is also a substantiated body of research and several hypotheses of language learning strategies (LLS). The model which will be referred to in this paper is the one designed by Rebecca Oxford who, in her earlier work, divided LLS into direct and indirect ones. Memory, cognitive and compensation strategies form a group of direct LLS which are used during tasks of mentally processing the target language. Metacognitive, affective, and social strategies belong to a group of indirect LLS which are not directly related to the language being learned [20]. In her later work, Oxford speaks of only of cognitive, metacognitive, social, and affective LLS but also of the fluctuation of LLS as a still unexplored language learning phenomena[3, 21]. One of the mostly used instrument in measuring the foreign and second language learning strategies is the Strategy Inventory of Language Learning (SILL), designed by Oxford [19], which consists of particles grouped in six categories according to six LLS. Motivation among Croatian learners of EFL has been the aim of several research during past three decades [9, 14, 16, 18], but the first to use the L2MSS instrument in Croatia was Martinovic [11] who validated it in a pilot study on 110 students of various non-English majors at University of Zadar. She later continued to explore motivation in relation to previous EFL learning experience, gender, and the field of study [12, 13, 15]. The causal relationship among LLS, motivation, and FL success among high school students in Croatia was investigated by Karlak and Velki [10] who concluded that although motivation and LLS (metacognitive strategies the most) are a significant predictor of the communicative language competence, the future research should investigate the significance of personal traits and the perceived importance of EFL for participants’ future occupation. Fiser and Zivic [7] investigated how graduate students of Early and Preschool Education in Croatia assessed their EFL competence during online language practicum and concluded that students had no significant preference for online versus face-to-face learning setting, most of them did not feel the anxiety during active participation in EFL

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practicum and they did not use all the features of Microsoft Teams (MT) application which may had been helpful in learning. In a follow-up study.

2 Methodology 2.1 Participants 27 first- and 17 s-year students of Teacher Education study at the University of SlavonskiBrod in Croatia participated in the pilot study. For better understanding of the effects of online learning experience, the author also included 26 fifth-year students of the same study programme at the same university because online learning setting affected them at different part of their secondary and tertiary level of education. The age of participants spanned from 18 to 30 years; the majority of them being 19 (27,1%), 20 (25,7%), or 23 (17,1%) years old. Sex was not a significant factor due to only one male participant. All the participants learned EFL for four years in their high schools. All 70 participants took EFL State Graduation Exam: 21,7% accomplished grade D, 42% grade C, 27,5% grade B, and 8,7% grade A. During high school, 5,9% of students obtained an average EFL grade D, 32,4% grade C, 42,6% grade B, and 19,1% grade A. 45,7% of participants had online EFL classes during their high school. 2.2 Instrument and Procedure Data was gathered by means of a questionnaire consisting of four parts and distributed to participants in November 2022 during their classes. The first part was designed by the author to gather participants’ socio-demographic data. The second part consisted of the L2MSS scale including 52 particles arranged in 6-point Likert rating subscales: the Ideal L2 Self, the Ought-to L2 self, the Intended Effort, the Instrumentality Promotion, and the Instrumentality Prevention subscale [22]. The third part represented the SILL scale with 50 particles, version 7.0, for learners of EFL and English as a second language [19]. It consists of six subscales followed by five-point Likert-type rating: Memory, Cognitive, Compensation, Metacognitive, and Social Strategies subscales. The fourth part of the questionnaire was the Emotional Engagement (EE) scale developed by Bernardi´c and her colleagues [1], consisting of five particles followed by five-point Likert-type scale.

3 Results and Discussion Correlations between the L2MSS, SILL and EE scales (Table 1) revealed that students who showed more positive attitudes towards motivational factors also showed more positive attitudes towards LLS (p < 0,01). Results on the EE scale did not correlate significantly with either scale. The Mann-Whitney Test did not reveal any significant difference on the results of all three scales and subscales among participants who had online EFL classes during high schools and those who had none, but further analysis showed some interesting results which may contribute to understanding if COVID-19 pandemic affected the relation of motivation and LLS in learning EFL. The Kruskal-Wallis Test revealed a significantly

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Table 1. Averageresults on L2MSS, SILL, and EE scales L2MSS scale N

SILL scale

EE scale

Valid

55

66

70

Missing

15

4

0

Mean

3,5904

3,1396

2,8943

Std. Deviation

,73427

,54560

,75121

Minimum

1,90

2,03

1,00

Maximum

4,91

4,58

4,60

positive correlation between the average EFL high school grades and: the L2MSS scale and its three subscales (Intended Effort, Ideal L2 self, Instrumentality-promotion), the SILL scale and its two subscales (Cognitive and Metacognitive), and the EE scale. As can be seen from the Table 2, students who achieved an average grade A in EFL classes during high school reported higher ranking of motivation (especially intended effort, L2 self and instrumentality promotion motives), and more frequent use of LLS (especially cognitive and metacognitive). However, students whose average EFL high school grade was C or D reported more emotional engagement to learn EFL at university. Findings are in concordance with findings of pre-pandemic period research of Martinovic [12] who discovered positive correlation of EFL high school grades with intended effort, ideal L2 self and instrumentality promotion motives; and negative correlation with ought-to and instrumentality prevention motives. In addition, only students with lower average EFL high school grade reported being more emotionally engaged in learning EFL at university. Table 2. Results on the L2MSS, SILL and EE scales and subscales in relation to average EFL high school grades The average EFL grade in N high school

M

Kruskal-Wallis Asymp. sig. H

Intended effort

2 3 4 5 Total

4 20 28 13 65

21,13 17,160 22,13 35,38 48,27

,001*

Ideal L2 self

2 3 4 5 Total

4 21 27 13 65

18,88 28,738 21,31 33,35 55,50

,000*

(continued)

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Z. Fišer Table 2. (continued) The average EFL grade in N high school

M

Kruskal-Wallis Asymp. sig. H

Instrumentality-promotion 2 3 4 5 Total

4 22 28 12 66

20,88 11,411 24,66 37,71 44,08

,010*

L2MSS

2 3 4 5 Total

4 18 24 7 53

18,25 9,731 20,17 30,83 36,43

,021*

Cognitive strategies

2 3 4 5 Total

4 22 29 13 68

26,63 10,507 25,80 34,05 52,65

,015*

Metacognitive strategies

2 3 4 5 Total

3 22 29 13 67

30,50 12,893 25,43 33,79 49,77

,005*

SILL

2 3 4 5 Total

3 22 26 13 64

26,50 8,863 27,02 31,23 45,69

,031*

Emotional engagement

2 3 4 5 Total

4 22 29 13 68

56,88 21,095 41,75 34,71 14,88

,000*

* p < 0,05.

The same test also revealed a significant correlation between the achieved EFL grade on the State Graduation Exam and: the L2MSS Ideal L2 self and the Instrumentalityprevention subscales, the SILL Affective strategies subscale, and the Emotional Engagement scale (Table 3). Students who achieved higher grades on the State Graduation Test reported higher ranking of Ideal L2 self and lower ranking of instrumentality-prevention motives, less frequent use of affective LL strategies and less emotional engagement in learning EFL than students who achieved lower grades. Again, these findings confirm the pre-pandemic ones as Martinovic [12] also concluded that higher EFL high school grades related to lower instrumentality prevention motives. As for LLS, Bozinovic and Peric [2] concluded that less competent students used more social, affective, and cognitive LLS strategies than more competent students; and MihaljevicDjigunovic [17] found

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Table 3. Results on scales and subscales in relation to state EFL Graduation Exam grades Grade on EFL State Graduation exam

N

M

Kruskal-Wallis H

Asymp. Sig

Ideal L2 self

2 3 4 5 Total

13 29 18 6 66

22,38 31,76 40,53 44,92

9,149

,027*

Instrumentality-prevention

2 3 4 5 Total

14 29 17 6 66

40,71 35,64 31,91 10,83

10,850

,013*

Affective

2 3 4 5 Total

15 28 19 6 68

46,33 35,23 27,61 23,33

9,731

,021*

Emotional engagement

2 3 4 5 Total

15 29 19 6 69

46,90 36,02 28,63 20,50

10,507

,015*

* p < 0,05.

only affective and social strategies did not correlate significantly with motivation to learn EFL.

4 Conclusion Motivation and LLS have proven to influence EFL learning during tertiary level education and findings of this research are in concordance with pre-pandemic research conducted in Croatia. The main contribution of this research, nonetheless, lies in identifying their correlation, taking into consideration the experience of online learning participants had during the COVID-19 pandemic. Findings generally confirmed that students who achieved higher EFL grade before enrolling to university programme were more motivated to become proficient users of that language by using more LLS and planned to use that language in ensuring a better future for themselves. Students who achieved lower EFL grades during their high school education showed more emotional engagement and affective approach to learning EFL at university. The findings of the outlined research should, nonetheless, be considered cautiously due to a relatively low number of participants. The same questionnaire will be administered to students of other non-English

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major groups at the same University which will ensure the opportunity to validate findings on a larger number of participants and shed some light on the possible effect of online EFL courses during tertiary level education (which was administered during previous academic year) on motivation, LLS, and emotional engagement. The emotional engagement should also be further investigated as the scale consists of a small number of particles and the analysis resulted with a relatively low alpha coefficient [1].

References 1. Bernardic, N.P., Putarek, V., Rovan, D., Petricevic, E., Vlahovic-Stetic, V.: Students’ engagement in learning physics: a subject specific approach. In: Buric, I. (ed.) Proceedings of the 20th Psychology Days in Zadar: Book of Selected, pp. 193–203. University of Zadar, Zadar, Croatia (2017) 2. Bozinovic, N., Peric, B.: Uporaba strategija ucenja u odnosu na znanje i razinu ucenja stranoga jezika. Metodicki Ogledi 19(2), 115–135 (2012) 3. Cohen, A.D., Wang, I.K.-H.: Fluctuation in the functions of language learner strategies. System 74, 169–172 (2018). https://doi.org/10.1016/j.system.2018.03.011 4. Dörnyei, Z.: The Psychology of the Language Learner: Individual Differences in Second Language Acquisition. Lawrence Erlbaum, Mahwah (2005) 5. Dörnyei, Z.: The Psychology of Second Language Acquisition. Oxford University Press, Oxford (2009) 6. Dörnyei, Z.: Towards a better understanding of the L2 learning experience, the Cinderella of the L2 motivational self system. Stud. Second Lang. Learn. Teach. 9(1), 19–30 (2019). https://doi.org/10.14746/ssllt.2019.9.1.2 7. Fiser, Z., Zivic, T.: Teaching English language online: an example of students’ competence self-assessment. In: International Scientific Conference ‘Zadarski filoloski dani 9’, Book of Abstracts, Zadar, Croatia, 12–13th November 2021, pp. 59–60 (2021) 8. Gardner, R.: Social Psychology and Second Language Learning: The Role of Attitudes and Motivation. Edward Arnold, London (1985) 9. Jakovac, M., Kamenov, Z.: Prior learning experience, motivation and learning strategies as successful factors in ESP learning. Strani Jezici 41, 7–32 (2012) 10. Karlak, M., Velki, T.: Motivation and learning strategies as predictors of foreign language communicative competence. Croatian J. Educ. 17(3), 635–658 (2015). https://doi.org/10. 15516/CJE.V17I3.1759 11. Martinovic, A.: Testing the L2MSS among Croatian university students: a pilot study. In: Mihaljevic Djigunovic, J., Medved Krajnovic, M. (eds.) UZRT 2012: Empirical Studies in English Applied Linguistics, pp. 183–192. FF Press, Zagreb (2013) 12. Martinovic, A.: The L2 motivational self-system: Differences among learners. Jezikoslovlje 19(1), 133–157 (2018) 13. Martinovic, A., Buric, I.: L2 motivation: the relationship between past attributions, the L2MSS, and intended effort. J. Foreign Lang. 13(1), 409–426 (2021). https://doi.org/10. 4312/vestnik.13.409-426 14. Martinovic, A., Poljakovic, I.: Attitudes toward ESP among university students. Fluminensia 22(2), 145–161 (2010) 15. Martinovic, A., Soric, I.: The L2 motivational self-system, L2 interest, and L2 anxiety: a study of motivation and gender differences in the Croatian context. ExELL 6(1), 37–56 (2018). https://doi.org/10.2478/exell-2019-0005 16. Mihaljevic Djigunovic, J.: Research on the affective domain of EFL learning: a study of motivation. Studia Romanica et Anglistica Zagrabiensa 42, 257–268 (1997)

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17. Mihaljevic Djigunovic, J.: Beyond language learning strategies: a look at the affective link. Sraz XLV–XLVI, 11–23 (2001) 18. Mihaljevic Djigunovic, J., Bagaric, V.: A comparative study of attitudes and motivation of Croatian learners of English and German. Studia Romanica et Anglica Zagrabiensa 52, 259– 281 (2007) 19. Oxford, R.: Strategy Inventory for Language Learning (SILL) Version 7.0 for Speakers of Other Languages Learning English, in Oxford, R. (1990). Language Learning Strategies: What Every Teachers Should Know. HarperCollins Publisher, New York (1989) 20. Oxford, R.: Language Learning Strategies: What Every Teacher Should Know. Newbury House, New York (1990) 21. Oxford, R.: Teaching and Learning Language Learning Strategies, 2nd edn. Routledge, New York and London (2017) 22. Taguchi, T., Magid, M., Papi, M.: The L2 motivationalself-system among Japanese, Chinese and Iranian learners of English: a comparative study. In: Dörnyei, Z., Ushioda, E. (eds.) Motivation, Language Identity and the L2 Self, pp. 66–97. Multilingual Matters, Bristol (2009) 23. Ushioda, E., Dörnyei, Z.: Motivation. In: Gass, S., Mackey, A. (eds.) The Routledge Handbook of Second Language Acquisition, pp. 396–409. Routledge, London and New York (2012)

Cyber Violence Form of Domestic Violence Petric˘a Tertereanu1 , Mihai Dragomir2 , and Aurel Mihail T, ît, u3(B) 1 Faculty of Industrial Engineering and Robotics, University Politehnica of Bucharest,

Splaiul Independen¸tei nr. 313, 6th District, Bucharest, Romania 2 Technical University of Cluj-Napoca, 28 Memorandului Street, Cluj-Napoca, Romania 3 Lucian Blaga University of Sibiu, 10 Victoriei Street, Sibiu, Romania

[email protected]

Abstract. The scientific paper aims to present an approach to cyber violence in relation to abuse in the real world. In recent times, more attention is being paid to cybercrime, including the problem of domestic abuse facilitated by digital technology and online communications, the increasing accessibility of the internet, the rapid spread of mobile information and the widespread use of social media. Modern technology offers domestic aggressors new ways to control, coerce and pursue their victims, even going beyond spatial limits. Aggressors can use antivictim technology to monitor, harass them, install spyware on victims’ phones or attack them on social media to humiliate them. Also, numerous other situations of cyber violence faced by victims in the pandemic have been reported, such as: the discovery of viruses in devices, the receipt of suspicious attachments, the compromise of mail or social media accounts, the receipt of fraudulent emails. Keywords: cyber violence · electronic devices · information technology · cybercrime · stalkerware

1 Introduction The objective of any human society is to maintain the state of normality and active intervention is required to restore balance when public order is disturbed by antisocial acts and behaviour. Criminality, although it is associated as a negative side of the individual, is considered an indicator of the normality of human communities, both its increase and its significant decrease above the constant values recorded in certain periods of time, can signal a social disorder [1]. In the last period of time, more attention is being paid to cybercrime, including the issue of domestic abuse facilitated by digital technology and online communications. In particular, the Internet has provided an environment through which exploitation, emotional and sexual abuse, threat and blackmail of partners can spread. Non-physical forms of domestic violence based on the use of technology are beginning to be sanctioned and examined by several countries around the world [2]. Technology facilitates abuse by providing abusers with new and more sophisticated ways to control, harass and track their victims. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 550–556, 2023. https://doi.org/10.1007/978-3-031-31066-9_61

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Electronic devices such as computers, smartphones and tracking devices allow abusers to cross geographic and spatial boundaries that would otherwise prevent them from monitoring their victims. Technologies allow aggressors to create a sense of omnipresence and degrade the victim’s sense of security, especially after separation. In the context of the Covid-19 pandemic, abuse and online aggression in the domestic environment have multiplied, with an increase in cases of cyber violence. Also, many other situations of cyber violence that victims have faced during the pandemic have been reported, such as: the discovery of viruses in devices, receiving suspicious attachments, compromising email or social media accounts, receiving efraudulent miles [3]. In order to prevent the commission of domestic cyber violence, there is a need for information, monitoring and sanctioning of abuses according to the legislation in force.

2 Cyber Violence – A Form of Domestic Violence Kaspersky’s annual report on stalkerware (the term stalkerware refers to software programs, applications and devices that allow someone to secretly spy on another person’s private life) highlights the link between online and offline violence by showing that 24% of people globally confirm that they have been tracked by technology, and of these a quarter confirm the experience of violence or abuse from their partner [4]. In a highly connected world, abusers can use technology against victims to spy, harass, intimidate or hurt them: they can install spyware on victims’ phones, attack them on social media to humiliate them, or provide them with electronic devices that reveal location and relationships with other people. The term cyber violence refers to the repeated aggressions committed by a person (aggressor) towards his partner or ex-partner with the help of digital technologies. These include a number of controlling and coercive components such as threatening phone calls, cyber stalking, location tracking through smartphones, social media harassment, posting intimate images of partners without their consent which is considered revenge porn. Spyware has become increasingly used to facilitate domestic violence. In the beginning, spy programs (spyware software) were intended to help parents monitor their children’s online activities, but now they are also used very often by abusers to monitor the activity of their current or former partner [2]. Cyber abuse is usually an extension of real-world abuse, but does not necessarily imply that the abusers are powerful, nor do they necessarily come face-to-face with the victims. The emotional damage that can occur is significant and endangers the lives of the victims, and research has shown that women represent the largest number of victims, especially. after separation from an aggressive partner, being considered a form of gender-based violence [5]. There is different forms in which cyber violence occurs, the following in the figure being some of them (Fig. 1):

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Fig. 1. Cyber violence

– Cyber stalking involves surveillance by e-mail, text messages or on the Internet, which happen repeatedly, undermines the victim’s sense of security, causes fear, panic; – Cyberbullying involves unsolicited or sexually explicit e-mails, text or online messages, threats of violence, insults; – Non-consensual pornography (cyber exploitation or revenge pornography), i.e. the online distribution of photos or video recordings with graphic sexual content, without the consent of the person in the images. The legislation in our country generally mentions domestic violence, and in the content of article 4 letter h of Law 217/2013 it mentions cyber violence, referring to the ways in which it can manifest as represented in the following figure (Fig. 2): In general, attackers use technology to check phone messages, obtain passwords from personal accounts, locate the victim in real time, monitor devices, blackmail them, track them online through fake accounts. Location surveillance provides detailed information about the person where he goes, who he spends time with, what friends he has. Location can be tracked by phone, Wi-Fi connections, websites visited, social platforms used, email providers. Smart computer devices, mobile phones, tablets constantly show where a person is, recording the location even when they are not connected to the Internet. Location information collected over time may suggest aspects of our private lives [6]. Attackers can also use spyware to attack smart phones or tablets. Thus, they can monitor the location of the user of such a device through GPS, they can read and even record private conversations, they have access inclusively to bank data.

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Fig. 2. Ways to manifest cyber violence

In recent years, spyware has proven to be a formidable adversary, being difficult to detect and remove even by professional anti-spyware solutions. They are installed automatically when the user surfs the Internet with a vulnerable browser, when they install a program that appears to be legitimate, or when they download music or movies from unreliable sources. But not all spyware is used with malicious intent. Some legitimate programs or social networks, such as Facebook, come bundled with spyware that users unknowingly accept. There are some signs that users can look for to detect such programs, such as: – – – –

if changes are observed to the browser or to a software that the user has not authorized; if the device used is heavy and crashes often; if problems are encountered with the use of disk drives; if suspicious icons appear suddenly in the browser toolbar.

To prevent infection with this type of dangerous software, each user must ensure that the operating system is up to date, that all available updates are downloaded and installed for both security software and anti-spyware solutions, as well as browser [7]. In Romanian legislation, the following crimes against the security and integrity of IT systems and data are provided for and punished [10] as represented in the following figure (Fig. 3):

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Fig. 3. Offences against the safety of information systems

The perception among victims is that law enforcement authorities approach online violence and harassment differently and less effectively than offline [8]. A very important amendment to Law no. 217/2003 on preventing and combating violence is that the police or the judge have the possibility of issuing a protection order (temporary or judicial) also in situations where the criminal activity concerned acts in the sphere of cyber violence [9]. But technology can also have a supporting role, to facilitate access to services, to provide data about rights and opportunities, about ways of action, support networks, for obtaining evidence and evidence. An example of this is the mobile application “Bright Sky Ro”, created to support victims of domestic violence, a free digital tool that provides victims with assistance and useful information, available in Romanian, Hungarian and English. The application can be downloaded on the mobile phone, either in plain sight or in hidden mode, and is intended to educate and inform. The app provides specialist information and support to victims of domestic violence, people who are in an abusive relationship or who are worried about someone who is. Between January and September 2022, 9,771 provisional protection orders were issued by the police, 20% more than in the first 9 months of 2021. Up to this point, 10,000 Romanians protect themselves from domestic violence and use the Bright Sky RO application. This application is the only free digital tool that supports victims of domestic violence in Romania. Another important element is that the application offers a private diary function where a user can save files in text, photo, video or audio format. They are then sent to an email address selected by the recipient. These files may be used as evidence in subsequent actions and proceedings [11]. High level of stress among couples increases the rate of domestic violence 3.5 times more than among those with low levels of stress The Covid 19 pandemic has had a significant impact on the incidence of domestic violence worldwide [12]. Although no one could have predicted that the world would see such an increase in cases, it is time for law enforcement authorities, governments and society at large to come together to devise strategies to limit the adverse effects of the Covid-19 pandemic on domestic violence [13].

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3 Conclusions The online environment is insufficiently regulated and does not address the associated risks seriously enough. Online harassment is not dealt with at an appropriate level, which does not keep pace with the extremely fast evolution of the field. It is extremely important that all users of smart devices and personal computers are informed about all possible computer threats that can affect them, and how to deal with them. Drastically reducing cybercrime by strengthening the expertise of those responsible for criminal investigation and prosecution. The responsibility of state institutions is to minimize the risk of victimization and to support those affected. In this sense, there is a need not necessarily for information, but especially for education, respectively awareness and internalization at the level of individuals of the norms, rules and good practices. Violence and abuse in the online environment can be responses to physical or mental challenges exercised spontaneously or over time by the life partner or by another person from the family or domestic environment. As in traditional domestic violence, the economic aspect is not negligible in cyberviolence, especially with regard to depriving the aggressor of access to certain banking services or financial resources (changing passwords, deleting messages, imposing bans, transferring sums of money etc.) [14]. Public-private partnerships are needed to invest in critical digital tools that streamline access to evidence-based yet pragmatic digitized services. Researchers have suggested that low income is linked to an increase in domestic violence. And where a family has no history of abuse, economic distress during a pandemic due to financial strain and lack of social support can fuel domestic violence.

References 1. European Economic and Social Committe. Strategia de securitate cibernetic˘a (2021). https:// op.europa.eu 2. Gas, it, oi, V.: Tehnologii informat, ionale, folosite ca metod˘a de violent, a˘ domestic (2021). https://anticoruptie.md/ro/blog/violeta-gasitoi/tehnologiile-informationale-folositeca-metoda-de-violenta-domestica 3. Gîtlan, C.: Violent, a˘ cibernetic˘a, form˘a a violent, ei domestic. Biroul Informare Documentare, nr. 3(170) (2022). ISSN 2065-9318 4. The State of Stalkerware Report (2021). https://stopstalkerware.org/2022/04/12/ 5. European Institute for gender equality EIGE. Violent, a cibernetic˘a împotriva femeilor s, i fetelor (2017). Search results – Publications Office of the EU (europa.eu) 6. Manualul pentru lucr˘atorii tineri, traineri s, i profesorii care lucreaz˘a cu tineretul cu privire la violent, a în mediul online (2019). www.cyberviolence.eu 7. Tuducea, H., Surd, C.: Amenint, a˘ ri informatice pe înt, elesul tuturor. Biroul Informare Documentare, nr. 4(171) (2022). ISSN 2065-9318 8. The Ripple Effect: Covid 19 and the Epidemic of Online Abuse (2020). https://www.endvio lenceagainstwomen.org.uk/campaign/online-abuse/

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9. Legea nr. 217/2003 privind prevenirea s, i combaterea violent, ei domestice republicat˘a (2003). https://legislatie.just.ro 10. Codul Penal al României, Legea 286/2009 (2009). https://www.politiaromana.ro/ro/comuni cate/fenomenul-violentei-domestice-ramane-de-actualitate-in-romania-bright-sky-ro-aplica tia-mobila-ce-sprijina-victimele-violentei-domestice-folosita-de-aproape-32-000-de-ori-dela-lansarea-in-romania 11. Emezue, C.: Digital or digitally delivered responses to domestic and intimate partner violence during Covid 19. JMIR Public Health Surveill. (2020). https://doi.org/10.2196/19831 12. Sharma, A., Borah, S.B.: Covid-19 and domestic violence: an indirect path to social and economic crisis. J. Fam. Violence 37, 1–7 (2020). https://doi.org/10.1007/s10896-020-001 88-8 13. Polit, ia Român˘a - Fenomenul violent, ei domestice r˘amâne de actualitate în România. Bright Sky RO – aplicat, ia mobil˘a ce sprijin˘a victimele violent, ei domestice, folosit˘a de aproape 32.000 de ori de la lansarea în România (politiaromana.ro) 14. Women as victims of partener violence, Justice for victims of violent crime (2019). Women as victims of partner violence – Justice for victims of violent crime – Part IV (europa.eu)

Anomaly Detection and Classification in Agricultural Produce Using Image Processing and CNN Assisted by a Robotic Arm Varsha Viswanathan(B) , Supraajha Murali, and Venkatakrishnan Veeraraghavan Department of Computer Science and Engineering, Easwari Engineering College, Chennai, India [email protected]

Abstract. The Global Hunger Crisis has long been one of the most pressing problems of the modern world. Surveys have shown that globally, around 14 percent of food produced is wasted between harvest and retail. This project aims to develop a mechanism that uses image processing and deep learning to classify agricultural produce and perform anomaly detection. The system performs two kinds of evaluations; a mass-evaluation and a singular evaluation. The mass evaluation of produce is done by angling a camera at an angle theta (θ), that is pre calculated through an optimal angle calculation algorithm. In addition, the system provides controls to a supervisor to specifically evaluate individual items based on the factor of “intuitive inquiry”. In this process, a robotic arm picks the target item and takes it to the camera physically for end-to-end coverage. The data obtained from both mass analysis and individual analysis is fed into a program containing metrics for evaluation. Based on the degree of adherence/divergence from standards, the system also recommends a further progression by classifying the item into sets—i.e., if the item is anomaly-free, if it is fully defective and must be discarded, if it can be corrected through further processing, or if it has been under processed. With each iteration of item evaluation, the system intelligently learns from its decisions for improved accuracy and speed. Keywords: Computer Vision · Image Processing · Convolutional Neural Networks · Deep Learning

1 Introduction The recent trends have seen many innovative methods to curb the rise of the Global Food and Hunger crisis, including an increased pressure on corporate, government and larger manufacturers/organizations to take accountability and combat this issue. The advent of technology has greatly contributed to countering this issue, and the leveraging of Artificial intelligence (AI), Machine learning (ML) and CNN has proved valuable in bringing about methodologies that responsibly curate the amount of food products manufactured and consumed, and bring about a reduction in the wastage of food and food products [1]. This project aims to take a similar approach to the agriculture industry by using image processing and CNN to directly identify and weed out waste agricultural © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 557–561, 2023. https://doi.org/10.1007/978-3-031-31066-9_62

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produce [2] directly at the manufacturing and sorting stage. This helps to remove the risk of contaminating large quantities of produce, reducing the amount of waste by providing a prescription mechanism, and hand-over of food products that are safe for consumption.

2 Existing System The study of base paper, past papers and present systems revealed that the existing models for waste identification and classification are all semi-automated. Some systems include the use of CNN and image processing in their mechanism, but still rely on manual transfer of items to and from the observational area. Other systems make use of a robotic arm, such as Baxter robot, however the classification is still done manually [3]. The base paper has used a CNN model of 15 layers, as opposed to the existing systems which have 20 plus layers [4]. They use this model to classify plastic and other chemical waste in industrial items.

3 Proposed System This project aims to mechanize waste detection and segregation through the technological concepts of Robotics, Convolutional Neural Networks (CNN) and Deep Learning [5]. It has a working methodology that commences from the procuring of item-based data, and concludes with detection and classification. We implement an independent algorithm that calculates an “optimal angle” theta (θ), which is the angle that provides the most accurate captures for image processing [6]. The items for evaluation are placed on a conveyor belt successively, and are sent forward towards the camera. The camera is angled towards the items at the optimal angle θ. The input data obtained live via a camera that scans the row of items that are placed consecutively on the conveyor belt. The data is then fed into the CNN-based system that identifies whether it is to be classified as waste, and the percentage of adherence towards a perfect sample is obtained. This percentage is fed into a program, which, based on a given metric, will classify the waste further into a course of progression. There is also the presence of an external supervisor, who monitors this continuous flow of testing of items. In case the supervisor is suspectful that a certain item has not been identified/positioned correctly by the system the supervisor is given the controls to stop the conveyor belt and enter the row number of the suspected item. There is a robotic arm (such as a Baxter robot) [7] that picks up that particular item, takes it in front of the camera, rotates it for complete detection and then recommends the progression. The conveyor belt is then resumed and the items are evaluated. The sample is finally returned to the next section via a robotic arm. This project also recursively teaches itself through learning from each iteration.

4 Methodology The project objectives are to build a system to detect and segregate waste from other materials. The components of the system are a robotic arm, camera, central CNN-based system and a gripper capable of picking up objects. The methodology for this project

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was divided into three parts: optimal angle calculation algorithm, image processing and deep learning. The algorithm that calculates the optimal angle θ is made by analyzing various other image processing implementations by identifying a commonly used angle for capture. This is the angle, θ that is used to position the camera for capture of the images. The base paper has adopted a simplified model where there could be only one waste within the camera lens. The project in proposal improves this by arranging the items successively in a conveyor belt that are mass-assessed by the camera. Theta Calculator—Algorithm This algorithm calculates an “optimal angle” theta (θ), which is the angle that provides the most accurate captures for image processing. The items for evaluation are placed on a conveyor belt successively, and are sent forward towards the camera. The camera is angled towards the items at the optimal angle θ.

5 Figures See Figs. 1 and 2.

Fig. 1. Architecture of the system

Fig. 2. Sequence diagram

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6 Comparison Table S. No. Title

Author(s)

Year

Advantage

1

Waste Classification System Using Image Processing and Convolutional Neural Networks (Base paper)

Janusz Bobulski and Mariusz Kubanek

2019 Achieving high efficiency for images with a resolution more than twice lower than the available 23-layer network

2

Real-Time Andres Milioto, Semantic Philipp Lottes, Segmentation of Cyrill Stachniss Crop and Weed for Precision Agriculture Robots Leveraging Background Knowledge in CNNs [8]

2018 System Training dataset generalizes well, very small can operate at around 20 Hz, and is suitable for online operation in the fields

3

A Color and Eftekhar Hossain Texture Based and Mohammad Approach for the Anisur Rahaman Detection and Classification of Plant Leaf Disease Using KNN Classifier [9]

2019 Classified diseases like alternaria alternata, anthracnose, bacterial blight, leaf spot, and canker of various plant species

4

Object Detection and Recognition for a Pick and Place Robot

5

Image Monika Jhuria, processing for Ashwani Kumar, smart farming: Rushikesh Borse Detection of disease and fruit grading [9]

Rahul Kumar, 2014 Developed a robust Sanjesh Kumar, method of image Sunil Lal, Praneel classification using Chand image processing

2013 Vectors morphology gives 90% correct result and it is more than other two feature vectors

Disadvantage Does not work in real-time environment

Automation specific to a very small group of dataset

The feature extraction algorithm was tested and found to be 83.6443% accurate Back propagation concept is used for weight adjustment of training database. This is time consuming

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7 Conclusion The current layout and plan of this project involves the identification, classification and segregation of waste items in agricultural produce via CNN and image processing. This project includes optimality functions that improve the correctness by identifying optimal angles, providing human intervention for checking etc. It also solves the initial problems of excessive waste by producing classification mechanisms that don’t simply discard all items but prescribe for maximum reuse. Further implementations and future scope include increase in time-efficiency and allowing for unordered mass scanning of items rather than successively ordered.

References 1. Bal, F., Kayaalp, F.: Review of machine learning and deep learning models in agriculture. Int. Adv. Res. Eng. J. 5(2), 309–323 (2021). https://doi.org/10.35860/iarej.848458 2. Renukadevi, M., Sulaikha, C.M.: A survey on image processing methodologies for crop and weed detection. Ann. RSCB 25(6), 10251–10260 (2021) 3. Kumar, R., Lal, S., Kumar, S., Chand, P.: Object detection and recognition for a pick and place robot. In: Asia-Pacific World Congress on Computer Science and Engineering, pp. 1–7. IEEE (2014) 4. Bobulski, J., Kubanek, M.: Waste classification system using image processing and convolutional neural networks. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2019. LNCS, vol. 11507, pp. 350–361. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-20518-8_30 5. Watson, J., Hughes, J., Iida, F.: Real-world, real-time robotic grasping with convolutional neural networks. In: Annual Conference Towards Autonomous Robotic Systems, pp. 617–626. Springer, Cham (2017).https://doi.org/10.1007/978-3-319-64107-2_50 6. Olague, G., Mohr, R.: Optimal camera placement for accurate reconstruction. Pattern Recogn. 35(4), 927–944 (2002) 7. Ju, Z., Yang, C., Ma, H.: Kinematics modeling and experimental verification of baxter robot. In: Proceedings of the 33rd Chinese Control Conference, pp. 8518–8523. IEEE (2014) 8. Milioto, A., Lottes, P., Stachniss, C.: Real-time semantic segmentation of crop and weed for precision agriculture robots leveraging background knowledge in CNNs. In: Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 2229–2235. IEEE (2018) 9. Hossain, E., Hossain, M.F., Rahaman, M.A.: A color and texture based approach for the detection and classification of plant leaf disease using KNN classifier. In: Proceedings of the 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE), pp. 1–6. IEEE (2019)

On the Optimal Design of a Scale-Free Supply Network Piercarlo Cattani1 and Francesco Villecco2(B) 1 Department of Computer, Control and Management Engineering, University of Rome “La Sapienza”, via Ariosto 25, 00185 Roma, Italy 2 Department of Industrial Engineering, University of Salerno, via Giovanni Paolo II 132, 84084 Fisciano, Italy [email protected]

Abstract. In this paper we define a scale-free network based both on the preferential attachement parameter, of the Barabasi-Albert model, and on the new parameter of carrying capacity under a logistic growth. The main advantage is that by using this new parameter the network will grow as a set of communites each one with a limited number of nodes, each community with only one hub and a very little number of connections between communities, thus minimizing the number of links. With this model, which fulfills the 80–20 Pareto rule, we will also get an optimal designed network characterized by the limited cost of management. Keywords: Supply chain management · scale-free network · preferential attachement · Barabasi and Albert model

1 Introduction One of the main tasks in Engineering management is to design a supply chain network with minimal costs, from all perspectives (physical, structural, enviromental, economical, sustainable….). The optimal network of nodes/activities (social, business, firms,…) should be characterized by the minimal number of links with high efficiency exchange of information/communication between nodes. The concept of high efficiency in a network is to find the minimalto build up a network, in particular by connecting the highest number of members (nodes), with the minimum number of links, thus avoiding redudancies, that is an overloading number of useless links. In this paper we propose a model for an efficient optimal network where the nodes are connected with the minimum number of links. This network is organized through a system of communities each one having the minimum number of hubs and links, thus increasing the efficiency and sustainability of the network. The sustainability is intended as to have the minimum number of hubs and links by keeping an high efficiency (communication/exchanges) of the network.A network, substaintially is a graph where each nodeis a network member linked to other members with edges representing some suitable relationship among them. Although there exists several kind of networks, we will focus only on the so-called scale free networks. They are structured in a such way that the nodes degree (see below) distribution © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 562–570, 2023. https://doi.org/10.1007/978-3-031-31066-9_63

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is described by a power law. Unfortunately, there is still an open debate and several concerns aboutthe power law distribution and the corresponding networks, in particular it has been argued that there not exists many concrete example in nature or society of these scale-free networks. Indeed the scale free property has been shown so far only on a few examples such as social networks, internet sites, airline nets, Hirsch index citations, and computer networks but the main interest for these networks is due to the fact that they agree with the basic empirical Pareto’s rule of 80–20 that can be seen in any kind of experimental data set. There are many evidences of the Pareto rule, in nature, society, and science. It can be shortly described by the fact that the majority of nodes (80%) in a network are quite poor of properties while the minority (20%) which is owing the highest facilities is represented by a very few set of nodes. In this paper we propose a model where a very few set of nodes (hubs) have the highest number of connections, moreover the network is organized as a union of communities. The network is constructed in a such way to reduce the number of connections among nodes and from one community to another, thus reducing the connections, and at the same time by increasing the comunication speed among nodes and being a more sustainable network for the environment because the network will be more efficient. Let us think at the traffic road system, the lowest is the number of roads efficiently connecting the nodes the best would be for the environment and for the costs. In particular in order to construct the sustainable communities we will use the concept of carrying capacity and logistic growth of the degree number, in order to fix an upper limit to the growth of each community [1–3]. We will compare our model with the so-called Barabasi Albert model [4–6]which is characterized by the preferential attachement and by the infinite growing of the nodes degree which however is unrealistic as well as unsustainable for the costs and enviromental impact. In our model, which is still scale-free, the highest degree of nodes will grow up to a finite value, called carrying capacity, and consequenly also the number of links will be limited as well.

2 Scale-Free Networks A scale-free network is a set of nodes N whose degrees k are determined by a power law distribution at least for N going to infinity. That is, the number N of nodes in the network having k connections are inversely proportional to k so that N (k) ∝ k −γ where usually it is 2 0, i∈Im

i.e., the latency is the same across all links with nonzero flow and smaller than the zero flow latency of the rest of the links. The average delay of a network Lm = (1 (·), . . . , m (·)) at flow x = (x1 , . . . , xm ) ∈ Sm−1 is given by the sum  m i=1 xi i (xi ). A system optimum of a network Lm = (1 (·), . . . , m (·)) is a flow x = (x1 , . . . , xm ) ∈ Sm−1 that minimizes the average delay. Further, we assume that each link k in the network is owned by a service provider who sets a link price of qk . Let q = (q1 , . . . , qm ) denote a price vector of the network. In order to choose the amount of flow and the routing pattern optimally, we define an effective cost of using link k to be the sum of the latency k (xk ) and the link price qk when the total flow on the link k is xk , i.e., k (xk )+qk .  Let L(x) := L(x) + q denote an effective cost vector at the flow vector x = (x1 , . . . , xm ). We also assume that a reservation utility (link capacity) is R and a flow is not being sent when the effective cost of the link exceeds the reservation utility R. Let R = (R, . . . , R) denote a reservation utility vector (see Fig. 1). It should be mentioned [1,8] that for any q ∈ Rm + with q ≤ R there always exists (q) (q) (q) (q) a unique Wardrop equilibrium x = (x1 ,  x2 , . . . , xm ) ∈ Rm + with either of m the following properties (we denote x1 := k=1 |xk |):     (q) (q) i (xi ) + qi = min k (xk ) + qk < R, ∀ i ∈ supp x(q) , x(q) 1 = 1, k∈Im     (q) (q) i (xi ) + qi = min k (xk ) + qk = R, ∀ i ∈ supp x(q) , x(q) 1 ≤ 1. k∈Im

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  (we) (we) Definition 1. A flow vector x(we) = x1 , · · · , xm is a Wardrop equilibrium if it is a solution to the following optimization problem m

  (we) (we) R − k (xk ) − qk yk . ∈ Argmax x y≥0 y1 ≤1

k=1

  (so) (so) is called a system optiDefinition 2. A flow vector x(so) = x1 , · · · , xm mum if it is a solution to the following optimization problem m

(so) x ∈ Argmax (R − k (yk ) − qk ) yk . y≥0 y1 ≤1

k=1

For the definitions of a Wardrop equilibrium and the system optimum see also [1,11,12]. In the next definition we introduce the notions of a Wardrop optimal flow and a Wardrop optimal network.   (wof ) (wof ) is called a Definition 3. A flow vector x(wof ) = x1 , · · · , xm Wardrop optimal flow if it is simultaneously a Wardrop equilibrium and a system optimum of the network. A network that has a Wardrop optimal flow is called a Wardrop optimal network. 1 (x1 ) + q1 , R 2 (x2 ) + q2 , R total one unit of flow

m (xm ) + qm , R

Fig. 1. Model of a parallel network with m links

 m ), a flow x = (x1 , . . . , xm ) ∈ Sm−1 is called a Given a network Lm (L Wardrop optimal flow if it is Wardrop equilibrium and system optimum of Lm  m ). A network that has a Wardrop optimal flow is referred to as a Wardrop (L optimal network. We denote by WOF the class of all Wardrop optimal networks.

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Before we proceed further with our results, we first provide some main definitions (see [4,5,13]) and statements to be used in the rest of this paper.  Definition 4. A sequence x(n) n∈N with x(1) := x is called an orbit of the point x ∈ Sm−1 .

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m Let EεLm (y, x) := ε(y, Lm (x)) = ε i=1 yi li (xi ) and EεLm (x, x) m ε(x, Lm (x)) = ε i=1 xi li (xi ) for any x, y ∈ Sm−1 and ε ∈ (−1, 0).

:=

Definition 5. A flow x is called a Nash equilibrium if one has EεLn (x, x) ≥ EεLn (y, x) for any y ∈ Sm−1 . A flow x is called a strictly Nash equilibrium if one has EεLn (x, x) > EεLn (y, x) for any y ∈ Sm−1 with y = x. In order to study the stability of fixed points of the replicator equation, we employ a Lyapunov function. Definition 6. A continuous function ϕ : Sm−1 → R is called a Lyapunov function if the number sequence {ϕ(x), ϕ(R(x)), ϕ(R(2) (x)), . . . , ϕ(R(n) (x)), . . .} is a bounded monotone sequence for any initial point x ∈ Sm−1 . Definition 7. A fixed point y ∈ Sm−1 is called stable if for every neighborhood U (y) ⊂ Sm−1 of y there exists a neighborhood V (y) ⊂ Sm−1 of y such that an orbit {x, R(x), · · · , R(n) (x), · · · } of any initial point x ∈ V (y) remains inside of the neighborhood U (y). A fixed point y ∈ Sm−1 is called attracting if there exists a neighborhood V (y) ⊂ Sm−1 of y such that for any initial point x ∈ V (y) its orbit {x, R(x), · · · , R(n) (x), · · · } converges to y. A fixed point y ∈ Sm−1 is called asymptotically stable if it is both stable and attracting. Proposition 1. Every network (latency vector function) Lm · · · , m (·)) has a unique Wardrop equilibrium in the simplex Sm−1 .

=

(1 (·),

The following result provides some sufficient condition which ensures an existence of Wardrop equilibrium inside the simplex Sm−1 = {x ∈ Rm : x1 = 1, x ≥ 0} and in fact describes the capacity of Wardrop’s equilibrium. be the inverse function of the latency function k for Proposition 2. Let −1 k all k ∈ Im and q < R. Then the following statements are true: m (we) 1 < 1; (i) If k=1 −1 k (R − qk ) < 1 then x m −1 (ii) If k=1 k (R − qk ) ≥ 1 then x(we) 1 = 1. We consider a Wardrop equilibrium x(we) (a Wardrop optimal flow x(wof ) ) with full capacity 1, i.e., x(we) 1 = 1 (x(wof ) 1 = 1). Let Sm−1 := {x ∈ Rm + : x1 = 1} be the simplex. We now provide a characterization of a Wardrop optimal flow x(wof ) with full capacity 1, i.e., x(wof ) ∈ Sm−1 .  Let L(x) = (˜1 (x1 ), · · · , ˜m (xm )) be an effective cost vector at the flow x = (x1 , . . . , xm ), where ˜k (xk ) = k (xk ) + qk is an effective cost of the link k ∈ Im .  m = (˜1 (·), . . . , ˜m (·)), Theorem 1. Given a differentiable and convex network L m−1 is a Wardrop optimal flow if and only if a flow vector x = (x1 , . . . , xm ) ∈ S the following conditions are satisfied: (i) ˜i (xi ) = ˜j (xj ) for all i, j ∈ Im with xi > 0 and xj > 0; (ii) xi ˜i (xi ) = xj ˜j (xj ) for all i, j ∈ Im with xi > 0 and xj > 0;

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(iii) ˜i (0) ≥ ˜j (xj ) + xj ˜j (xj ) for all i, j ∈ Im with xi = 0 and xj > 0. Given any flow vector p = (p1 , . . . , pm ) ∈ Sm−1 with p > 0, let px :=   x1 xm , . . . , for any x ∈ Sm−1 . Let WOF(p) be a set of all effective cost p1 pm  vectors L(x) = (˜1 (x1 ), . . . , ˜m (xm )), whose Wardrop optimal flow is p. Then it can be shown that the set WOF(p) is a convex cone.

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Dynamic Approach to Wardrop Optimal Flows

Let x, L( px ) =

m

k=1 xk 



xk pk

 be the average effective cost of the network at

the flow vector x ∈ S . We assume that the network users may dynamically change the distribution of the total one unit flow over alternatively parallel links. (n) (n) Namely, if x(n) = (x1 , . . . , xm ) ∈ Sm−1 is the flow distribution of the users m−1

at the step n then the relative growth rate

(n+1)

xk

(n)

−xk

(n) xk

of the flow on the link

k at the step (n 1)

+  is negatively proportional to the difference between the (n) x effective cost  pkk of the link k at the step n and the average effective cost

(n)    (n)   x (n) m = k=1 xk  pkk x(n) , L xp of the network as a whole at the step n. We now propose the dynamic model of optimal flow distribution by considering the discrete-time replicator equation R : Sm−1 → Sm−1 on Wardrop optimal networks defined as follows   

 m xi xk xi  (1) − , ∀ k ∈ Im (R(x))k = xk 1 + ε  pk pi i=1 where  : [0, p¯] → [0, +∞) is a continuously differentiable and strictly increasing function, p = (p1 , . . . , pm ) ∈ intSm−1 is an interior flow, p¯ := min1 pi , ε ∈ (−1, 0). i∈Im

Some particular cases of Eq. (1) were studied in the literature [14,15]. d We define the constant μ := max dz (z(z)) . Let ei be the vertex of the z∈[0,p] ¯  simplex Sm−1 , i ∈ Im , and pα := sα1(p) i∈α pi ei for all α ⊂ Im , where sα (p) =  m−1 . i∈α pi and p = (p1 , . . . , pm ) ∈ intS Recall (see [5,13]) that a flow x ∈ Sm−1 is called a Nash equilibrium of the replicator equation given by (1) if x, εL( px ) ≥ y, εL( px ) for all y ∈ Sm−1 . Denote Fix(R) = {x ∈ Sm−1 : R(x) = x} a set of fixed points of the replicator Eq. (1). We study the dynamics of the Eq. (1) by means of a Lyapunov function. Let S|α|−1 := conv{ei }i∈α for α ⊂ Im , where conv(A) is the convex hull of A, and intS|α|−1 := {x ∈ S|α|−1 : supp(x) = α} be an interior of the face S|α|−1 . Proposition 3. Let ε ∈ (− μ1 , 0) ∩ (−1, 0). Then the following statements hold true:

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(i) Mp:k (x) := max{ xpii } − xpkk for all k ∈ Im is a decreasing Lyapunov function i∈Im

for R : intSm−1 → intSm−1 ; (ii) Mpα :k (x) := max{ xpii } − xpkk for all k ∈ α ⊂ Im is a decreasing Lyapunov i∈α

function for R : intS|α|−1 → intS|α|−1 . The asymptotic stability and the dynamics of the replicator Eq. (1) can be described all over the simplex as in the following proposition. Proposition 4. Let ε ∈ (− μ1 , 0) ∩ (−1, 0). Then an orbit of the replicator equation R : Sm−1 → Sm−1 starting from any initial point x ∈ Sm−1 converges to the fixed point psupp(x) in the interior of the face S|supp(x)|−1 . Proposition 5. Let x, y ∈ Sm−1 be two distinct elements of the simplex Sm−1 m such that y > 0. Let yx := ( xy11 , · · · , xym ), y¯ := min yk > 0 and x − y1 := k∈Im  k∈Im |xk − yk |. Then the following statements hold true: (i) min xykk < 1 < max xykk ; k∈I k∈Im  m  xk xk (ii) y¯ max yk − min yk ≤ x − y1 ≤ m max k∈Im

k∈Im

k∈Im

 xk yk

− min

k∈Im

xk yk

.

The main result of this paper presented in Theorem A, which describes the dynamics of the discrete-time replicator Eq. (1) for sufficiently small ε ∈ (−1, 0), is then proved by using the Propositions 3, 4 and 5. Theorem A. Let ε ∈ (− μ1 , 0)∩(−1, 0). Then the following statements hold true:  {pα }; (i) One has Fix(R) = α⊂Im

(ii) The unique Wardrop optimal flow p is the only Nash equilibrium; (iii) The unique Wardrop optimal flow p is the only stable fixed point; (iv) Any interior orbit converges to the unique Wardrop optimal flow p.

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Multi-Agent Intelligent Transport System

Intelligent transport systems (ITS) are being developed to control and optimize network traffic flows. The technologies used are mainly intelligent technologies, that employ AI techniques, information technologies, and mathematical optimal transport methods. The main feature of modern ITS is their integration with methods of geoinformatics, spatial models, data mining, and geo/spatial knowledge acquisition methods. In this section, we propose functional structures of some components of integrated multi-agent ITS. The subsystem of active intelligent control of transport network (Fig. 2) consists of the following: (1) Measuring the traffic flow and analyzing data that facilitates the transport network management; (2) Operative Planning including the study of transport network behavior under various scenarios (such as bad weather, accidents, road works, increased demand, etc.), as well as developing control strategies that,

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when needed, increase the productivity of the transport network and assess the suitability of the developed strategies in terms of their cost and potential efficiency; (3) Strategy Selection as implementation of the most promising strategies directly on the highways by installing the necessary equipment and software; (4) Decision Support System that filters incoming real-time measurements, predicts the behavior of the transport system for the next few hours and helps the dispatcher choose the control strategy that best suits the situation; (5) Expert Knowledge module that uses retrospective data and AI techniques in the process of developing of control strategies and their selection; (6) Simulator module based on mathematical transport models that uses operative planning to run a large number of simulations of various scenarios and potential traffic improvement actions, where scenarios may include redistribution of traffic flows due to possible road works, increased travel costs, maximum road capacity, etc.; (7) Geomatics module that incorporates telematics and geoinformation systems data is used for constructing dynamic transport model and its calibration based on data processing methods. The adequate and efficient traffic flow allocation requires the system of traffic flow optimization and forecast whose structure is presented in Fig. 3. The complex traffic flow simulation subsystem that supports the active control of transport network is shown in Fig. 4. It contains the components: (1) Model / Map of TN provides the map of transport network of a city (area) in the form of a directed graph; (2) Crossroads describes the configuration of crossroads and the rules of passage of it; (3) Origin-Destination Traffic Flow provides the traffic flow information and generates the flow distribution between fixed origindestination pairs; (4) Traffic Flow Simulator provides the simulation of flows in

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Fig. 3.

Functional Structure of Traffic Flow Optimization and Forecast Subsystem

Fig. 4.

The Structure of Traffic Flow Assignment Simulation Subsystem

transport network based on traffic light signals and current traffic flow in the network; (5) Routing Module transforms the flow distribution into actual traffic flow allocation/routes with the use of the current situation in the transport network provided by the Traffic Flow Simulator; (6) Routes Scheduler contains information on travels that are currently being performed, represented in the form of routes as a sequence of links over which either the users are traveling or going to travel; (7) Historic Data module provides information/data support and keeps track of all the journeys in the network; (8) Traffic Flow Manager implements the control of traffic flow assignment in the network.

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The proposed generalized structures of ITS subsystems can serve as unified models for the development of perspective advanced AI-based ITS and intelligent control systems for dynamic traffic flow allocation in transportation networks.

6

Conclusion

We have introduced the notions of Wardrop optimal flows and Wardrop optimal networks and considered a dynamical model of optimal traffic flow distribution in parallel networks. We have shown the existence and uniqueness of Wardrop equilibrium in such networks. We have provided an evolutionary game theory formulation of dynamic approach to Wardrop optimal flows using the model of discrete-time replicator dynamics on Wardrop optimal networks. We have also proposed the conceptual and functional structure of intelligent information system for intelligent control, optimization and forecast, and simulation of dynamic traffic flow assignment in transportation networks. Future research will address the study of Wardrop optimal flows on dynamic networks and on general directed networks as well as algorithmic analysis of the developed models and methods.

References 1. Acemoglu, D., Ozdaglar, A.: Competition and efficiency in congested markets. Math. Oper. Res. 32(1), 1–31 (2007) 2. Nash, J.F.: Equilibrium points in n-person games. Proc. Nat. Acad. Sci. USA 36(1), 48–49 (1950) 3. Nash, J.F.: Non-cooperative games. Ann. Math. 54, 287–295 (1951) 4. Hofbauer, J., Sigmund, K.: Evolutionary game dynamics. Bull. Amer. Math. Soc. 40, 479–519 (2003) 5. Sigmund, K.: Evolutionary Game Dynamics. AMS, Providence (2010) 6. Hofbauer, J., Sigmund, K.: Evolutionary Games and Replicator Dynamics. Cambridge University Press, Cambridge (1998) 7. Patriksson, M.: The Traffic Assignment Problem: Models and Methods. VSP, The Netherlands (1994) 8. Acemoglu, D., Srikant, R.: Incentives and prices in communication networks. In: Nisan, N., Roughgarden, T., Tardos, E., Vazirani, V.V. (eds.) Algorithmic Game Theory, pp. 107–132, Cambridge University Press (2007) 9. Carlier, G., Jimenez, C., Santambrogio, F.: Optimal transportation with traffic congestion and Wardrop equilibria. SIAM J. Control. Optim. 47, 1330–1350 (2008) 10. Beckmann, M., McGuir, C., Winsten, C.: Studies in Economics of Transportation. Yale University Press, New Haven (1956) 11. Larsson, T., Patriksson, M.: Equilibrium characterizations of solutions to side constrained traffic equilibrium models. Matematiche (Catania) 49, 249–280 (1994) 12. Larsson, T., Patriksson, M.: Side constrained traffic equilibrium models: analysis, computation and applications. Transportation Res. 33, 233–264 (1999) 13. Cressman, R.: Evolutionary Dynamics and Extensive Form Games. MIT (2003) 14. Saburov, M.: On replicator equations with nonlinear payoff functions defined by the Ricker models. Adv. Pure Appl. Math. 12, 139–156 (2021) 15. Saburov, M.: On discrete-time replicator equations with nonlinear payoff functions. Dyn. Games Appl. 12, 643–661 (2022)

Sustainable Mobility: Changing Mindsets and Rethinking Paradigms Natalya Shramenko(B) and Christoph Hupfer Baden-Württemberg Institute of Sustainable Mobility, Hochschule Karlsruhe University of Applied Sciences, Karlsruhe, Germany {natalya.shramenko,christoph.hupfer}@h-ka.de

Abstract. The global problem of climate change necessitates the reduction of greenhouse gas emissions. Achieving the UN 2030 Sustainable Development Goals and the goals of the Paris Climate Agreement requires a transition from traditional approaches to planning, organization and development of cities and urban agglomerations to building sustainable systems and developing sustainable mobility. In this regard, it is necessary to change the worldview and rethink the paradigms of the further development of society in the context of global problems and crises. The publication focuses on the main paradigms. The study analyzes statistical data, which shows that the transport sector is the largest consumer of energy and plays a significant role in global greenhouse gas emissions. Thus, a significant reduction in greenhouse gas emissions, as well as the creation of a comfortable and safe urban environment, will be facilitated by a change in the model of consumption and mobility in cities. The directions for rethinking the established paradigms of the development of society in the face of climate change and the development of sustainable mobility are systematized. This can serve as a basis for system-wide transformations and further research on the development of activities and innovative solutions in the formation of strategies for the sustainable development of urban agglomerations. At the same time, for successful innovation processes in the development of sustainable mobility, comprehensive political support and decisive action from the administrative structures are required. Keywords: sustainable mobility · climate change · greenhouse gas · urban agglomeration · green logistics · transport

1 Introduction The global problem of the world community is the problem of climate change, which is associated with environmental pollution and the emission of harmful substances into the atmosphere. Solving the problem of climate change on Earth requires changing the worldview, values, norms and culture of consumption [1]. In 2015, at the UN World Summit, the “2030 Agenda for Sustainable Development” [2] was adopted, which identifies 17 sustainable development goals that are of crucial importance for all mankind. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 712–721, 2023. https://doi.org/10.1007/978-3-031-31066-9_83

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To achieve the goals of sustainable development, it is necessary to move from traditional approaches to the planning, organization and development of cities and urban agglomerations to the formation of sustainable systems and the development of sustainable mobility. This requires rethinking the paradigm of further development of society in the context of global problems and crises, on the one hand, and taking into account the changing preferences of people in the current level of digitalization and the development of information and communication technologies, on the other hand. The aim of the research is to analyze statistical data and trends in the development of urban agglomerations, to systematize directions for rethinking the paradigms of social development in the face of climate change. The theoretical and methodological basis of research are general scientific methods: a systematic approach, analogy, generalization, analysis and synthesis.

2 Literature Review The term “sustainable mobility” was proposed in the Green Paper[3].The global problem of climate change necessitates the reduction of greenhouse gas emissions, especially in urban agglomerations [3, 4]. In 2015, the Paris Climate Agreement [5] brought together the efforts of 196 countries to curb climate change and its negative consequences.To support the green transition towards climate neutrality, the European Commission has set targets to reduce greenhouse gas emissions by at least 55% by 2030 compared to 1990 and to become the first climate-neutral continent by 2050 [6]. In [7], an analysis of the concept of sustainable mobility, the main transport policies implemented by the European Union and the United States is presented. The authors note that it is not enough to refer to environmental aspects, although they are of paramount importance, social and economic consequences must also be taken into account. The support of a targeted transport policy by the federal government and the EU plays a significant role[8]. The research presented in [9] shows that there is still a big gap between the theory of sustainable mobility and its implementation in practice. The conclusions drawn by the authors represent obstacles to the sustainable development of mobility in urban areas. Urban sustainability is seen as an important outcome of good urban governance.City administrations must promote the development of sustainable urban communities through the development of effective scenarios and urban planning, environmental protection and the optimal use of limited resources[10].In modern conditions, approaches to urban planning are changing. Urban planning needs to change stereotypes,we need to think big and start thinking differently about how we use space in our cities and how we regulate its use [11]. In turn, the effectiveness of urban planning is associated with extensive governance problems and includes both urban management and government (municipality or local government) [12]. Researchers focus on changing the urban management paradigm and offer various concepts.For example, the concept of integrated urban governance implies a change in the administration condition and in the way of thinking as well as a different attitude as regards the need for sustainable development of the cities [13].

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In the article [14], the authors argue that new technologies based on information and communication platforms facilitate massive forms of collaboration, which should be understood in terms of a new paradigm for governance: Open Governance. For a long period, the basis of urban growth was the car-centric transport paradigm, which led to adverse social, environmental and economic consequences. Mobility as a service (MaaS) is an innovative concept[15, 16],which can help change people’s behavior when choosing a mode of transport and reduce dependence on private cars [17]. However, for transport users, the car remains a convenient and preferred means of transport, which they are not ready to give up[18]. In modern conditions, there is a paradigm shift from classical logistics to smart logistics [19]. The ability to analyze big data allows you to make effective decisions to reduce costs in the supply chain [20, 21] and develop strategic approaches to transport management [22].Human-centeredness and sustainability are important aspects of modern logistics services, which requires rethinking and revising the appropriateness of technologies both at the operational and managerial levels [23]. In the context of the rapidly developing concept of “Industry 5.0”, the key technologies of intelligent logistics are based on human-machine systems, collaborative robots and human-robot cooperation [24].

3 Analysis of Statistical Data and Trends in the Development of Urban Agglomerations According to statistics [25], the largest CO2 emissions in the world fall on energy and transport - 73.2% (including energy use in industry - 24.2%, transport - 16.2%, energy consumption in buildings - 17.5%). Statistics provided by the European Commission [26] indicate that in 2019 the total volume of passenger traffic within the EU-27 amounted to 6038 billion pkm. Cars accounted for 71.6% of passenger traffic, railways - 7%. The total volume of freight traffic within the EU-27 in 2019 amounted to 3392 billion tkm. The share of road transport in this total volume is the largest - 52%, while the share of rail transport is 12% [26]. At the same time, Average GHG emissions (gCO2 e per passenger-km), well-to-wheel, for passenger and freight transport in the EU-27 in rail transport are 4–5 times lower than in road transport [27]. Thus, a significant reserve for reducing greenhouse gas emissions from transport is a shift in priority to the use of railway transport, including the integration and expansion of the scope of the railway infrastructure in cities and urban agglomerations. Statistical data [28] indicate that among all modes of transport, the largest emissions of greenhouse gases are 44.4% for cars and 27.3% for trucks of various carrying capacities. At the same time, an increase in the level of motorization[29–32] in most countries (Fig. 1) unconditionally leads to an increase in greenhouse gas emissions by cars of different categories. The evolution of road traffic deaths per million inhabitants on average on the roads of the European Union [33–36] shows an improvement in road safety between 2014 and 2021 (Fig. 2). However, this indicator is still at a high level.

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Thus, a significant reduction in greenhouse gas emissions, as well as the creation of a comfortable, accessible and safe urban environment, will contribute to a change in the consumption and mobility model in cities. Motor vehicles. Per 1000 people.

Fig. 1. The level of motorization in some countries for 2007, 2014–2016, 2021–2022

60 50

51

51.5

50

49

49

51 42

44

40 30 20 10 0 2014 2015 2016 2017 2018 2019 2020 2021 Fig. 2. Number of deaths in traffic accidents per million inhabitants, 2014–2021 on the roads of the European Union

In modern conditions, especially as a result of the COVID-19 pandemic, digitalization trends in all spheres of life and the associated needs for urban mobility are accelerating. “Home-office” and “co-working” are becoming common practice, which significantly reduces the need for office space, which is located mainly in the central part of cities. Online services and e-commerce are developing at a rapid pace, which leads to a significant reduction in the number of city trips of people. The development of SMART

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technologies, the concept of the “Internet of things”, information and communication platforms allows us to take into account the personalized needs of people and creates great opportunities for the rational use of time, as well as for the implementation of preferences when choosing a route and mode of transportation. The advent of sharing services is redefining the need for personal vehicles. At the same time, modern urban planning is characterized by car-centricity, the desire to increase the capacity of the road network, and the search for opportunities to create parking spaces. In recent years, there has been an increase in the level of motorization (Fig. 1), which leads to an increase in emissions of harmful substances into the atmosphere, an increase in noise levels and the number of traffic accidents. Deteriorating health conditions, including those associated with the emerging threat of a pandemic, the limited space of cities, the need to improve road safety, the need to concentrate social facilities and services in people’s areas, increase society’s desire for sustainable mobility.

4 Systematization of Directions for Rethinking the Paradigms of the Development of Society The sustainable development of modern urban agglomerations, as well as minimization of the consequences of the identified problems, can be achieved through a comprehensive understanding of the concept of sustainable mobility and the implementation of its strategies at different levels of decision-making.Thus, making cities more suitable for comfortable life is possible through the conscious desire of society to implement sustainable mobility strategies. It is necessary to change the values, norms and culture of consumption. In the context of confronting climate change and developing sustainable mobility, it is necessary to change the worldview and rethink the established paradigms of social development: – Changing the economic paradigm in the context of the introduction of digital technologies and automation of business processes. Changes are needed in the economic sector, focused on the integration of the payment system with mobility facilities and services. When making decisions and evaluating them, including pricing, it is necessary to move from a direct assessment of costs to a comprehensive assessment of the process, taking into account social and environmental factors. Further development of the circular economy, sharing economy and blockchain technologies is required; – A rethinking of the role of transport and mobility is required. The new transport paradigm considers transport as a single system integrated into the urban space, where the focus is on people and their needs in the pursuit of a comfortable urban life. The development of new mobility facilities and services should be based on the integration of transport, information and payment systems. It is necessary to develop a sustainable transport system based on social and environmental transformation, on intermodality and interoperability of various modes of transport. Significant attention should be paid to the rational use of urban space and infrastructure through the priority use of public transport and the sharing of individual vehicles (cars, bicycles, scooters). With the

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–

–

–

–

–

717

introduction of a set of motivational and incentive mechanisms, the MaaS technology will significantly reduce the use of personal transport for urban travel; The paradigm of managing urban systems is changing, based on innovations in public policy. There is a need for system-wide transformations and the transformation of the process of making traditional local decisions into a system of integrated decisions aimed at the economic and social development of cities suitable for a comfortable life, taking into account the needs of people of various categories and the interests of future generations. For this purpose, a digital information and communication platform can be used that will facilitate effective, unhindered communications and cooperation between authorities, citizens, businesses and all interested parties; The urban planning paradigm should be based on systemic intersectoral integration, further development of the smart city concept and implementation of the concept of transit-oriented design. The main trends in rethinking the urban planning paradigm are associated with the digitalization of all spheres of life (the development of SMART technologies, e-commerce, the Internet of things), a change in mobility preferences (working remotely, “home-office”, “co-working”, the availability of many modern online services), the need to redistribute urban space to maintain and preserve the natural ecosystem; Modernization of the regulatory paradigm. It is necessary to develop new standards and regulations for the development of sustainable transport systems and the effective management of sustainable mobility. Particular attention should be paid to the development of public transport, the development of unified technical standards, the introduction of innovative resource-saving technologies and the use of alternative forms of energy; The formation of a new paradigm of smart logistics, which is based on a combination of the concepts of applying innovations in infrastructure, innovative vehicles and transport technologies, as well as optimizing the process of transport management in a dynamically changing logistics environment. In connection with the transition from supply chains to complex logistics networks with a large number of random factors, it is necessary to use new methods and technologies for making and implementing logistics decisions. To optimize transport and logistics processes, such methods as data analysis, artificial intelligence, and machine learning methods are of paramount importance. Logistics services in modern highly dynamic markets should be characterized by adaptability, flexibility, intellectualization of logistics operations and logistics infrastructure facilities, environmental friendliness; It is necessary to change the worldview and life values of the population. The basis of a comfortable and happy life is a healthy lifestyle and a safe living environment. In this regard, it is necessary to change the norms and culture of consumption.

However, socio-ecological transformation is impossible without comprehensive political support. Successful innovative processes in the development of sustainable mobility require decisive action on the part of administrative structures in the formation and implementation of municipal policy, as well as social policy (including the functioning of a sustainable transport system), which are aimed at improving the level and quality of life of the population.

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5 Let’s Make It Happen If we look at the processes that are carried out in the implementation of concepts for sustainable mobility, it seems obvious that in sustainable mobility, too, knowledge often does not lead to corresponding action. The reasons for this can essentially be seen in the fact that the people for whom a change is planned are not sufficiently involved in the planning. Or that solutions are offered to problems that people do not see as their own. And finally, because the changes are often associated with restrictions and not with gains. It is therefore also necessary to pursue participatory mobility development that involves people in the change process at an early stage, actively and decisively. Then people have the chance to see challenges, develop qualities and make the changes their own heart’s desire. Here, living labs have proven to be a low-threshold, participatory approach with a high impact on the decision to change [37]. Finally, authoritative decisions, many of which are made by laypeople in political committees, must be prepared in such a way that the qualities of the plans can be better grasped and the increase in quality of life can be addressed as an individual benefit. It is helpful to summarize the multitude of criteria and aspects into one authoritative decisive question. Then central changes or improvements can be addressed in a tangible way and lead to viable decisions [38].

6 Conclusion Urban agglomeration development trends are associated with the rapid development of digital technologies and information and communication platforms that open access to many online services and contribute to the development of e-commerce and the Internet of things, as well as create opportunities to take into account people’s personal mobility preferences. Increasing emissions of harmful substances into the atmosphere, the presence of traffic congestion, the increase in noise levels and the number of traffic accidents, as well as the limited space of cities, increase the desire of society to develop sustainable mobility. The analysis of statistical data shows that the share of road transport in the total volume of passenger and freight traffic within the EU-27 is the largest and amounts to 52%. Thus, a significant reduction in greenhouse gas emissions will be facilitated by a change in urban consumption and mobility patterns. The directions for rethinking the established paradigms of the development of society in the face of climate change and the development of sustainable mobility are systematized. Large-scale changes in various sectors of the urban economy and system-wide transformations aimed at the development of sustainable cities will make it possible to obtain a synergistic effect in the future by improving the quality of life of people, creating a comfortable urban environment, and increasing the investment attractiveness of cities. However, successful innovation processes in the development of sustainable mobility require comprehensive political support and decisive action on the part of administrative structures.

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The findings presented in this paper can serve as a basis for system-wide transformations and further research on the development of activities and innovative solutions in the formation of strategies and plans for the sustainable development of urban agglomerations.

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Model of Optimization of Cargo Space Volume Utilization in Delivery Vehicles Maida Eljazovi´c1,2(B) and Ermin Muharemovi´c2 1 Nelt Ltd., East Sarajevo, Bosnia and Herzegovina

[email protected] 2 Faculty of Traffic and Communications, University of Sarajevo, Zmaja od Bosne 8, 71 000

Sarajevo, Bosnia and Herzegovina

Abstract. Optimum use of the volume of the cargo space of the vehicle requires compliance of the dimensions of pallets, transport packaging and basic packaging with the dimensions of the vehicle’s cargo space. A detailed analysis of the packed goods and the way of filling the space in the delivery vehicle requires a comparison of the system data with the actual data during loading. This problem stems from the complexity of the input data, which is greatly influenced by the ordering method, the choice of packaging, the quantity and number of different items.The paper proposes a model for optimizing the volume provided by software in relation to the actual volume. The model introduces coefficients that allow a more precise calculation of the actual volume. Keywords: Optimization · Packaging · Volume utilization · Vehicle fleet · Utilizationcoefficient

1 Introduction In accordance with the demands of the market and modern tendencies of sustainable development, there is a need and aspiration to improve logistics processes, reduce transport costs, and improve the systems used in transport in the observed company. All of the above requires the implementation of continuous analyses and measurements, in order to achieve an optimal solution in the daily delivery of goods to customers and consumers. Since most transport route optimization systems provide precise data on the weight of the loaded shipment, pallet occupancy and mathematical volume, without analyzing the physical volume of the packed shipment, which includes the “air” transported in the packaging in everyday business, this information is necessary as would have insight into the actual utilization of each vehicle in the fleet. This paper proposes a model that, with a combination of system and real physical measurement, will improve the utilization of the cargo space of delivery vehicles.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 722–728, 2023. https://doi.org/10.1007/978-3-031-31066-9_84

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723

2 Adjusting the Transport Packaging Dimensions with Transport Means Standardization in the area of product distribution includes all means (packaging, pallets, containers, vehicles, handling machinery, storage equipment, etc.) and procedures related to the manipulation, storage and transportation of goods. In order to make the best possible use of the cargo area of the delivery vehicle and container, it is necessary to harmonize the dimensions of pallets, transport packaging and basic packaging with the dimensions of the cargo space. In this process, packaging plays a big role, i.e. packaging of goods in boxes [1], for the purpose of combining several products that are delivered to one customer or for the purpose of easier loading, unloading and transportation. At the same time, the selection of adequate packaging is a complex process when it comes to transporting shipments of different dimensions, which do not have the possibility for “ideal” packaging to maximize the use of packaging. Significant problems during transport planning arise when packing non-standard and different items in the cargo area of the means of transport. Some items have their own transport packaging, while others must be packed individually in separate boxes. The aforementioned affects the impossibility of completely compact packaging and the reduction of the level of cargo space utilization, which can indirectly cause numerous problems [2]. It happens that due to the lack of space in the cargo space it is not possible to load all the shipments intended for delivery, or that the vehicles are not loaded enough, and that there is a large volumetric part which is taken up by “air”.

3 Analysis of the Capacity Utilization of Cargo Space of Delivery Vehicles Analysis of fleet utilization provides data that facilitates fleet management and finds ways to reduce costs and increase overall profit. The paper analyzes the volume utilization of the company’s vehicles, which is engaged in the delivery of consumer goods to customers on the territory of Bosnia and Herzegovina. Based on the results of the analysis, proposals for improvement elements are formulated, the application of which would optimize the use of delivery vehicles. The software that is the subject of the analysis is used to optimize delivery, and it serves to distribute packages by vehicles and send those vehicles to delivery points [3]. The goods are distributed by vehicles in order to evenly distribute the load on all delivery vehicles. Advanced algorithms take into account the total mileage per individual vehicle and the working hours of workers, the compatibility of types of goods and vehicle models is also taken into account. The need to find a model for the analysis of the utilization of the volume capacity of the cargo area stems from the fact that all intelligent systems used in the distribution of shipments provide accurate data on the weight utilization of the vehicle (carrying capacity), pallet capacity, working time, vehicle kilometers traveled, consumption in a simple way fuel but not the volume utilization of space [4].

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This problem stems from the complexity of the input data, which is greatly influenced by the ordering method, the choice of packaging, the quantity and number of different items. In order to obtain accurate vehicle utilization data as well as the amount of transported “air” in package boxes, it is necessary to measure the physical volume of packed and loaded goods over a longer period of time and compare the same volume with the system volume. The system volume is the measurement of each item by its dimensions and the summation of all products in one vehicle, not taking into account the unused space between packed products. 3.1 Defining the Model The analysis is based on the observation of three types of customers who are classified by turnover (income) and quantity of goods delivered. They are divided into three categories TIR 1, TIR 2, TIR 3. TIR 1 customers represent customers of the largest category in terms of turnover. The average number of pallets of goods delivered to this category of customers is from 14 to 18 pallet places, which are delivered by N1 category vehicles. TIR 2 customers represent customers of the middle category in terms of the traffic they achieve, customers who are delivered by vehicles of category N2. TIR 3 customers are customers of the smallest category in terms of the traffic they achieve, these customers are delivered by vehicles of category N3. Categories of delivery vehicles[5] are divided into three categories: N1 category represents delivery vehicles with 18 pallet spaces, load capacity 8 t and volume 27.6 m3 . The N2 category represents vehicles with a capacity of 8 pallets, 3t capacity and a volume of 12.2 m3 . The N3 category represents vehicles with a capacity of 4 to 6 pallet spaces, a load capacity of 1 to 3t and a volume of 9.2 m3 . Depending on the size of the company, within one category there may be several delivery vehicles transporting the same category of customers, which is shown in Table 1. Table 1. Categories of customers, vehicles and system volume Vehicle category Ni

Customer Category

System Volume (m3 )

Vehicle capacity (m3 )

System vehicle utilization

N1

TIR 1

VN1,TR1

CN1,TR1

ISN1

N2

TIR 2

VN2,TR2

CN2,TR2

ISN2

N3

TIR 3

VN3,TR3

CN3,TR3

ISN3

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725

The system utilization (ISNi ) of the delivery vehicle is obtained as the ratio of the system volume of the vehicle’s capacity and the volume of the loaded goods ISNi =

CNi,TR VNi,TR

(1)

where: VNi,TR – System volume for N category and TR customer category, CNi,TR – Vehicle capacity of the N category, which is defined by the vehicle manufacturer. The calculation of the system volume is based on the multiplication of the length, width and height of the individual article [6]. If we observe several items and mark them with x1, x2 , x3 …xn .Then the total volume for the observed group of articles is calculated according to the formula: n VNi,TR = xi (2) i=1

After calculating the system volume according to formula (2), the vehicle capacity is known, it is possible to calculate the system utilization of the vehicle capacity using formula (1). In order to determine the ratio of the system and physical volume, it is necessary to calculate the physical volume.Physical volume VFIZ is calculated by measuring packed goods on euro pallets in dimension of 1,2 × 0, 8 m, multiplied by the height of the tallest point of the packed goods on each pallet and the number of pallets in the vehicle: VNi,FIZ = 1, 2 × 0, 8 × h × p

(3)

where: h- height of the tallest point of the packed goods on the pallet. p- number of pallets in the vehicle. The coefficient is calculated according to the formula: k=

VNi,FIZ VNi,TR

(4)

where: k- system and physical volume ratio coefficient, VFIZ – physical volume, VN,TR – system volume. If we add the coefficient K to the vehicle utilization system data, we will get the actual volume utilization of the vehicle IFIZ , including the empty space transported in packaging. Vehicle utilization is calculated according to the formula: IFIZ = k × ISNi

(5)

This information is essential for analyzing the utilization of the company’s vehicle fleet, for making decisions [7] about the purchase of new vehicles and input for choosing the packaging in which certain products are packed [8].

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3.2 Model Application Example As an example, a company that makes deliveries on the territory of Bosnia and Herzegovina was taken, where a total of 9 vehicles were observed, 3 vehicles for each of the categories. Table 2 shows the system volume obtained with loading the data from the ERP database for each individual item by its dimensions (length, width, height) for the observed company that uses the Sky Track system. Using the formula (1),system utilization was calculated, as shown in Table 2. Table 2. System display of vehicle capacity utilization from the Sky Track system Vehicle category

Customer Category

System Volume m3 VNi,TR

Vehicle capacity CNi,TR

System Volume Utilization ISNi

N1

TIR 1

16,7

27,6

60,40%

N1

TIR 1

14,74

27,6

53,40%

N1

TIR 1

12,31

27,6

44,60%

N2

TIR 2

7,92

12,2

64,90%

N2

TIR 2

6,76

12,2

55,40%

N2

TIR 2

6,52

12,2

53,40%

N2

TIR 3

4,6

9,2

50,00%

N2

TIR 3

4,03

9,2

43,80%

N2

TIR 3

4,01

9,2

43,60%

To calculate the physical volume VFIZ , statistical measurements were used, which were made on a 5-year basis on three routes every day, a total of 3,600 measurements. Table 3 contains the physical volume data calculated according to formula (3) for the observed categories of customers and vehicles. Formula (4) was used to calculate the coefficient that gives the ratio between the system and physical volumes, and the results are entered in Table 3. Table 3. System and physical volume ratio. Vehicle category

Customer Category

System Volume m3 VNi,TR

Physical Volume m3 VNi,FIZ

System and physical volume ratio k

N1

TIR 1

16,7

19,3

1,15

N1

TIR 1

14,74

18,5

1,26

N1

TIR 1

12,31

15,8

1,28 (continued)

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727

Table 3. (continued) Vehicle category

Customer Category

N2

TIR 2

N2

System Volume m3 VNi,TR

Physical Volume m3 VNi,FIZ

System and physical volume ratio k

7,92

10,3

1,30

TIR 2

6,76

9,8

1,45

N2

TIR 2

6,52

10,4

1,60

N2

TIR 3

4,6

7,4

1,61

N2

TIR 3

4,03

7,1

1,76

N2

TIR 3

4,01

7,5

1,87

The results showed the following: For customers in the TIR 1 category, physical and system volume ratio coefficient k was calculated in the range of 1.15 to 1.28. For customers in the TIR 1 category, physical and system volume ratio coefficient k was calculated in the range of 1.30 to 1.60. For customers in the TIR 1 category, physical and system volume ratio coefficient k was calculated in the range of 1.61 to 1.87. Using the formula (5), the actual physical utilization of the vehicle was calculated, as shown in Table 4. Table 4. Actual physical utilization of cargo space volume Vehicle category

Customer Category

System and physical volume ratio k

System volume utilization ISNi

Actual physical utilization IFIZ

N1

TIR 1

1,15

60,40%

69,50%

N1

TIR 1

1,26

53,40%

67,00%

N1

TIR 1

1,28

44,60%

57,20%

N2

TIR 2

1,3

64,90%

84,40%

N2

TIR 2

1,45

55,40%

80,30%

N2

TIR 2

1,6

53,40%

85,20%

N2

TIR 3

1,61

50,00%

60,60%

N2

TIR 3

1,76

43,80%

77,20%

N2

TIR 3

1,87

43,60%

81,5 %

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M. Eljazovi´c and E. Muharemovi´c

4 Conclusion Companies that deal with the transportation of goods usually have their own vehicle fleet, which needs to be analyzed daily and to conclude what decisions to make in the future. The utilization of the fleet of road freight vehicles is the most important component of decision-making in business, and through analysis it is possible to determine the profitability of certain business opportunities and show whether there are other ways to make business mutually beneficial for clients and for the company.[5]. It can be concluded that with coefficient k being higher, the greater the relationship between the volume provided by the system and the actual volume, or in other words we have a larger amount of transported “air” in the transport process. In the observed example, it can be concluded that the physical or actual utilization of the cargo area is 12–27% higher than the system utilization. If only system data was used we would have an approximate utilization of the cargo space, which is lower than the actual utilization, where as a result the planned goods for transport would not be able to be loaded into the planned vehicle. By combining the system and periodically measured coefficient k, we get accurate data on the free and used volume in vehicles, which gives us the opportunity to precisely plan business activities and better use transport capacities.

References 1. García-Arca, J., Garrido, A.T.G.-P., Prado-Prado, J.C.: Packaging Logistics. In: International Encyclopedia of Transportation. Elsevier, pp. 119–129. https://doi.org/10.1016/B978-0-08102671-7.10230-1 (2021) 2. Lazarevi´c, D., Dobrodolac, M., Petrovi´c, M.: Optimizacija iskoriš´cenja tovarnog prostora formiranjem geometrijskog modela plana pakovanja pošiljaka. In: Proceedings of the International Scientific Conference - Sinteza 2019, pp. 45–51 (2019). https://doi.org/10.15308/Sin teza-2019-45-51 3. Guzenko, A. Guzenko, N.: Process optimization for last mile logistics. Transp. Res. Procedia 63, 1700–1707 (2022). https://doi.org/10.1016/j.trpro.2022.06.184 4. Jacyna, M.: The role of the cargo consolidation center in urban logistics system. In: International Journal of Sustainable Development and Planning, vol. 8, no. 1, pp. 100–113 (2013). https:// doi.org/10.2495/SDP-V8-N1-100-113 5. Kosovac, A., Muharemovic, E.: Pickup and delivery costs - a proposed outsourcing model based on the number of stops. J. Appl. Eng. Sci. 19(2), 270–274 (2021). https://doi.org/10. 5937/jaes0-28450 6. Park, H., Van Messem, A., De Neve, W.: Item measurement for logistics-oriented belt conveyor systems using a scenario-driven approach and automata-based control design. In: IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA), pp. 271–280 (2020). https://doi.org/10.1109/ICIEA49774.2020.9102044 7. Abate, M.A.: Essays on capacity utilization, vehicle choice, and networks in the trucking industry Kgs. Lyngby: Technical University of Denmark, Department of Transport (2013) 8. Vasi´c, N.D.: Modelling and defining logistics service dimensions in electronic commerce, Doctoral Dissertation, University of Belgrade, Faculty of Transport and Traffic Engineering. Belgrade (2021)

Mobility-as-a-Service and the Future of Urban Mobility: A Human-Centered Approach to Multimodal Journey Planning Bia Mandžuka(B) , Marinko Jurˇcevi´c, and Krešimir Vidovi´c Faculty of Transport and Traffic Sciences, Vukeli´ceva 4, 10000 Zagreb, Croatia [email protected]

Abstract. This paper examines the potential of Mobility as a Service (MaaS) to shape the future of urban mobility from a human-centered perspective. The concept of smart mobility and its effects on human behavior and urban areas are discussed (as a key component of Smart City Paradigm), and a definition and background of MaaS is provided, including a taxonomy of integration levels. The paper also analyzes two existing Multimodal Journey Planners (MJPs) within the MaaS ecosystem. Keywords: Mobility-as-a-Service · urban mobility · Human-centered · Multimodal Journey Planners (MJPs)

1 Introduction Urbanization has caused shifts in how people move around and their travel behavior and preferences. Traditional transportation planning methods often focus on the typical commute from home to work/school and back. However, to truly understand and plan for current mobility needs, a more comprehensive approach is required that takes into account the diverse and ever-changing nature of people’s travel patterns. The unpredictability of mobility in urban areas and the complexity of people’s travel habits necessitate this broader perspective. The European Commission has prioritized promoting sustainable mobility for several years. The goal of EU measures and programs is to enable all residents seamless mobility and access to key destinations and services, increase service safety, reduce harmful emissions and noise, and improve the efficiency and profitability of the transportation system as a whole [1, 2]. The topic of sustainable mobility is prevalent in the European context, as evidenced by significant investments from EU funds. A significant shift in approach towards increasingly frequent mobility issues began in 2013 with the creation of the European concept of transport planning in urban areas, in the form of the “EU 2013 - Urban Mobility Package”. Based on this package, the concept of “Sustainable Urban Mobility Plans (SUMP)” was established. SUMP is a strategic plan that builds on existing practices in planning and considers integration, participation, and evaluation principles to meet the mobility needs of city residents (now and in the future) and ensure © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 729–738, 2023. https://doi.org/10.1007/978-3-031-31066-9_85

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a better quality of life in cities and their environment. In recent years, encouraged by EU transportation policies, multimodal passenger systems have become imperative in addressing mobility issues [3]. Smart cities aim to address the negative impacts of high motorization levels in urban areas by implementing sustainable and integrated city concepts. This includes the integration of smart services and advanced technologies to improve the overall quality of life in the city. Smart mobility, which involves the application of intelligent transport systems, is a key component of this concept and aims to provide intuitive and human-centered services for travel planning and transportation. The focus is on meeting the needs of modern individuals and addressing issues such as urbanization, climate change, and pollution. The idea of “human-centered mobility” is frequently brought up in discussions about “smart mobility”. This concept focuses on meeting the needs of modern individuals through smart and user-friendly services, from the initial planning stages of a trip to providing up-to-date information during the journey [4]–[7]. Smart cities aim to optimize processes in urban environments by implementing sustainable solutions that promote economic prosperity and social well-being, while also protecting the environment and improving the quality of life. Mobility-as-a-Service (MaaS) is a new approach to urban mobility that offers a mobility solution tailored to users’ needs by integrating various modes of transportation such as public transportation, car sharing, bike and car rentals, and taxi services on a single platform [8]. The paper consists of five chapters. The second chapter, entitled “Smart Mobility - a key element of Smart City paradigm”, delves into the concept of smart mobility as a fundamental component of the Smart City and its goals, particularly in urban areas. It also focuses on Advanced Traveler Information Systems (ATIS) and Integrated Multimodal Traveler Information (IMTI) [9, 10]. The third chapter, “Mobility-as-a-Service Paradigm” provides a definition and background of the MaaS concept, as well as a taxonomy of levels of integration. It also examines how MaaS can change the way people travel. The next chapter, “Multimodal Journey Planning within MaaS”, presents an overview of two journey planners supported by MaaS. Finally, the concluding considerations offer insights into the role of MaaS in shaping the future of urban mobility and potential areas for further research.

2 Smart Mobility - a Key Element of Smart Cityparadigm The negative effects of high levels of motorization are most felt in cities. Therefore, it was necessary to design a new paradigm, that is, a sustainable and integrated city concept that will eliminate or at least alleviate negative impacts on the environment. In this sense, the concept of the smart city emerges as a response to the many challenges faced by urban environments - increasing urbanization and the associated demographic changes, climate change, environmental pollution, etc. Imbalances in the urban environment also affect human health, quality of life and other living organisms in the ecosystem. Despite numerous scientific efforts, strategies, and initiatives in the form of measures and awareness raising, research suggests that humanity is still not approaching global sustainability. The widely accepted goal of the smart city concept is to improve economic growth and social development through innovative, smart technology and strong collaboration among key stakeholders.

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Today there are many definitions and understandings of the Smart City concept, and in literature, the concepts of “intelligent city” and “digital city” are often found, which are conceptual versions. Therefore, there is still no official and unambiguous definition for the term “smart city”. In general, the term “Smart City” is a broad concept that encompasses almost all conceptual versions and corresponding characteristics. One of the most widespread versions of the smart city model is based on six “smart” dimensions smart economy, smart mobility, smart environment, smart people, smart living, and smart governance [11]. The integration of advanced technologies is driving the adoption of smart city concepts. This paradigm relies on connecting smart services to enhance urban living. Technologies like IoT, Big Data, and AI will play a critical role in the future development of smart cities (Fig. 1).

Fig. 1. Smart City concept with key components (adapted by the authors) [11]

“Smart Mobility” is essential for the sustainable functioning of urban areas, reducing traffic congestion, environmental pollution, and providing more accessible and sustainable options for all groups of users. Additionally, the concept of “Human-centered mobility” [4] is often mentioned in the context of smart mobility, which focuses on meeting the needs of modern individuals through intuitive, smart services, from the moment of travel planning, ticket buying to available and timely information during travel. The

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Smart Mobility concept is a fundamental component in the push for sustainable transportation. Analysis of literature in the field of Smart Mobility shows that the main goals fall into four categories [12]–[15]: reducing environmental pollution and noise pollution, decreasing traffic congestion, increasing traffic safety, and increasing the availability of public transportation. The goal of introducing advanced solutions in the transportation system is to improve the efficiency of existing infrastructure and reduce physical expansions that attract additional traffic. In this regard, intelligent transport systems play a significant role as they represent a holistic, management and information-communication upgrade to the classic transportation system, resulting in significant improvements in performance, traffic flow, more efficient passenger and cargo transport, improved traffic safety, comfort, and protection of passengers, reduced environmental pollution, etc. It is difficult to imagine flexible and high-quality public transportation without the application of Intelligent Transport Systems (ITS). By implementing ITS services in urban transport, there is an increase in attractiveness, reliability, availability, and accessibility [16]. In recent years, Traveler Information Systems (TIS) have been particularly relevant as support for trip planning. Providing information to travelers is one of the functional areas of ITS. This area includes static and dynamic information about the transportation network, pre-trip and travel information services, and support for services that collect, store, and manage information for transport planning. Pre-trip information services are significant for users as they allow for trip planning from home or any other location where internet access is available and information about transportation modes, time, or travel costs are provided. In addition to pre-trip information, access to information during the trip is also important (known as On-trip planning) [16]. Advanced Traveler Information Systems (ATIS) are advanced systems that help travelers make informed decisions about their trip, before and during their journey. These systems are designed to adapt to the specific needs of each individual user, and the latest ATIS systems are capable of providing real-time support for multimodal travel. The framework for third-generation ATIS systems, which are personalized and support multimodal travel in real-time, has been proposed in recent research studies [9, 17]. Integrated Multimodal Travel Information (IMTI) is particularly important as it enables travelers to access a variety of transportation options in an integrated way. Multimodal Journey Planners (MJPs) are built on this information and are a key component of ITS systems, as they provide a wide range of information to assist users in planning door-to-door trips. They represent the integration of various services and are considered a crucial component of ITS implementation today [10, 18]. Overall, smart mobility has the potential to revolutionize transportation by making it more efficient, safer, and more sustainable. It can also improve the overall travel experience for passengers by providing them with accurate, real-time information and more options for transportation. As technology continues to advance and cities become increasingly congested, smart mobility will become even more important in addressing the challenges of transportation and mobility.

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3 “Mobility as a Service” Paradigm Mobility today can be seen as a constantly evolving entity, where users adapt to new conditions. To make the most of human mobility, solutions that are sustainable and adaptable are needed, which will bring about economic growth and social benefits, while also protecting the environment and improving people’s quality of life. In this context, Mobility-as-a-Service (MaaS) is a novel approach that aims to make mobility more efficient. It provides a service that combines different forms of transport such as public transport, shared mobility, bike rentals and taxi services all on one platform, accessible via a mobile app or web interface. The MaaS paradigm places the human – “the user of the transport system” at its core. In this way, it represents a higher service level, where mobility is tailored to the user (based on the preferences and needs of the modern user - the passenger) [8, 19]–[21]. A digital platform, which can be accessed through a mobile app or web interface, allows individuals to plan their multimodal trips using real-time travel information through a multimodal travel planner. This platform also enables users to reserve and pay for the service through a single integrated ticket. As a result, the cost of travel is no longer a significant factor in determining one’s choice of trip or route because the integrated ticket covers all transportation costs. Additionally, the service can be paid for through a monthly or annual subscription package called “mobility package” or “pay-as-you-go” system, where users have the option to choose from fixed, flexible, and unlimited package options [8]. The reliance on personal vehicles is a significant problem as it contributes to both air pollution and traffic congestion. To address these issues, it is important to encourage the use of more sustainable modes of transportation such as public transportation, biking, and walking. One way to do this is by developing services that make these options more convenient and accessible for people. Mobility as a Service (MaaS) is a solution that aims to meet the needs of real users. “With a majority of people now owning smartphones and regularly using transportation apps, technology can play a crucial role in simplifying the journey for them. People expect technology to assist them in choosing the right mode of transport at the right time, having access to multiple modes of transport and optimizing the route and duration of their journey” [22]. MaaS can lead to more efficient and convenient travel experiences by increasing travel demand through making it more convenient and affordable for people to travel, leading to more trips being taken. It can also change travel habits by making it easier for people to take spontaneous trips or to travel at times or to places that they might not have otherwise considered. Additionally, MaaS can provide personalization of the service, based on user preferences and/or data collected from the user, leading to a more tailored and efficient service. Furthermore, MaaS can also provide cost savings for users by allowing them to pay for transportation on a pay-per-use basis, rather than owning a car and paying for fuel, insurance, and maintenance. Furthermore, it can increase the use of public transportation by providing users with convenient and integrated options for planning and paying for trips that include multiple modes of transportation, including public transport [20, 23]–[26]. As people’s schedules become more hectic and complicated, they are becoming increasingly demanding in terms of the services they need for transportation. They want

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to reduce the time they spend waiting, and they want to be able to choose the best travel options that fit their schedules. Nowadays, real-time passenger information is available through various platforms. For example, Google Maps provides a lot of information about public transportation, however, other features such as payment, booking, and integration of different travel modes are either not fully integrated or not available at all. MaaS has the potential to offer a better and more user-friendly experience by providing integrated services. A taxonomy of four levels of MaaS system integration is provided in Table 1., including a level of “zero/no integration”. This taxonomy can be used as a reference when comparing different MaaS concepts [27]. Table 1. Taxonomy of MaaS (adapted by the authors) Level of integration

Explanation

0 No integration

Separate services are provided for different means of transport

1 Integration of information

“Single trip focus”, “users rather than costumers”, users are not ready to pay for service (e.g., Google Maps)

2 Integration of booking & payment “A natural extension to a travel planner”, finding routes, booking, and paying for individual trips is made easier 3 Integration of the service offer

“Contracts and responsibilities”, “focuses on the total need of a household”, mobility bundles & subscriptions

4 Integration of the societal goals

“Added value is reduced private car ownership and use”, “a more accessible, liveable city”, promoting the sustainability of the urban environment

Source:[27]

MaaS is a concept that goes beyond the mere integration of existing public transport options. It encompasses the introduction of new sharing mobility solutions, such as bicycle sharing and e-scooters as a new micro-mobility service. These new forms of transportation supplement the existing range of public transport systems, offering a wider range of options for users to choose fromand which better cover the real needs of end-users. The integration of these new forms of transportation, and the resulting increase in mobility options, can lead to a more efficient and sustainable transportation system overall.The effective implementation of MaaS requires a holistic approach and collaboration between various stakeholders, including the government, transportation providers, and technology companies. According to [28] the definition of MaaS will tolerate integration level 2 as the bottom, which includes the integration of booking and payment. In the next chapter, examples, and initiatives within the MaaS concept are described.

4 Multimodal Journey Planning Within MaaS The challenge of creating sustainable transportation is multi-faceted, requiring a shift in thinking and understanding not only at the societal level, but also at the individual

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level of users and travelers. Switching from personal cars to more sustainable modes of transportation is still a challenging behavioral change for individuals and a larger societal issue. In addition to the convenience, comfort, and status associated with owning and using a personal car, it is important to offer a sustainable transportation concept (especially in urban areas) that can compete with the attractiveness of personal cars [29]. As mentioned earlier, the core of this new concept revolves around people, the end user (customer). Changing the way people think about mobility is a complex task that requires a systematic approach. To be truly successful in this transition, it is important to understand and take into account the specific needs and preferences of the end user and to offer a sustainable mobility solution that is tailored to these needs. Timely and accurate information is especially important for multimodal trips, precisely because of the complexity of such journeys. Available travel information can greatly influence the decisions of travelers who want to get to their destinations in the most convenient, i.e., the most efficient, way. Travelers need multimodal information systems adapted to their needs, which can provide information before and during the trip with regard to the combined mode of transport (according to preferences). Travel planners should not only be considered as pre-trip data search tools, but should encompass the entire travel process, providing complete and integrated services to travelers. Travel information, especially personalized, can influence the decisions of travelers who want to reach their destinations in the most convenient way and, ultimately, overall satisfaction with public transport services. Within the EU region, there are various active multimodal travel planners available with varying functionalities. Many of them include basic features for selecting a multimodal route, but only a few are fully personalized and user-oriented [30]. Given the characteristics of the multimodal travel concept, it is obvious that there is a need for a user-centered journey planning information platform [31]. In this context, MaaS signifies a transformative shift in how transportation is approached and there are many platforms available now, known as multimodal travel planners that MaaS at some level of integration. The integration level of these platforms can vary, with some offering basic functions for selecting a multimodal route and others being completely user oriented. The emergence of these platforms demonstrates the growing demand for more convenient, efficient, and sustainable transportation options. Whim and Citymapper are examples of platforms that, as described in the literature, fall under the third level of integration in the MaaS taxonomy [27, 32]. These platforms are highlighted and discussed in further detail below. Whim One of the main transportation goals of the city of Helsinki is to reduce the level of motorization, that is, to encourage a transition from personal cars to more sustainable modes of travel. In order to achieve this, it is necessary to offer a flexible, easy, fast, and affordable service that can compete with the more dominant mode of transportation, the personal car. The city of Helsinki offers an application called Whim, which represents the third level of integration in the MaaS taxonomy and is the highest level of available applications. The service is aimed at a well-defined group of users who prefer multimodal travel. The application provides a range of features and a wide range of available mobility

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services, from public transport (the multimodal mobility offer is diverse) to bike-sharing systems, taxi services, car-sharing services, and conventional car rental services. To achieve a high level of integration and collaboration among stakeholders, a key step was to open and share data between transportation service providers and other actors involved in the mobility service provision process. Whim is available in Vienna, Antwerp, Turku, Tokyo, Switzerland, and Birmingham [33]–[35]. Citymapper Citymapper is a widely used multimodal travel planner app available in many European and American cities. It offers a wide range of features that enhance the overall experience of the user. The app provides step-by-step instructions during the trip, which is especially useful for complex multimodal journeys. It also displays fare information for different modes of transportation and integrates with platforms like Uber, Lyft, City Bike, and GREEN Bike. Additionally, it allows users to customize their profile by saving favourite routes and stops. Users can also subscribe to receive information on specific modes of transportation and share their location via social media with selected contacts. The app is also available for the city of Zagreb [36].

5 Conclusion Mobility as a Service (MaaS) is a mobilityparadigm that aims to provide users with a convenient and seamless way to access various modes of mobility by integrating them into a single, digital platform. It can transform the way people travel by delivering a personalized and seamless experience for individuals and society as a whole. The concept of MaaS is just one aspect of the larger shift towards more efficient and sustainable mobility. It’s not just about technology and service, but also the collaboration and integration of various stakeholders to create a seamless and inclusive mobility experience.

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26. Zhao, X., Andruetto, C., Vaddadi, B., Pernestål, A.: Potential values of MaaS impacts in future scenarios. J. Urban Mob. 1, 100005 (2021). https://doi.org/10.1016/J.URBMOB.2021. 100005 27. Sochor, J., Arby, H., Karlsson, M., Sarasini, S.: A topological approach to Mobility as a Service: a proposed tool for understanding requirements and effects, and for aiding the integration of societal goals. In: International Conference on Mobility as a Service (ICOMaaS) (2017). Accessed 21 Jun (2022). https://www.researchgate.net/publication/320 107637_A_topological_approach_to_Mobility_as_a_Service_A_proposed_tool_for_unders tanding_requirements_and_effects_and_for_aiding_the_integration_of_societal_goals 28. Harms, L., Durand, A., Hoogendoorn-Lanser, S., Zijlstra, T.: Exploring Mobility-as-a-Service (2018). https://maas-alliance.eu/wp-content/uploads/2018/11/MaaS-brochure-ENG 29. Beirão, G., Sarsfield Cabral, J.A.: Understanding attitudes towards public transport and private car: a qualitative study. Transp. Policy (Oxf) 14(6), 478–489 (2007). https://doi.org/10.1016/ J.TRANPOL.2007.04.009 30. Jakob, M., Hrncir, J., Oliva, L., Ronzano, F., Zilecky, P., Finnegan, J.: Personalized fully multimodal journey planner. Front. Artif. Intell. Appl. 263, 1225–1226 (2014). https://doi. org/10.3233/978-1-61499-419-0-1225 31. Esztergár-Kiss, D.: Framework of Aspects for the Evaluation of Multimodal Journey Planners. Sustainability 2019 11(18), 4960 (2019). https://doi.org/10.3390/SU11184960 32. The role of micro-mobility in MaaS: First-hand insights from TIER Mobility. https:// www.intelligenttransport.com/transport-articles/128716/micro-mobility-maas-tier-mob ility/. Accessed 26 Jan 2023 33. MAAS in Helsinki: a precursor to a new urban mobility? https://blog.padam-mobility.com/ en/2019/08/01/the-maas-in-helsinki-the-forerunner-of-a-new-urban-mobility/. Accessed 27 Mar 2022 34. Parangonnage international du CEREMA, MaaS in Europe: Lessons from the Helsinki, Vienna and Hanover experiments (2019) 35. About Whim - MaaS Global. https://whimapp.com/about-whim/. Accessed 22 Jun 2022 36. Citymapper: All Your Transport - Apps on Google Play. https://play.google.com/store/apps/ details?id=com.citymapper.app.release&hl=en&gl=US. Accessed 08 Nov 2022

Possibilities of Queuing System at Postal Operators Mladenka Blagojevi´c1(B) , Dragana Šarac2 , Amel Kosovac3 , and Ermin Muharemovi´c3 1 Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Beograd, Serbia

[email protected]

2 Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia 3 Faculty of Traffic and Communications, University of Sarajevo, 71000 Sarajevo,

Bosnia and Herzegovina

Abstract. The postal operators are often faced with the problem of long queues. Customers expect fast and efficient service and operators must meet their requirements. This paper describes the use of various systems for queue organization and informationas a toolsfor optimizing the queuing system at the selected postal operator with the aim of reducing queues and increasing the number of served customers. The number of postal service customers who support the application of systems for queue organization and information was investigated, as well as the customers who support the application of these systems in combination with mobile applications. In the research, several simulations were performedin the MATLAB software package. The goal is to reduce the waiting time of customers by using mobile applications. Keywords: Postal operator · Queuing system · Mobile applications

1 Introduction The theory of mass service, and therefore queuing systems, are the most suitable models for studying the characteristics of traffic systems, as stated in the paper [1]. Queuing analysis (also known as queuing theory or mass service theory) appeared in the first decade of the twentieth century thanks to the Danish mathematician A. K. Erlang. The goal of queuing theory is often to optimize the number of service lines so customers do not happen unnecessarily to queues or leaving the system because customers can prefer to leave the system rather than wait in the queue [2]. Queuing systems represent systems that serve customers’ needs and requirements that come into the system just for that purpose. The queuing system represents all the elements that come between the arrival of the customer to the system and its departure from the system [2]. The queuing theory has been analyzed and discussed in numerous papers, and only some of them are [3–7]. The systems for queue organization and information aresystems for electronic control of queues and providing information to users and workers in counter halls. The nature of the systems comes from the nature of the mass service system (queuing system). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 739–745, 2023. https://doi.org/10.1007/978-3-031-31066-9_86

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Represent a technical solution for long queues in waiting rooms and provides clients and employees with a work atmosphere without crowding, stress. These systems represent, as well as, a highly technologically organized way of doing work with an even distribution of work among workers. The systemsmake it possible to reduce crowding and stress in waiting rooms while providing information to users, and additional software modules and services (SMS notifications) have been developed. Usually, the elementary parts of the systems for queue organization and informationare the user desk/terminal (intended for issuing serial numbers to clients, as well as providing information to clients with the possibility of printing parts of information material), touch screen, counter terminal, management console, central display, central computer. In this paper, research was carried out on the number of postal service clients who support the application of thesystems for queue organization and information as a queuing system, as well as how many clients support the application of these systems in combination with mobile applications. The paper presents an upgrade of the paper [8]. In contrast to paper [8], the authors in this paper observed the possibilities of applying various systems for queue organization and information in the year 2022 at the postal operator, not only one, on a modified sample and with an increased number of simulations. They limited research only to research on reduction of waiting time.The application of the systems for queue organization and informationincrease the quality of service in the sense that clients do not have to wait for service in lines, but can come at the time of their service, which is defined on the previously drawn ticket. Additionally, by using mobile applications, it is possible to reserve a virtual number in a postal network unit, as well as get an estimated waiting time for service without first drawing a ticket. If there is another unit of the postal network near the client, it is possible to compare the waiting time in one and the other and, based on that, make a decision as to which is better to go to. In the research, several simulations were performed in which waiting times in queues were compared with and without the use of mobile applications. The goal is to reduce the waiting time by using mobile applications. The simulations were performed in the MATLAB software package.

2 The Research Problem The queues for which the systems for queue organization and informationare used usually are formed in two ways: • A common queue is formed, • Independent queues are formed where users choose the first free counter, and if there is none, then a shorter queue is chosen [9]. In the research that follows, the one public postal operator was observed. The simulation of one and the other mentioned case of the formation of waiting lines was carried out, where the generation of users is defined by an exponential distribution for the reason that the occurrence of users cannot be predicted. The average user arrival time is 120s, the average service time is 180s and it is also defined by an exponential distribution because the service time is not constant. Working hours of 8 h are simulated. The simulation results are shown in Table 1.

Possibilities of Queuing System at Postal Operators

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Table 1. Simulation results Queue type

Common queue

Independent queues

Number of served users

250

213

Utilization of the counter

95%

87%

Based on the results of the simulation, we conclude that the number of users served, as well as the percentage of utilization of counter, is higher in the case of common queue. Analyzing the postal network units, it was concluded that the units located in larger cities understand the importance and advantage of common queues. However, those units that are located in smaller cities have not yet seen this importance. If the postal operator wants to increase the number of served users and reduce the service time, which results in more satisfied users, he should definitely pay attention to the way queues are formed. 2.1 Acceptance of the Systems for Queue Organization and Information The paper presents research on how many users support the use of various systems for queue organization and information in combination with mobile applications. The survey was conducted in two cities, one big and one a small city. Active users of postal services were surveyed during September 2022. A two hundred respondents were surveyed. The age structure of the participants in the survey is from 20 to 75 years old. The younger age structure was more represented in observed bigger city. The results of the first part of conducted research showed that there are different interests of users for the introduction of the new systemsfor queue organization and information. The introduction of a new systems in big city would be supported by 67% of the total number of respondents, while in small city the introduction of the systems would be supported by 42% of respondents. The second part of survey shows that as many as 80% of surveyed users would use mobile applications and systems for queue organization and information. This results in the possibility of increasing the number of users on the one hand, and on the other hand reducing congestion and achieving a uniform distribution. Using the systems for queue organization and information, users receive information on the estimation of the time required for their service. Therefore, users, knowing when they will be served, would have the possibility to leave the postal network unit and arrive at the time scheduled for their service. In this way, crowds at the post office would be reduced, and the number of users served would be maintained. As a benefit of this type of service, we should expect an increased number of new users thanks to less crowds. Thus, the number of users waiting for service would be almost uniform throughout the day. In order to confirm the importance of the proposed systems, an online survey was conducted on how many users would give up service at the post office if the ticket, on which they receive a number and the average waiting time for service, said that they would wait 15–20 min. The results of the research show that 48% of users would give up and 52% would stay in line. In this way, users would feel more “free” because they would not have to wait in line if they have other occupations and, of course, they would be

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more satisfied with the implementation of the new system. This could affect the increase in the number of users due to the aforementioned freer approach to waiting for service.

3 Results of Application of systems for Queue Organization and Information and Mobile Applicationsat Postal Operator The queue organization and information systemsenable the generation of a number for each new user and the formation of a queue in accordance with the arrival of the user. In addition, by using mobile applications, users are enabled to withdraw a virtual number based on which they receive information about the time of arrival at the post office in order to avoid long waits. In the example, a system of N = 50 users is observed, where there are Nc = 3 counters in the post office. The percentage of users using mobile applications was changed in the range from 10% to 50% with a step of 10% of the total number of users. In order to compare thequeue organization and information systems and the same systems with the use of the application, the average waiting time for service was calculated separately for the following two cases: case 1. Average waiting time when 10%, 20%, 30% and 40% of the total number of users use the application, case 2. The average waiting time when those same users would not use the application. The average waiting time, with and without the mobile application, of the total number of users N is determined in the following example. All the obtained results point to the advantages of using the mobile application, which can be seen through the average waiting time, which is 1.15% to 34.40% shorter in the case of the application of the mobile application. The number of users using the application is changed from 10%–50% of the total number with a step of 10%. The serial numbers of users using the application are randomly selected from 1 to N. The average waiting time of users when they are not using the application is calculated using the following equation: Twnapl =

N  i=1

 Ts(i) ∗ ceil

 1 Snu(i) − 1 ∗ Nc N

(1)

where: Ts- service time considered as a randomly chosen value (random) in the range of 2–5 min, different for each user. Snu- serial number of the user. N - total number of users. Nc– number of counters.

Possibilities of Queuing System at Postal Operators

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The average waiting time of users in the case when they use the application is calculated using the following equation: Twapl =

Npa 

Twap(i) ∗

i=1

  N −Npa 1 1 Snu(i) − 1 + ∗ Ts(i) ∗ ceil Npa Nc N − Npa

(2)

i=1

where Twap(i) - randomly selected waiting time of user i in the case when the application is used. This time is a randomly selected number in the range of 2–5 min, different for each user. It is reasonable to assume that users, although using the application, arrive a few minutes before being served. IQSS will estimate the time it takes for the Nth user to come to the line for service, but must take some margin in the estimation so that it does not happen that the user arrives at the post office, and his number has already been selected. Npa - the total number of users who would potentially use the application. The mean waiting times for the case when 10%, 20%, 30%, 40% and 50% of users use the application are presented in Tables 2, 3, 4, 5 and 6, respectively. Also, the average waiting time is given in the tables in case when users would not use the application. Mean waiting times were calculated for five replicates to provide different (randomly chosen) sequence numbers of users (not) using the application. The tables also present the reduction in waiting time expressed in percentages, which is obtained by the following equation: Reductionofwaitingtime =

Twnapl − Twapl ∗ 100% Twnapl

(3)

where: Twnapl - average waiting time without application. Twapl - average waiting time with application deployment. Table 2. Average waiting time when 10% of users use the application Simulation number

1

2

Average waiting time with application [min]

10.18

11.15

Average waiting time without application [min]

10.95 7.03

Reduction of waiting time [%]

3

4

5

9.54

10.54

11.35

11.28

10.52

11.51

11.56

1.15

9.31

8.42

1.82

744

M. Blagojevi´c et al. Table 3. Average waiting time when 20% of users use the application

Simulation number

1

2

3

4

5

Average waiting time with application [min]

10.54

10.54

11.17

9.72

10.01

Average waiting time without application [min]

12.46

10.92

11.74

11.02

11.90

Reduction of waiting time [%]

15.41

3.48

4.85

11.79

15.88

Table 4. Average waiting time when 30% of users use the application Simulation number Average waiting time with application [min]

1

2

3

4

5

8.41

8.83

8.50

8.68

8.11

Average waiting time without application [min]

10.95

10.82

10.68

11.47

10.79

Reduction of waiting time [%]

23.19

18.39

20.41

24.32

24.83

Table 5. Average waiting time when 40% of users use the application Simulation number Average waiting time with application [min]

1

2

3

4

5

8.47

8.54

7.54

8.71

9.12

Average waiting time without application [min]

11.75

10.72

11.31

11.74

11.54

Reduction of waiting time [%]

27.91

20.33

33.33

25.81

20.97

Table 6. Average waiting time when 50% of users use the application Simulation number Average waiting time with application [min]

1

2

3

4

5

8.41

8.74

7.76

8.42

9.25

Average waiting time without application [min]

11.54

10.96

11.83

11.84

11.83

Reduction of waiting time [%]

27.12

20.25

34.40

28.88

21.81

4 Conclusion Based on the results presented in the paper, it can be concluded that the application of the queue organization and information systemscan influence the increase in the number of users, user satisfaction which leads to a reduction in service time. However, even in this case, it is not possible to control the arrival of users at the post office. Using a mobile application, thanks to which users would have insight into the current number of users waiting in line, further increases the advantage of using thequeue organization and information systems. Through the work, it was shown that the application of the systems for queue organization and informationand mobile applications reduces the

Possibilities of Queuing System at Postal Operators

745

average waiting time in the queue. So, for example, if 50% of users used the application, the average waiting time would decrease by 20%–34% compared to the average waiting time without applying the application, which confirms the justification of introducing the queue organization and information systemsas a mobile application into exploitation.

References 1. Begovi´c, M., Šari´c, S.: Sustavskipristupmodeliranju s pomo´cupodvorbenihmodela. Promet 3(6), 311–316 (1991) ˇ 2. Dutková, S., Achimský, K., Hoštáková, D.: Simulation of queuing system of post office. In: Transportation Research Procedia, vol. 40, pp. 1037–1044 (2019).https://doi.org/10.1016/j. trpro.2019.07.145 3. Xiao, H. Zhang, G.: The queuing theory application in bank service optimization. In: Proceedings: 2010 International Conference on Logistics Systems and Intelligent Management (ICLSIM), pp. 1097–1100 (2010). https://doi.org/10.1109/ICLSIM.2010.5461127 4. Yaduvanshi, D., Sharma, A., More, P.: Application of queuing theory to optimize waiting-time in hospital operations. Oper. Supply Chain Manage. Int. J. 12(3), 165–174 (2019) 5. Afolalu, S.A., Ikumapayi, O.M., Abdulkareem, A., Emetere, M.E., Adejumo, O.: A short review on queuing theory as a deterministic tool in sustainable telecommunication system. Materials Today: Proceedings, vol. 44, Part 1, pp. 2884–2888 (2021). https://doi.org/10.1016/ j.matpr.2021.01.092 6. Afolalu, S.A., Babaremu, K.O., Ongbali, S.O., Abioye, A.A., Abdulkareem, A., Adejuyigbe, S.B.: Overview impact of application of queuing theory model on productivity performance in a banking sector. J. Phys: Conf. Ser. 1378(3), 1–9 (2019). https://doi.org/10.1088/1742-6596/ 1378/3/032033 ˇ 7. Medi´c, S., Stojakovi´c, N., Capko, D., Durakovi´c, N., Grbi´c, T.: Mathematical model of queue size in a postal network unit with variable number of servers. IEEE 17th International Symposium on Intelligent Systems and Informatics (SISY), pp. 000127–000132 (2019). https://doi. org/10.1109/SISY47553.2019.9111598 ˇ c, A., Blagojevi´c, M., Popovi´c, Ð: Mogu´cnosti primene IQOS sistema i mobilnih 8. Musi´c, J., Cupi´ aplikacija u Pošti Srbije, VI Medunarodni simpozijum transporta i komunikacija Novi Horizonti 2017. Univerzitet u Istoˇcnom Sarajevu, Saobra´cajni fakultet Doboj (2017) 9. Radenkovi´c, B., Stanojevi´c, M., Markovi´c, A.: Raˇcunarskasimulacija, Saobra´cajnifakultet, Beograd (2004)

Author Index

A Abazovi´c, Ensar 596 Alagi´c, Ismar 418 Alma, Žiga 233 Alrefaee, Mohammad Adnan Diab Anti´c, Aco 78 Avdagi´c-Golub, Elma 639, 659

´ Cubela, Diana 69 Curcio, Maria 54

516

B Bagdasaryan, Armen 702 Bajri´c, Hadis 396 Banjanovi´c-Mehmedovi´c, Lejla 461 Beganovi´c, Omer 283 Begic-Hajdarevic, Derzija 241, 450 Bekteševi´c, Jasmin 427, 434, 442 Belšak, Rok 19, 156 Berardi, Valentino Paolo 329 Berus, Lucijano 19, 62, 156 Bevz, Oleh 131 ´ Mirha 389, 585 Biˇco Car, Blagojevi´c, Mladenka 739 Blanuša, Vladimir 260 Bogorin-Predescu, Adrian 411 Boskovic, Bojana 646 Brajlih, Tomaž 156 Brezoˇcnik, Lucija 486 Brezoˇcnik, Miran 156 Buljan, Stipo 149 C Cabaravdic, Malik 213 Cattani, Piercarlo 504, 524, 562 ˇ Cauševi´ c, Samir 696 Cekic, Ahmet 241, 450 Celenta, Giampiero 365, 373, 577 Cheredarchuk, Natalia 182 ˇ cak, Mirjana 534 Ciˇ Cobo, Mehmed 213 Cohodar Husic, Maida 450

D Daši´c, Predrag 112 De Leone, Renato 486 De Simone, Marco Claudio 356, 365, 373 Dedi´c, Luka 609 Destovi´c, Fatih 434 Dimitrov, Lubomir 170, 182 Dimovski, Tome 470 Djukanovic, Milena 276 Doicin, Cristian Vasile 27, 381 - c, Luka 78 Ðordevi´ Dorozhka, Tetiana N. 338 Dragomir, Mihai 550 Dudi´c, Branislav 139 Ðuki´c, Himzo 123 - Mi´ca 78 Ðurdev, Džaferovi´c, Ejub 291 Džakmi´c, Šejla 516 Džananovi´c, Ajdin 667, 683 E Eitler, Sandra 616 Eljazovi´c, Maida 722 Ezgeta, Drago 667, 696 F Faki´c, Belma 69, 283 Ficko, Mirko 62, 156, 450 Fišer, Zrinka 542 Franco, Carmela 37 G Genel, Ömer Ekim 321 Gomes, Eduarda 149 Gotlih, Janez 19, 62, 156 Grujic, Ivan 646

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 I. Karabegovic et al. (Eds.): NT 2023, LNNS 687, pp. 747–749, 2023. https://doi.org/10.1007/978-3-031-31066-9

748

Guercio, Vincenzo 504, 524 Gusan, Vasile 27 H Hadžali´c, Mustafa 283 Hadžiabdi´c, Vahidin 427, 434, 442 Hadžistevi´c, Miodrag 260 Hajdar, Amir 497, 596 Halaˇc, Almin 291 Halilovi´c, Emir 396 Hernavs, Jernej 62 Holofieieva, Maryna 298, 305 Hozdi´c, Elvis 201 Hristoski, Ilija 470 Hruska, Matej 45 Hupfer, Christoph 628, 712 Husak, Ermin 3 Husakovi´c, Anel 461 Husi´c, Lejla 461 I Ionescu, Nicolae 27, 381 Ismir, Behadarevi´c 233 Isola, Giuseppe 329 Ivanov, Viktor 170, 182 Ivanova, Svitlana 170, 182 J Ješi´c, Dušan 139 Jevremovi´c, Vladeta 338 Josip, Kaˇcmarˇcik 233 Jovanovic, Mihailo 276 Jurˇcevi´c, Marinko 729 Jurkovi´c, Zoran 201 K Kalampakas, Antonios 702 Kalinina, Tetiana V. 338 Karabegovi´c, Edina 3 Karabegovi´c, Isak 3, 389 Karakatiˇc, Sašo 486 Karner, Timi 19, 62, 156 Katerynych, Stanislav 131 Khliebnikov, Anton V. 338 Klancnik, Simon 450 Klanˇcnik, Simon 62 Klimov, Sergii 298, 305 Kochmanski, Pawel 45 Konjicija, Samim 497

Author Index

Konoplov, Anatolii 182 Kopei, Bogdan 86 Kopei, Ihor 86 Kopei, Volodymyr 86, 98 Kos, Goran 609 Kosovac, Amel 639, 659, 675, 739 Kostiuk, Olha 221 Kovaˇc, Pavel 139 Kuk, Andrii 221 Kusyi, Yaroslav 98, 221 L La Regina, Rosario 37, 54, 321, 329, 348 Lemeš, Samir 283 Lenza, Tony Luigi Leopoldo 365 Lesyk, Dmytro 45 Levynskyi, Oleksandr 305 Lindov, Osman 621 Liu, Yafei 524 ˙Ipek 348 Lök, Sefika ¸ Lorusso, Angelo 577 Luki´c, Dejan 78 Lungu, Florin-Alexandru 193 Lysenko, Oleksandr B. 338 Lysenko, Oleksandr 112 M Mahmi´c, Mehmed 3 Malgaca, Levent 348 Mandžuka, Bia 729 Mandžuka, Sadko 609 Maric, Anita 276 Maši´c, Adnan 427, 434, 442 Medi´c, Adisa 675 Medin, Andrea 276 Mehanovi´c, Mustafa 696 Mehiˇci´c, Haris 675 Mehulji´c, Midhat 427, 434, 442 Melin, Kristian 396 Memi´c, Belma 639, 659 Metovi´c, Sadjit 442 Miloševi´c, Mijodrag 78 Mordyuk, Bohdan 45 Movrin, Dejan 260 Muhamedagic, Kenan 241 Muharemovi´c, Ermin 639, 659, 722, 739 Muminovi´c, Adis J. 249 Muminovi´c, Branka 283 Murali, Supraajha 557

Author Index

Mustafa, Mehanovi´c 690 Mykhailiuk, Vasyl 86 N Nalli, Giacomo 486 Nedim, Kamenjaševi´c 690 Neimarlija, Ermin 396 Novakovi´c, Borivoj 78 Noži´c, Mirna 123 O Olefir, Olena 170 Olteanu, Constantin Dorin 381 Omerhodži´c, Adnan 621, 683 Onysko, Oleh 86, 98, 221

749

Shepelenko, Ihor 131 Shramenko, Natalya 628, 712 Škorput, Pero 652 Softi´c, Almira 269 Solohub, Bohdan 221 Solovuch, Andrey 131 Solovykh, Evhen 131 Stanovska, Iraida 298 Stanovskyi, Oleksandr 305 Stojanovic, Nadica 646 Štrbac, Branko 260 Stupar, Savo 389, 585 Su´ceska, Suad 602 Šuli´c, Muharem 675 Šunji´c, Darko 149

P Pal, Snehashis 156 Palazhchenko, Yevhen 478 Pappalardo, Carmine Maria 37, 54, 321, 329, 348 Paravli´c, Armin 596 Pavlyshko, Andrii 298 Persak, Tadej 450 Peršak, Tadej 62 Pervan, Nedim 249, 427 Pituley, Lolita 98 Podgorelec, Vili 486 Popil, Oleg 112 Potoˇcnik, David 62 Powalka, Bartosz 45

T Taras, Iryna 98 Tari´c, Mirfad 139 Tatarevi´c, Adnan 683 Tertereanu, Petric˘a 550 Tetiana, Kalinina 112 Tiˇc, Vito 571 Tiro, Dragi 313 T, ît, u, Aurel Mihail 27, 193, 381, 411, 550 T, ît, u, Stefan 411 Tonkonogyi, Volodymyr 298, 305

R Ramdedovi´c, Amel 516 Ramljak, Amina 241 Ranisavljev, Miloš 260

V Val, Sonia 486 Varda, Kenan 269, 283 Veeraraghavan, Venkatakrishnan 557 Veneziano, Salvio 356, 373 Vidovi´c, Krešimir 609, 652, 729 Villecco, Francesco 504, 524, 562 Viswanathan, Varsha 557 - 516 Viteški´c, Nada

S Saburov, Mansoor 702 Saletovi´c, Vedad 249 Šarac, Dragana 739 Sarajli´c, Mirzet 667, 683, 690 Sarajli´c, Nermin 461 Šari´c, Isad 249 Savkovi´c, Borislav 139 Schodl, Reinhold 616 Serdarevi´c-Kadi´c, Sabina 269 Šesti´c, Munira 389, 585 Shendryk, Sergii 478 Shendryk, Vira 478

U Ungureanu, Andreea Maria 193 Urum, Galyna 170

W Wang, Tonghao

504

Z Zagorulko, Iryna 112 Zaimovi´c-Uzunovi´c, Nermina Zeba, Gordana 534 Žiga, Alma 213

269