Springer Handbook of Additive Manufacturing (Springer Handbooks) [1st ed. 2023] 3031207513, 9783031207518

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Springer

Handbook

oƒ

Additive Manufacturing Eujin Pei Editor-in-Chief Alain Bernard Dongdong Gu Christoph Klahn Mario Monzón Maren Petersen Tao Sun Editors

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Springer Handbooks

Springer Handbooks maintain the highest standards of references in key areas of the physical and applied sciences for practitioners in industry and academia, as well as graduate students. Designed to be useful and readable desk reference books, but also prepared in various electronic formats, these titles allow fast yet comprehensive review and easy retrieval of essential reliable key information. Springer Handbooks cover methods, general principles, functional relationships and fundamental data and review established applications. All Springer Handbooks are edited and prepared with great care by editors committed to harmonizing the content. All chapters are written by international experts in their field. Indexed by SCOPUS. The books of the series are submitted for indexing to Web of Science.

Eujin Pei • Alain Bernard • Dongdong Gu • Christoph Klahn • Mario Monzo´n • Maren Petersen • Tao Sun Editors

Springer Handbook of Additive Manufacturing With 617 Figures and 136 Tables

Editors Eujin Pei College of Engineering, Design and Physical Sciences Brunel University London Uxbridge, UK

Alain Bernard Lab. for Digital Sciences of Nantes École Centrale de Nantes NANTES CEDEX 3, France

Dongdong Gu CMST Nanjing University of Aeronautics and Astronautics Nanjing, China

Christoph Klahn Karlsruhe Institut of Technology KIT Karlsruhe, Germany

Mario Monzón Dept. Mechanical Engineering University of Las Palmas de Gran Canaria Las Palmas de Gran Canaria, Las Palmas, Spain

Maren Petersen University of Bremen Bremen, Germany

Tao Sun Materials Science & Engineering University of Virginia Charlottesville, VA, USA

ISSN 2522-8692 ISSN 2522-8706 (electronic) Springer Handbooks ISBN 978-3-031-20751-8 ISBN 978-3-031-20752-5 (eBook) https://doi.org/10.1007/978-3-031-20752-5 © 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 Paper in this product is recyclable.

Foreword by R. Ian Campbell

Having worked as a researcher in Additive Manufacturing (AM) for the best part of three decades, I have seen many books on AM being launched to varying degrees of success. Some have been written from an educational viewpoint, others have been targeted at industry, while some have focused on specific AM technologies or materials. This book is called a handbook because it is intended to be a trusted companion for anyone who wishes to make effective use of AM. Each section covers a particular aspect of AM and the seven sections combine to provide a truly comprehensive coverage of the entire AM ecosystem. The Introduction covers economic, logistical, and managerial aspects of using AM. Whether the reader is studying AM in college or seeking to adopt AM in an industrial environment, all the required information and knowledge they need is provided in a logical order. Whilst the section clearly presents the substantial benefits of AM, it also covers the more problematic topics such as the impact of AM on intellectual property rights or the limitations of the technology. It finishes with a forward-looking glimpse into how AM is likely to impact manufacturing in the future. As a designer myself, I am particularly pleased to see the in-depth treatment given to design and product definition in the second section. Most AM builds begin with a three-dimensional computer model of the part(s) that need to be realized. Without a high-quality definition of the design, the results of the AM build are likely to be flawed. More fundamentally, without an innovative product design, the strengths (and significant cost) of AM are likely to be wasted. This section leads the reader through the various steps that need to be incorporated into a “design for AM” strategy. The design innovation that is required to make AM economically viable must often be supported by advanced design software such as generative design and topology optimization. Both of these are covered in the latter part of this section. The next section is entitled “Processes Section” and explains the operation of all the main types of AM systems and the secondary processes associated with them. This clearly shows the reader that the AM build itself is only one part of the full manufacturing process. It must be accompanied by quality control, monitoring, post-processing, testing, and part qualification. Sometimes, these secondary processes can take longer than the AM build and can add significant expense. However, without them AM would have remained a prototyping technology and would never have broken into the final part manufacture market. The Materials section covers the full range of materials that are currently being used in AM. Polymers have been used for many years and metal AM is being used increasingly in the aerospace, automotive, and medical markets. As well as covering the major classes of metals used for AM, this section also addresses the increasingly important areas of ceramics and composites. AM has proved itself to be very flexible in the range of materials it can use and has even led to the development of new materials, created specifically for AM processes. Any manufacturing process is only as capable as the people who are using it. Without proper education and training of the workforce, AM can turn out to be an expensive waste of time. Everyone involved in the AM ecosystem, from design engineer to machine operator, needs to be fully empowered to achieve the most effective outcome. In recognition of the criticality of

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this topic, the next section in the book covers some of the most important initiatives in AM education and training, both in Europe and the United States. The final section of the book presents AM applications and case studies. In doing so, it helps to put into context all the knowledge and information that has been provided in the preceding sections. Some lesser-known applications of AM have been covered, including cultural heritage, tissue engineering, and packaging. These give particularly valuable insight into the flexible nature of AM, which lends itself well to complex shapes and specialized materials. Alongside the more typical industrial applications, these will give the reader a true appreciation of the full range of uses to which AM can be put. The knowledge gained from this section, and indeed the whole book, will give the reader a high level of confidence that their own use of AM will be effective and worthwhile.

Professor R. Ian Campbell Emeritus Professor of Computer Aided Product Design School of Design and Creative Arts Loughborough University United Kingdom

Foreword by R. Ian Campbell

Foreword by Ian Gibson

Additive Manufacturing (AM) is coming of age. By this, I mean that the technology associated with AM has gone through a sustained period of growth and development. It can no longer be considered as just an interesting technology that has some cool features to it that can enable people to make fun parts. Since its beginning in the late 1980s, early 1990s, AM machines have found their way into more and more application domains. This has been through development of the original approach of combining material cross-sections together, layer-by-layer, into a full solid object with data taken from 3D solid CAD models. Such development has extended the technology in one or more of a variety of directions. Gradual (and in some cases, dramatic) improvements have been made in terms of the range of materials (and their corresponding properties), build speed, build dimensions, accuracy, resolution, reliability, usability and, ultimately, cost. It is “of age” because AM can now take its place alongside other mature manufacturing technologies to produce bigger, better, more beautiful products more efficiently and cheaper. I was first introduced to rapid prototyping (what is now more technically referred to as additive manufacturing and more commonly called 3D printing) in 1992, by one of my colleagues, Phill Dickens, when I was a young lecturer at Nottingham University in the UK. Along with some other colleagues, we formed the first UK rapid prototyping research group, organized the first European rapid prototyping conference, and purchased one of the first machines in the UK, an SLA250 from 3D Systems. This became the start of a lifelong obsession with the technology that has allowed me to observe its development at close quarters. What I now see is a time where industry is really interested in AM. This is not just the visionary early adopters, or those trying to take advantage of a disruptive technology to stay ahead of the curve. It is fair to say that nowadays manufacturers must seriously consider AM technology alongside all other manufacturing technologies to ensure they are staying relevant, agile and capable of meeting the needs of consumers. Over the last few years, we have experienced numerous disruptions to our everyday lives, the most notable of these being related to the COVID-19 virus. Regular supply chains have been interrupted, energy costs and the impact on the environment have forced us to improve efficiencies, often through greater use of automation and digitalization. AM has been part of this, enabling manufacturers to react quicker to changing demands, improve product quality and enable easier customization and personalization. Industry 4.0 is more and more an actual thing that most manufacturers not only aspire to but apply on a regular basis. AM is a digitally driven technology that in many cases leads the way for Industry 4.0. But, when should a manufacturer switch over to AM? What machines should they invest in and how can they make the best of these machines to suit their needs? What do they still need to know before they commit? How do they adapt their workforce to suit these changes? All engineers are familiar with the concepts of momentum and inertia. It is always easier to keep a body moving along the same trajectory. Changing that trajectory requires more energy, but if you’re moving towards an obstacle, such energy is necessary to keep it from crashing. However, if not enough energy is applied at the right time or in the right way, problems can still occur. Investment in new technology is much like steering a ship around icebergs. At what time vii

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should I invest my resources to steer around these obstacles and keep going towards my final destination? The Springer Handbook of Additive Manufacturing aims to inform companies and help them make the right decisions around AM. It starts by covering how the technology has developed over the years and how it has arrived at its current state. The obvious uses and benefits of AM are now well-established with accepted standards. This first section acts as a baseline for what should be known about AM in general. What then follows are sections on design, processes and materials. Designers need to add the capabilities of AM to their repertoire so that they can create products to suit these advantages, for example through the application of generative design or topology optimization methods. Even if a product has not been designed to make use of these methods, AM can still be the most cost-effective way of producing a product by virtue of its geometry, size, material or production volume. Engineers therefore need to know how AM fits into a standard production chain and what to expect in terms of the mechanical and other properties of resulting parts. The book concludes with a section on education and training around AM followed by a series of use cases designed to demonstrate the range and scope of AM, paving the way to future uses. Readers of this handbook will likely already know something about AM and are interested to learn more. They will be wanting to know how AM is affecting their lives and how it may develop in the future. They may be considering learning how to use, or even purchasing an AM machine. If that describes you, then this book would be a good starting point on a long and fascinating journey into the future of manufacturing.

Professor Ian Gibson Faculty of Engineering Technology University of Twente The Netherlands

Foreword by Ian Gibson

Foreword by Terry Wohlers

Additive Manufacturing (AM) is experiencing strong growth. Countless organizations in the AM industry are investing in a wide range of production applications, especially for short-run production and custom product manufacturing. As equipment ages across many industrial sectors, including military and defense, it has become challenging to find or manufacture replacement parts. AM is being used increasingly to get machinery back into service. One of the greatest successes in AM is an increase in the number of standards being developed and published. We are seeing increasing involvement globally within the AM community in standards development activities led by ASTM International and ISO, along with others. This is helping with the adoption of AM worldwide. The industry is also seeing a strong focus on postprocessing. Part 1 Section 10 provides an extensive overview of AM standards. One of the most interesting advancements is with tools and methods of design for additive manufacturing (DfAM). In part, they focus on approaches to optimize the strength-to-weight ratio of a design. Also, they help reduce expensive and time-consuming support material, especially for metal AM. Using DfAM to improve product performance is key. Aerospace, healthcare, and other industrial sectors have benefited greatly from DfAM. Part 2 provides information about design, including guidelines and how to identify suitable parts that can leverage the benefits of using AM. As AM matures, an area of interest is tracking and optimizing the end-to-end workflow using cloud-based manufacturing execution systems (MES). For metal AM, organizations are investing further into process monitoring. For AM processes that use both polymers and metals, expect to see further development in build speed and automated post-processing, which lowers the cost of parts. Part 3 includes two sections on post-processing methods, along with quality control and the automation of the process workflow. As sustainability becomes an increasingly important factor in the next few years, we foresee AM playing a critical role in supporting a global shift towards greener and cleaner methods of manufacturing. This trend will help support economic and environmental goals set by governments around the world. Methods of AM will be driven by market pull, such as applications of net-zero carbon, particularly in transportation and heavy industry. AM will become integrated into larger manufacturing ecosystems and will drive the creation of smart factories worldwide. Part 4 discusses different materials available for AM that could have a profound impact on the sustainability of parts and their use. This is followed by Part 5 that discusses aspects of postprocessing, testing, and inspection of AM parts, as well as micro structure and property characterization, heat treatment and and quality control. Managing businesses during a pandemic came with a learning curve for companies. Many became more agile with their workforce and other infrastructure as they waded through unprecedented times. Companies are beginning to explore emerging technologies that serve as a companion to AM as the benefits of convergence become clear. Diversification in technologies, as well as team members and geographic location, has led to unexpected opportunities, such as filling supply chain gaps. Part 6 provides a review of training and education programmes taking place in the USA and in Europe. Finally, Part 7 presents a diverse and interesting range of AM applications and case studies. ix

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It is hoped that readers of this handbook will increase their understanding of AM and how it will impact the future of product development and manufacturing worldwide.

Terry Wohlers Wohlers Associates, powered by ASTM International

Foreword by Terry Wohlers

Preface

Reading this preface would mean that you have selected this handbook either as your first foray into the world of Additive Manufacturing, or that you are already knowledgeable in this field but still wanting to know more about what the technology can provide. 1997 was the year that I had my first product being “rapid prototyped” – a term used to describe the quick fabrication of a physical part using three-dimensional computer-aided design (3D CAD) data. In the early 2000s, I found myself working in the industry where these physical models were being more widely accepted and recognized as a useful tool that could help communicate the design intent and to explain the mechanics of an engineering principle. In those days, parts made from the additive manufacturing process were not sufficiently robust to be used as end-use components and they were mostly limited for visual studies. I then made a career change to work in academia, where I taught (and still continue to teach) subjects including the Product Design Process, Computer-Aided Design, and Rapid Prototyping. At that time, learning resources, handbooks, and guides were less common and information was often scattered. Moving forward from a 14.4 kbps dial-up modem to today’s broadband and wireless 5G world, we see a plethora of online resources, videos, and user forums, and we are in the midst of facing information overload. While a much wider spectrum of additive, subtractive, hybrid, and forming processes are now being developed, along with novel materials and more efficient post-processing techniques, we face an uncertain world with energy security and long-term concerns over sustainable production. The holy grail of getting parts “First-time-right” is essential, and it is thus important to apply the correct knowledge to become better designers and engineers. Writing this book with 7 chapters and 58 sections took us 4 years since it was initially conceived. My team of editors have compiled only the most essential topics, covering an Introduction of Additive Manufacturing; Design and Data; Processes; Post-processing, Testing and Inspection; Materials; Education and Training; and Applications and Case Study Examples. In spite of the best of our efforts, there are bound to be more and newer information in this ever-expanding field. Still, it is hoped that this Springer Handbook of Additive Manufacturing will be a valuable resource for both students and educators, as well as those who are new to Additive Manufacturing. 15 November 2023

Dr. Eujin Pei

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Acknowledgments

For my wife, Ying. For your love and inspiration. This book is dedicated to you. – Eujin Pei

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Contents

Part I

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

1

History of AM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Eujin Pei, Israt Rumana Kabir, and Bastian Leutenecker-Twelsiek

3

2

Economics of Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . Christoph Klahn, David Butler, and Eujin Pei

31

3

Business Model Innovation in Additive Manufacturing Equipment Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sudhir Rama Murthy, Jiashun Huang, and Chander Velu

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4

Implementation of Additive Manufacturing in Industry . . . . . . . . . . . . . Daniel Omidvarkarjan, Ralph Rosenbauer, Christoph Klahn, and Mirko Meboldt

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5

Supply Chain Management for Additive Manufacturing . . . . . . . . . . . . Zitouni Beidouri, Amal Naji, and Latifa Fadile

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6

Intellectual Property Rights at Crossroads: The Copyright and Patent Implications Relating to 3D Printing . . . . . . . . . . . . . . . . . . . . . . . . . . . Dinusha Mendis and Rosa Maria Ballardini

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7

Technical Regulations and Policies Affecting AM . . . . . . . . . . . . . . . . . . Filip Geerts and Vincenzo Belletti

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8

Benefits Using Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . Adriaan B. Spierings and Christoph Klahn

115

9

Opportunities and Limitations of Additive Manufacturing . . . . . . . . . . . Frank Alifui-Segbaya, Iñigo Flores Ituarte, Seymur Hasanov, Ankit Gupta, and Ismail Fidan

125

10

Standards for Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . David G. Hardacre and Eujin Pei

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11

ManuFUTURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Eberhard Bessey

163

Part II

Design and Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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12

Design Guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Christoph Klahn and Bastian Leutenecker-Twelsiek

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13

Identification of Suitable Parts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Christoph Klahn

199

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Contents

14

Modeling and Simulation for Additive Manufactured Parts . . . . . . . . . . Khalid Zarbane

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15

Production Process Chain from CAD to Part . . . . . . . . . . . . . . . . . . . . . Adriaan B. Spierings and Christoph Klahn

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16

Reverse Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Salvatore Gerbino and Massimo Martorelli

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Strategies and Generative Design Towards the Development of Innovative Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Massimo Martorelli and Antonio Gloria

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Topology Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Akihiro Takezawa

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Security Threats in AM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mark Yampolskiy and Jacob Gatlin

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Part III

Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Features, Limitations, Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dongdong Gu, Lixia Xi, Ruiqi Wang, and He Liu

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21

Material Extrusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Azadeh Haghighi

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Vat Photopolymerization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Henry Oliver Tenadooah Ware, Rihan Hai, and Cheng Sun

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Material Jetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Negar Gilani, Aleksandra Foerster, and Nesma T. Aboulkhair

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Powder Bed Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Srujana Rao Yarasi, Andrew R. Kitahara, Elizabeth A. Holm, and Anthony D. Rollett

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Sheet Lamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marwan Haddad, Karlie B. Nixon, and Sarah Wolff

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Hybrid Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. P. Karunakaran

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Binder Jetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Erica Lynn Stevens Erickson and Markus Chmielus

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28

Directed Energy Deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sarah Wolff

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29

Quality Control in L-PBF for Industrial Production by Means of Production-Integrated Measurement Technology . . . . . . . . . . Lukas Weiser, Marco Batschkowski, Niclas Eschner, T. Landgräber, F. Ohlsen, S. Seiz, and Gisela Lanza

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30

Real-Time Monitoring of AM Processes . . . . . . . . . . . . . . . . . . . . . . . . . Zhongshu Ren, Cang Zhao, Niranjan D. Parab, and Tao Sun

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31

Environmental Health and Safety I . . . . . . . . . . . . . . . . . . . . . . . . . . . . François Richard

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32

Environmental Health and Safety II . . . . . . . . . . . . . . . . . . . . . . . . . . . . Seymur Hasanov, Ankit Gupta, Frank Alifui-Segbaya, and Ismail Fidan

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Contents

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Environmental Health and Safety III . . . . . . . . . . . . . . . . . . . . . . . . . . . Kyungho Park and Woocheol Sung

Part IV

559

Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Polymers for Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . Mario Monzón and Rubén Paz

571

35

Thermoplastic Polymers and Polymer Composites Used in Selective Laser Sintering (SLS) Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Burçin Özbay Kisasöz and Ebubekir Koç

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36

Ceramics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marco Pelanconi, Giovanni Bianchi, Oscar Santoliquido, Francesco Camerota, Antonio Di Mauro, Alice Rosa, Simone Vitullo, Samuele Bottacin, and Alberto Ortona

597

37

Composites (Fiber-Reinforced Plastic Matrix Composites) . . . . . . . . . . . Ankit Gupta, Seymur Hasanov, Frank Alifui-Segbaya, and Ismail Fidan

627

38

Quality Control for Powder Bed Fusion Additive Manufacturing . . . . . Özgür Poyraz and Evren Yasa

639

39

Additive Manufacturing of Nickel Alloys . . . . . . . . . . . . . . . . . . . . . . . . Anagh Deshpande

655

40

Additive Manufacturing of Titanium and Alloys . . . . . . . . . . . . . . . . . . Mitun Das and Vamsi Krishna Balla

671

41

Powder Bed Fusion Additive Manufacturing of Stainless Steels . . . . . . . Evren Yasa and Özgür Poyraz

699

42

Additive Manufacturing of Aluminum Alloys . . . . . . . . . . . . . . . . . . . . . Ji Ma

713

Part V

Post-processing, Testing, and Inspection . . . . . . . . . . . . . . . . . . . .

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Microstructure and Property Characterization of AM Materials . . . . . . Anagh Deshpande

727

44

Heat Treatment of Additive Manufactured Metals . . . . . . . . . . . . . . . . . Mustafa Safa Yilmaz and Gökhan Özer

741

45

Corrosion Behaviour of Additive Manufactured Metals . . . . . . . . . . . . . Gökhan Özer and Mustafa Safa Yilmaz

751

46

Part and Process Qualification for Serial Production . . . . . . . . . . . . . . . Claus Emmelmann and Christian Daniel

777

47

Quality Control for Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . Yahya Al-Meslemi, Kevin Ferreira, Charyar Mehdi-Souzani, Anne-Françoise Obaton, Hichem Nouira, and Nabil Anwer

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Post-processing for Additive Manufactured Metal Parts: A Brief Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jonathan Smith and David Butler

49

Post-processing Methods for Additive Manufactured Parts . . . . . . . . . . Dimitris Mourtzis and Panagiotis Stavropoulos

821 833

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Contents

Part VI 50

51

52

53

Education and Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

855

EU Funded Projects for Qualification and Standards Requirements in Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Adelaide Almeida, Eurico Assunção, and Ana Beatriz Lopez

857

VET and Academic Training for Additive Manufacturing in Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maren Petersen and Christoph Leupold

867

Innovative Training to Support Adoption of Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Khalid Rafi, Alexander Liu, Paul Bates, Nima Shamsaei, and Mohsen Seifi

881

Review of Additive Manufacturing Program Offerings in the United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . John E. Barnes and Timothy W. Simpson

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Part VII

Applications and Case Study Examples . . . . . . . . . . . . . . . . . . . .

905

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Additive Manufacturing Applications and Case Study Examples . . . . . . Alain Bernard, Christoph Klahn, and Manuel Biedermann

907

55

Additive Manufacturing in Cultural Heritage Preservation and Product Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bingjian Liu, Fangjin Zhang, Xu Sun, and Adam Rushworth

923

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Tissue Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pedro Gil Frade Morouço

941

57

Additive Manufacturing Applications for Art and Culture . . . . . . . . . . . Olaf Diegel, Juan Schutte, and Simon Chan

953

58

Applications for Packaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Claude Barlier, Christophe Abel, and Jean-Loup Rennesson

963

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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About the Editors

Eujin Pei is a Reader in Additive Manufacturing at Brunel University London in the United Kingdom. He is the Associate Dean for the College of Engineering, Design and Physical Sciences, and Director for the BSc Product Design Engineering program. He is a Chartered Engineer (CEng), Chartered Environmentalist (CEnv), and Chartered Technological Product Designer (CTPD). His research focuses on Design for Additive Manufacturing, 4D Printing, and Sustainable Manufacturing. Dr. Eujin is the Editor-in-Chief for the Progress in Additive Manufacturing journal (SpringerNature). He is the Chairperson for the National Standards Committee for Additive Manufacturing at the British Standards Institute BSI/AMT/8 that publishes standards for Additive Manufacturing. He also chairs the International Organization for Standardization ISO/TC261/WG4 committee that develops global standards for Additive Manufacturing Data and Design and chairs ISO/TC261/JG67 for Functionally Graded Additive Manufacturing, resulting in a total of six international standards that have been published to date since his appointment in 2015. Dr. Eujin is a Fellow, Trustee, and Council Member of the Institution of Engineering Designers (FIED). He received the ASTM International Additive Manufacturing Award of Excellence in Education in 2021, and his work has been exhibited at the Cooper Hewitt Smithsonian Design Museum in New York. Industry partnerships, collaborative research, and joint research supervision are very welcomed.

Emeritus Professor Alain Bernard graduated in 1982, with a PhD achieved in 1989. He worked as Associate Professor from 1990 to 1996 at Centrale Paris. From 1996 to 2001, he was appointed as a Full Professor in CRAN, Nancy I, and led the “Integrated Design and Manufacturing” team. Since 2001, he worked as a Full Professor at Centrale Nantes and was Dean for Research from 2007 to 2012. He was a Researcher at LS2N Laboratory (UMR CNRS 6004) and former Head of the “Systems Engineering – Products-ProcessesPerformances” team. Prof. Bernard’s research topics include Knowledge Management (KM), Product Lifecycle Management (PLM), information system modelling, enterprise modelling, systems performance assessment, virtual engineering, and additive manufacturing. He has supervised more than 40 PhD students and published more than 150 papers in refereed international journals and books. Prof. Bernard has been the Vice President of France Additive (French xix

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About the Editors

Association on Additive Manufacturing) since 1993. He is Vice Chairman of WG5.1 of IFIP (Global Product Development for the whole product lifecycle) and Fellow Emeritus of CIRP (International Academy for Production Engineering). In 2018, he was elected as Fellow of the Academy of Technologies of France (Académie des technologies).

Dongdong Gu is a Full Professor of Nanjing University of Aeronautics and Astronautics (NUAA) and the Director of Jiangsu Provincial Engineering Research Center for Laser Additive Manufacturing of High-Performance Components. He was an Alexander von Humboldt Research Fellow at Fraunhofer ILT, Aachen, Germany from 2009 to 2011. His principal research interest is laser-based Additive Manufacturing of high-performance/multi-functional metallic components. He is the Senior Editor of the Journal of Laser Applications, Assistant Editor of the International Journal of Machine Tools and Manufacturing, Deputy Editor-in-Chief of CJME: Additive Manufacturing Frontiers, and serves as an Editorial Board Member of Additive Manufacturing, Virtual and Physical Prototyping, etc. He has published more than 200 papers on Additive Manufacturing in international peer reviewed journals, including one paper entitled “Material-structure-performance integrated laser-metal additive manufacturing” in Science. He has applied for more than 36 national patents. He has served as Co-chairman, Executive Chairman, Academic Committee Member, and Keynote/Invited Speaker in more than 40 academic conferences. He was granted the Fraunhofer-Bessel Research Award from the Alexander von Humboldt Foundation Germany (2019), the Mercator Fellow Award from the German Research Foundation (DFG) (2018), the Most Cited Chinese Researcher from the Elsevier (2020 and 2021), the National “Tenthousand Talents Program” (2018), the Cheung Kong Young Scholars Award from the Ministry of Education of China (2016), the Top-Notch Young Talents Program of China (2015), and the Excellent Young Scientists Fund from the National Nature Science Foundation of China (2013).

Christoph Klahn is a Professor of Additive Manufacturing (AM) in Process Engineering at Karlsruhe Institute of Technology KIT. He was the Head of Design for New Technologies at inspire AG, closely related to ETH Zürich, until 2021. His current research explores the opportunities of Additive Manufacturing in process engineering, as well as the implications of AM techniques on the development process of devices. In his interdisciplinary team, he explores the topics of design for AM, value creation and value identification, and the improvement of devices for process engineering by AM. He modifies AM processes and process chains to create novel material properties for functional integration and improved production processes. Prof. Klahn entered the world of Additive Manufacturing by designing the first additive manufactured lightweight aircraft bracket at Airbus Germany in 2008. He received his Doctorate in Engineering from Hamburg University of Technology in

About the Editors

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2015 for developing an Additive Manufactured, permeable tooling steel for pneumatic ejectors in injection molding tools. Prof. Klahn is the founder of the conference series Additive Manufacturing in Products and Applications AMPA. The triennial international scientific conference fosters the exchange among researchers and practitioners from industry and academia since 2017.

Mario Monzón is a Doctor in Industrial Engineering and Full Professor in the Mechanical Engineering Department of the University of Las Palmas de Gran Canaria (ULPGC). He is the Director of the research group for Integrated and Advanced Manufacturing. His main research fields cover polymer processing, Additive Manufacturing (AM), rapid tooling, natural fiber composites, biomaterials for Additive Manufacturing, and bio-fabrication. He is a member of ISO TC261 and CEN TC438 committees for the standardization of AM technologies, representing Spain. He is also the Convenor of the Joint Working Group JWG11 “Additive Manufacturing for Plastics” with participation of experts from ISO TC261 (AM), ISO TC61 (thermoplastics), and ASTM F42 (AM). He has been the Coordinator of the PhD program of Chemical, Mechanical, and Manufacturing Engineering of ULPGC and also coordinates the research Master’s degree of Advanced Technologies and Industrial Processes. Prof. Monzón has participated in 39 national and European research projects (27 as main researcher), 18 research projects funded by companies, and 72 proceedings of conferences; published 71 scientific publications; and supervised 8 doctoral theses, 7 national patents, and 1 international patent (in 5 countries). He is also the Editor of the book Additive Manufacturing – Developments in Training and Education (Springer) and the book Guía de tecnologías de Rapid Manufacturing. Prof Monzón is a member of the editorial board of the international journal Bio-Design and Manufacturing (Springer).

Maren Petersen is a Full Professor at the University of Bremen and a member of the Institute of Technology and Education (ITB) Executive Board. After graduating in Chemical Engineering, she focused on laser materials processing and Additive Manufacturing as a Research Assistant at the Institute of Laser and System Technologies (iLAS), Hamburg University of Technology (TUHH). Her doctoral research dealt with the Additive Manufacturing of metal-ceramic composites using laser beams and developed for quantifying new material systems for Additive Manufacturing with reduced effort. In addition to her work as a Senior Engineer at ILAS, she was part of the development of the LZN Laser Zentrum Nord GmbH (now Fraunhofer IAPT) and a Lecturer at the welding training center SLV Nord for welding engineer training on the topics of joining composites and rapid manufacturing. At the University of Wuppertal, she held the Chair of “Didactics of Technology” as a substitute Professor until 2015, when she was appointed to the Professorship of “Vocational Metal Technology and its Didactics” at the University of Bremen’s ITB. Research projects in her department include work on VR-supported teaching applications in the field of welding and

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About the Editors

collaborative robotics, as well as work-process-oriented and competence-based professional training in Additive Manufacturing. Since October 2022, she is also a member of the Executive Board of the University of Bremen as Vice President for Teaching and Studies.

Tao Sun is an Associate Professor at the Department of Materials Science and Engineering, University of Virginia (UVA). Dr. Sun received PhD degree in Materials Science and Engineering from Northwestern University. Co-advised by Prof. Vinayak Dravid at Northwestern and Dr. Jin Wang at Argonne National Laboratory (ANL), Dr. Sun’s doctoral research focused on fabrication of nanostructured oxides using sol-gel based approaches and characterization of these structures using advanced synchrotron x-ray techniques. After graduation, Dr. Sun joined the X-ray Science Division (XSD) at ANL as a Postdoctoral Researcher, working on developing coherent electron scattering (with Dr. J. Murray Gibson) and coherent x-ray scattering (with Dr. Jin Wang) techniques. In 2012, Dr. Sun became an Assistant Physicist in the Imaging Group of XSD and promoted to the Physicist position in 2017. During this period, Dr. Sun developed and applied high-speed x-ray imaging and diffraction techniques for studying highly dynamic irreversible and non-repeatable material processes. In September 2019, Dr. Sun relocated to UVA and started his academic career. Dr. Sun’s lab at UVA studies additive manufacturing processes and materials using synchrotron x-ray and other in situ/ex situ characterization techniques. The team is particularly interested in understanding the physics underlying the energy-matter interactions and non-equilibrium material structural evolution involved in additive manufacturing processes.

Contributors

Christophe Abel CIRTES, Saint-Dié-des-Vosges, France Nesma T. Aboulkhair Centre for Additive Manufacturing (CfAM), University of Nottingham, Nottingham, UK Frank Alifui-Segbaya School of Medicine and Dentistry, Gold Coast Campus, Griffith University, Southport, QLD, Australia Adelaide Almeida European Federation for Welding, Joining and Cutting (EWF), Brussels, Belgium Yahya Al-Meslemi LURPA, ENS Paris-Saclay, Université Paris Saclay, Gif-sur-Yvette, France Nabil Anwer LURPA, ENS Paris-Saclay, Université Paris Saclay, Gif-sur-Yvette, France Eurico Assunção European Federation for Welding, Joining and Cutting (EWF), Brussels, Belgium Vamsi Krishna Balla Bioceramics & Coating Division, CSIR-Central Glass & Ceramic Research Institute, Kolkata, India Rosa Maria Ballardini University of Lapland, Rovaniemi, Finland Claude Barlier CIRTES, Saint-Dié-des-Vosges, France John E. Barnes TBGA, Sewickley, PA, USA Paul Bates ASTM International, USA, Washington, DC, USA Marco Batschkowski Karlsruhe Institute of Technology (KIT) – wbk Institute of Production Science, Karlsruhe, Germany Zitouni Beidouri LARILE: Laboratory of Advanced Research on Industrial and Logistics Engineering, Ecole Supérieure De Technologie, Hassan II University, Casablanca, Morocco Vincenzo Belletti CECIMO, Bruxelles, Belgium Alain Bernard Ecole Centrale de Nantes, LS2N UMR CNRS 6004, Nantes, France Eberhard Bessey MANUFUTURE-EU, INESC Brussels HUB, Rue du Luxembourg, Brussels, Belgium Giovanni Bianchi Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland Manuel Biedermann ETH Zürich, Product Development Group Zurich pd|z, Zürich, Switzerland Samuele Bottacin Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland xxiii

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David Butler Department of Design, Manufacturing, and Engineering Management, University of Strathclyde, Glasgow, UK Francesco Camerota Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland Simon Chan University of Auckland, Creative Design and Additive Manufacturing Lab, Auckland, New Zealand Markus Chmielus Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA, USA Christian Daniel Institute of Laser and System Technologies, Hamburg University of Technology, Hamburg, Germany Mitun Das Bioceramics & Coating Division, CSIR-Central Glass & Ceramic Research Institute, Kolkata, India Anagh Deshpande Reverb Industrial, Inc., San Diego, CA, USA Olaf Diegel University of Auckland, Creative Design and Additive Manufacturing Lab, Auckland, New Zealand Claus Emmelmann Institute of Laser and System Technologies, Hamburg University of Technology, Hamburg, Germany Erica Lynn Stevens Erickson Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA, USA Niclas Eschner Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Latifa Fadile LARILE: Laboratory of Advanced Research on Industrial and Logistics Engineering, Ecole Supérieure De Technologie, Hassan II University, Casablanca, Morocco Kevin Ferreira LURPA, ENS Paris-Saclay, Université Paris Saclay, Gif-sur-Yvette, France Ismail Fidan Department of Manufacturing and Engineering Technology, Tennessee Technological University, Cookeville, TN, USA Aleksandra Foerster Centre for Additive Manufacturing (CfAM), University of Nottingham, Nottingham, UK Jacob Gatlin Auburn University, Auburn, AL, USA Filip Geerts CECIMO, Bruxelles, Belgium Salvatore Gerbino Department of Engineering, University of Campania “L. Vanvitelli”, Aversa (CE), Italy Negar Gilani Centre for Additive Manufacturing (CfAM), University of Nottingham, Nottingham, UK Antonio Gloria Department of Industrial Engineering, Fraunhofer JL IDEAS – University of Naples Federico II, Naples, Italy Dongdong Gu Nanjing University of Aeronautics and Astronautics, Nanjing, China Ankit Gupta Department of Technology, College of Engineering, Computer Science, and Technology, California State University Los Angeles, Los Angeles, CA, USA Marwan Haddad Texas A&M University, College Station, TX, USA

Contributors

Contributors

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Azadeh Haghighi University of Illinois Chicago, Department of Mechanical and Industrial Engineering, Chicago, IL, USA Rihan Hai Northwestern University, Evanston, IL, USA David G. Hardacre Inspection Services, LRQA, Burnley, UK Seymur Hasanov Material Science and Mechanical Engineering, Harvard John A. Paulson School of Engineering and Applied Sciences, Boston, MA, USA Elizabeth A. Holm Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA Jiashun Huang School of Public Affairs, University of Science and Technology of China, Hefei, China Iñigo Flores Ituarte Faculty of Engineering and Natural Sciences, Tampere University, Hervanta Campus, Tampere, Finland Israt Rumana Kabir University of Hertfordshire, Hertfordshire, UK K. P. Karunakaran Department of Mechanical Engineering, Rapid Manufacturing Laboratory, Indian Institute of Technology Bombay, Mumbai, India Andrew R. Kitahara Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA Christoph Klahn Karlsruhe Institute of Technology, Institute of Mechanical Process Engineering and Mechanics, Eggenstein-Leopoldshafen, Karlsruhe, Germany inspire AG, Zurich, Switzerland Ebubekir Koç Aluminum Test Training and Research Center (ALUTEAM), Fatih Sultan Mehmet Vakif University, Istanbul, Turkey T. Landgräber Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Gisela Lanza Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Christoph Leupold University of Bremen, Bremen, Germany Bastian Leutenecker-Twelsiek University of Applied Sciences Hochschule Düsseldorf, Düsseldorf, Germany Alexander Liu ASTM International, Singapore, Singapore, Singapore Bingjian Liu University of Nottingham, Ningbo, China He Liu Nanjing University of Aeronautics and Astronautics, Nanjing, China Ana Beatriz Lopez European Federation for Welding, Joining and Cutting (EWF), Brussels, Belgium Ji Ma Department of Materials Science, University of Virginia, Charlottesville, VA, USA Massimo Martorelli Department of Industrial Engineering, Fraunhofer JL IDEAS – University of Naples Federico II, Naples, Italy Antonio Di Mauro Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland Mirko Meboldt Product Development Group Zurich pd|z, ETH Zurich, Zurich, Switzerland

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Charyar Mehdi-Souzani LURPA, ENS Paris-Saclay, Université Paris Saclay, Université Sorbonne Paris Nord, Gif-sur-Yvette, France Dinusha Mendis Bournemouth University, Poole, UK Mario Monzón Mechanical Engineering Department, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain Pedro Gil Frade Morouço Polytechnic of Leiria, Leiria, Portugal Dimitris Mourtzis Department of Mechanical Engineering and Aeronautics, Laboratory for Manufacturing Systems and Automation (LMS), University of Patras, Patras, Greece Amal Naji LARILE: Laboratory of Advanced Research on Industrial and Logistics Engineering, Ecole Supérieure De Technologie, Hassan II University, Casablanca, Morocco Karlie B. Nixon Texas A&M University, College Station, TX, USA Hichem Nouira Laboratoire National de Métrologie et d’Essais (LNE-CNAM), Paris, France Anne-Françoise Obaton Laboratoire National de Métrologie et d’Essais (LNE-CNAM), Paris, France F. Ohlsen Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Daniel Omidvarkarjan IWK Institute for Material Science and Plastics Processing, Rapperswil-Jona, Switzerland Alberto Ortona Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland Burçin Özbay Kisasöz Aluminum Test Training and Research Center (ALUTEAM), Fatih Sultan Mehmet Vakif University, Istanbul, Turkey Gökhan Özer Fatih Sultan Mehmet Vakif University, Aluminium Test Training, and Research Center (ALUTEAM), Istanbul, Turkey Niranjan D. Parab X-ray Science Division, Argonne National Laboratory, Lemont, IL, USA Intel Corporation, Hillsboro, OR, USA Kyungho Park Korea Conformity Laboratories, Health Division, Hygiene Product Center, Uiwang, Republic of Korea Rubén Paz Mechanical Engineering Department, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain Eujin Pei College of Engineering, Design and Physical Sciences, Brunel University London, London, UK Marco Pelanconi Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland Maren Petersen University of Bremen, Bremen, Germany Özgür Poyraz Eskişehir Technical University, Eskişehir, Turkey Khalid Rafi ASTM International, Singapore, Singapore, Singapore Sudhir Rama Murthy Saïd Business School, University of Oxford, Oxford, UK Institute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge, UK Zhongshu Ren Department of Materials Science and Engineering, University of Virginia, Charlottesville, VA, USA

Contributors

Contributors

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Jean-Loup Rennesson INORI, Saint-Dié-des-Vosges, France François Richard Pratt & Whitney Canada, St-Denis-sur-Richelieu, QC, Canada Anthony D. Rollett Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA Alice Rosa Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland Ralph Rosenbauer ETH Competence Center for Materials and Processes MaP, ETH Zurich, Zurich, Switzerland Adam Rushworth University of Nottingham, Ningbo, China Oscar Santoliquido Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland Juan Schutte University of Auckland, Creative Design and Additive Manufacturing Lab, Auckland, New Zealand Mohsen Seifi ASTM International, USA, Washington, DC, USA S. Seiz Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Nima Shamsaei Auburn University, USA, Auburn, AL, USA Timothy W. Simpson State College, PA, USA Jonathan Smith Department of Design, Manufacturing, and Engineering Management, University of Strathclyde, Glasgow, UK Adriaan B. Spierings inspire AG, St.Gallen, Switzerland Panagiotis Stavropoulos Department of Mechanical Engineering and Aeronautics, Laboratory for Manufacturing Systems and Automation (LMS), University of Patras, Patras, Greece Cheng Sun Northwestern University, Evanston, IL, USA Tao Sun Department of Materials Science and Engineering, University of Virginia, Charlottesville, VA, USA Xu Sun University of Nottingham, Ningbo, China Woocheol Sung Korea Conformity Laboratories, Environment Division, IAQ Center, Anyang, Republic of Korea Akihiro Takezawa Waseda university, Tokyo, Japan Chander Velu Institute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge, UK Simone Vitullo Hybrid Materials Laboratory, Mechanical Engineering and Materials Technology Institute (MEMTi), University of Applied Sciences (SUPSI-DTI), Lugano, Switzerland Ruiqi Wang Nanjing University of Aeronautics and Astronautics, Nanjing, China Henry Oliver Tenadooah Ware North Carolina State University, Raleigh, NC, USA Lukas Weiser Karlsruhe Institute of Technology (KIT) – wbk Institute of Production Science, Karlsruhe, Germany Sarah Wolff The Ohio State University, Columbus, OH, USA Lixia Xi Nanjing University of Aeronautics and Astronautics, Nanjing, China

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Mark Yampolskiy Auburn University, Auburn, AL, USA Srujana Rao Yarasi Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA Evren Yasa Eskişehir Osmangazi University, Eskişehir, Turkey Advanced Manufacturing Research Centre University of Sheffield, Samlesbury, UK Mustafa Safa Yilmaz Bursa Uludag University, Engineering Faculty, Mechanical Engineering Department, Bursa, Turkey Khalid Zarbane Laboratory of Advanced Research in Industrial Engineering and Logistics (LARILE), National Institute of Electricity and Mechanics (ENSEM), Hassan II University of Casablanca, Casablanca, Morocco Fangjin Zhang School of Design and Creative Arts, Loughborough University, Loughborough, UK Cang Zhao Department of Mechanical Engineering, Tsinghua University, Beijing, China

Contributors

Part I Introduction

1

History of AM Eujin Pei

, Israt Rumana Kabir, and Bastian Leutenecker-Twelsiek

Contents 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Pre-historical Emergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 Transformation to the Automatic Systems . . . . . . . . . . . . . . . . . .

3 3 4

1.2 1.2.1 1.2.2 1.2.3 1.2.4 1.2.5 1.2.6 1.2.7

Developments of Additive Manufacturing . . . . . . . . . . . . . . . Vat Photopolymerization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Powder Bed Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Directed Energy Deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material Jetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material Extrusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sheet Lamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Binder Jetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 5 6 9 12 15 17 19

1.3

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Abstract

The history of Additive Manufacturing (AM) goes back to the nineteenth century in the form of photo-sculpture and three-dimensional (3D) cartography. The AM process chain is not limited to technological advancements and process mechanisms but also accelerated and supported through developments in Computer-Aided-Design (CAD), materials, testing, certification, and postprocessing. This chapter provides a chronological account of AM processes (Vat Photopolymerization, Powder Bed Fusion, Directed Energy Deposition, Material Jetting, Material Extrusion, Sheet Lamination, and Binder Jetting) from late nineteenth century to present. Readers will have E. Pei (*) College of Engineering, Design and Physical Sciences, Brunel University London, London, UK e-mail: [email protected] I. R. Kabir University of Hertfordshire, Hertfordshire, UK B. Leutenecker-Twelsiek University of Applied Sciences Hochschule Düsseldorf, Düsseldorf, Germany

a clear understanding about the origins and development of different AM processes, thereby to gain foresight about possible trends in AM and its future applications. Keywords

Additive Manufacturing · History · Chronology · Developments · Processes

1.1

Background

It is worth noting that although AM is considered an advanced manufacturing tool, its true emergence started from the mid-nineteenth century. In this section, a historical foundation of AM is described from its formative phase through manual means of additive processes to produce a three-dimensional structure. The historical narrative then continues with a phase of digitalization and automation to its present day.

1.1.1

Pre-historical Emergence

Some scholars claimed that the roots of AM [1, 2] began in the middle of the nineteenth century, when Francoise Willème in France developed the first process for a 3D photo-sculpture adapted from a relatively new technique of photography in 1859 [3]. This process is interesting as it combined the idea of additive modelling and an analogue attempt at 3D scanning. Willème’s idea was to convert flat 2D photographic images of people into a 3D representation. He arranged 24 cameras in a circle around the person and exposed the plates to simultaneously capture various silhouettes that were cropped and figuratively joined around a central axis. The segment model with an outer contour was a representation of the photographic subject and it was worked out of wood using mechanical transfer tools with an ablative process. Beaman [1] coined this term

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_1

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E. Pei et al.

“Solid Freeform Fabrication“as an earlier term for AM, and gave recognition to the photo-sculpture process as well as a novel technique of topographical mapping. In 1890, American mapmaker E. Blanther, filed a patent for a method of producing 3D relief maps [4]. This was based on the layering of contoured wax plates one at a time and then fused together in layers and smoothed on the outer surfaces. In the work of Baese (1904) [5] and Montheath (1924) [6], light-sensitive materials and selectively graduated use of light was utilized to create the bond between materials. In 1925, a manual arc-based Directed Energy Deposition (DED) technique was patented by the Westinghouse Electric and Manufacturing Corporation. Their process used an electric arc to deposit molten superimposed layers from a metallic electrode to produce 3D ornamental objects [7]. Further in 1951, Otto John Munz [8] proposed using photopolymers in an analogue form of stereolithography; and DiMatteo, in 1974, suggested an analogue method of creating a layer-by-layer casting mold for objects with complex surface geometries [9]. However, these ideas lacked the technological prerequisites for industrial utilization, as they were limited to an analogue setup. Therefore, what makes it clear about the unique selling point of AM above all other conventional manufacturing processes is the intrinsic integration of digital technology with the production process.

1.1.2

Transformation to the Automatic Systems

With the advent of modern computers and digital tools, the modelling of virtual 3D models accelerated the development of AM. The development of lasers also played a vital role in its digital initiation. The first functioning ruby laser was realized by Theodor Maiman in 1960. Using both computers and lasers in 1971, Swainson first presented a process in which light-sensitive polymers were photochemically and selectively bonded in a layering process using computerguided laser energy and built up to form 3D objects [10]. However, Swainson’s computer did not have any virtual models. The morphological direction and control of the laser application was carried out directly from a simultaneous acquisition of the geometries of the reference object by means of three laser interferometers. In 1973, Pierre Alfred Ciraud proposed a technique that joined powders on various material bases employing selective laser sintering to form a predefined geometry. Both photochemical and the physical way of joining materials formed the basis of today’s Vat Photopolymerization (VPP) and Powder Bed Fusion (PBF) processes. Subsequently in 1979, Ross Housholder developed and patented a technique for powder-bed laser sintering [11], a layer-by-layer structure using a mask-based heat input. This was followed by a process based on

photopolymerization by Hideo Kodama in Japan that was first proposed in 1981 [12]. He described the production of 3D components from photopolymers for the creation of prototypes, thus termed as “Rapid Prototyping”. The stereolithography process developed by Charles W. Hull (also known as Chuck Hull) was based on the same approach and he filed a patent in 1984 [13]. He presented a commercial version of this AM system at an industrial trade fair in 1987 with his own company, 3D Systems. Liquid plastic was solidified layer-by-layer by means of selectively guided laser and exposure was timed according to computer specifications and progressively building a 3D object. The construction data was transmitted directly from a virtual model to the machine and being produced layer-upon-layer. Some scholars recognize this as the start of the first wholly functioning “3D Printer” that began with Hull’s stereolithographic machine. A corresponding system for PBF followed when Carl Deckard and Joe Beaman from the University of Texas at Austin brought the first commercial machine onto the market and obtained patents in 1989 [14]. Within 1987 to 1990, other AM processes were developed and patented, such as Material Extrusion (MEX) by Steve Scott Crump. Commercialization took place through the company Stratasys, retailing its first machines from 1992. The production of metallic components was also carried out through the use of a powder bed and fused with lasers in the 1990s by Matthias Fockele and Dieter Schwarze with their company Fockele & Schwarze (F&S) in cooperation with the Fraunhofer Institute for Laser Technology (ILT Aachen, Germany). Patents for laser-based metal PBF system was registered in 1996 and the first systems were delivered in 1998. Almost simultaneously, Ralf Larsson applied for patents in Sweden in 1993 for a powder bed system using electron beams that were granted in 1997. This technology, known as Electron Beam Melting (EBM), also a member of PBF family, was commercialized by Arcam AB. In following sections, a detailed historical account of each of the seven AM processes will be discussed.

1.2

Developments of Additive Manufacturing

The scope of this section will be limited to historical facts of each of the seven AM processes, defined by ISO/ASTM 52900 [15], comprising of Vat Photopolymerization using liquid photopolymer in a vat that is selectively cured by a light-activated polymerization process; Powder Bed Fusion that uses thermal energy to selectively fuse regions of a powder bed; Directed Energy Deposition in which focused thermal energy is used to fuse materials by melting as they are being deposited; Material Jetting where droplets of feedstock material are selectively deposited; Material

1

History of AM

Extrusion where material is selectively dispensed through a nozzle layer-by-layer; Sheet Lamination in which sheets of material are bonded to form a part; and Binder Jetting in which a liquid bonding agent is selectively deposited to join powder materials. The following sections provide a historical narrative on the development of the seven AM processes focusing on the invention and commercialization. The other elements of AM processes including design, modelling, materials and standards, policy and protocol are found in the subsequent chapters of this book.

1.2.1

Vat Photopolymerization

Vat Photopolymerization (VPP) is a technique that uses a light source to selectively cure and create a 3D parts layerupon-layer from a vat containing photopolymer resin. There are several derivatives of VPP based on the curing medium, selective curing mechanism, and the process, [16] including but not limited to: • • • • • • • • •

Continuous Liquid Interface Production (CLIP) [17] Daylight Polymer Printing (DPP) Digital Light Manufacturing/Processing (DLM/DLP) Electron/X-ray Lithography [18, 19] Grayscale Lithography [20] Lithography-based Ceramic Manufacturing (LCM) Low Force Stereolithography (LFS) [21] Nanoimprint Lithography [22] Scan, Spin and Selectively Photocure Technology (3SP) [23] • Solid Ground Curing (SGC) [24]

a)

5

• Stereolithography or Stereolithography Apparatus (SLA ® 3D Systems Corporation) [13] • Two-Photon Polymerization (2PP) [25] VPP was first patented by Swainson in 1975 in the USA with two laser beams to cure the photopolymer [26], also known as Two-Photon Polymerization (2PP) or Direct Laser Writing (DLW) that was later developed as a microfabrication technique for microelectronics [27], tissue engineering [28], and regenerative medicine applications [29]. In 1981, Dr. Hideo Kodama [12] was the first to propose the VPP process from Japan and he filed a patent [30]. However, due to lack of experimental validation, the patent was not granted. Henceforth, additional patents for VPP were also submitted in 1984 around the world by Yoji Marutani in Japan [31], Andre et al. in France [32], and Charles W. Hull in the USA [13]. Among them, Charles W. Hull was the first to commercialize the VPP system known as Stereolithography Apparatus (SLA). He co-founded a company named 3D Systems in 1986 and in the following year, presented his VPP system at an industrial trade fair. The SLA-1 beta was the first commercially available VPP or AM machine and the precursor of the SLA 250 machine [33]. Later in 1987, 3D Systems developed the Standard Triangle Language or Standard Tessellation Language (STL) file format for SLA [34], and this file format is now being used in almost all AM processes to transfer the 3D CAD model data to a printable file format. The detailed description and development of the AM file formats including STL will be found in the chapter Additive Manufacturing File Formats and Solid Modeling Support of this handbook. A 3D Systems’ Viper Si2 VPP machine is presented in Fig. 1.1.

b)

Fig. 1.1 3D Systems Viper Si2 (a) [35], Photocentric Liquid Crystal HR2 3D Printer (b) [36]

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Japan’s NTT Data CMET and Sony/D-MEC also commercialized versions of VPP systems in 1988 and 1989, respectively. NTT Data CMET, now part of Teijin Seiki, a subsidiary of Nabtesco, called its system Solid Object Ultraviolet Plotter (SOUP), while Sony/D-MEC, now D-MEC, called its product Solid Creation System (SCS). In 1991, Electro Optical Systems (EOS) of Germany sold its first VPP systems STEREOS 400 and in the same year, Quadrax introduced the Mark 1000 SL system, which used visible light resin [33]. In 1991, Cubital introduced the Solid Ground Curing (SGC) process, which is a mask-based lithography technique cured with a UV lamp, but later ceased operations in 1999 due to the complexity of the system [37]. In 1993, Denken introduced a VPP system that used a solid-state laser. Denken’s VPP system was one of the first to fit on a bench top and was introduced at a low price, compared to other systems on the market. A newer Japanese system from Meiko targeted mainly at jewelers although they ended their VPP business in 2006. In 1994, Fockele & Schwarze (F&S) of Germany introduced a VPP machine, but it was only retailed on a limited basis [33]. In 2009, a multi-material VPP system was developed and patented by the University of Texas at El Paso [38, 39]. In this process, multiple vats containing different materials were introduced to print multi-material or functionally graded parts. However, switching multiple vats during the process reduced the process speed and caused contamination of mixed materials that led to other technical challenges and had to be resolved. Other commercial giants such as Denken, EnvisionTEC, and 3D Systems launched their VPP systems in the market at different times. In 2015, Carbon introduced a novel concept known as Continuous Liquid Interface Production (CLIP) using an oxygenpermeable bottom plate to make the printing process 100 times faster than a conventional VPP machine [40], also known as Digital Light Synthesis (DLS) that uses a projector to cure the polymer resin. Carima from Korea, 3D Systems from the United States, and Prodways from France also developed variations of this technology [41]. However, in 2016, EnvisionTEC pioneered its Micro Plus continuous Digital Light Manufacturing (cDLM), also known as Digital Light Printing (DLP), machine that used a UV Light-Emitting Diode (LED) capable of printing at a speed of 10–20 min per inch on the Z-axis [41]. This was targeted at the jewelry industries, and it was able to print castable objects. In the same year, Photocentric [42] launched the world’s first daylight hardening system known as Daylight Polymer Printing (DPP), which is a Liquid Crystal Display (LCD) based VPP process shown in Fig. 1.1b. 3D Systems also released their first digital synthesis VPP machine that was known as “Figure-4™”, claiming to make 3D production feasible through scalable and modular units. Initially, VPP systems were expensive and less accessible. Following the development of DLP- and LCD-based systems, other companies

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began to offer scalable and low-cost resin printers with high-quality print capabilities [43]. For example, ELEGOO Mars and AnyCubic Photon offered VPP printers at a cost of $500 with a reasonable print accuracy. From 2011 to 2019, Formlabs adapted the use of VPP in the form of printers based on Low Force Stereolithography (LFS) technology around the cost of $3500 [39, 44–47]. Across other sectors, Lithoz’s proprietary Lithography-based Ceramic Manufacturing (LCM) technique was released in 2011 to utilize corning glass for the first time. In 2015, French ceramics experts at 3DCERAM-SINTO advanced its 3D Printing ceramics technology to develop components for medical X-ray imaging systems [48]. Besides mechanical and technological innovations, the development of VPP as an AM process was accelerated by breakthroughs in terms of materials and applications. Currently, there are a range of photopolymers developed for VPP including structural, tough, durable, flexible, elastic, castable, biocompatible, and bioink resins. A summary of key discoveries and commercial timeline of VPP is shown in Table 1.1.

1.2.2

Powder Bed Fusion

Powder Bed Fusion (PBF) creates 3D parts by focusing a high-density energy beam (laser or electron beam) over a bed of powdered material to fuse or melt the cross sections of the part layer-by-layer until achieving the full geometry [49]. PBF comprises a range of technologies including Selective Laser Sintering (SLS), Selective Laser Melting (SLM), and Electron Beam Melting (EBM) that share similarities. There are several derivatives of PBF processes also known as: • Direct Metal Laser Remelting (DMLR) [50] • Direct Metal Laser Sintering (DMLS ® EOS GmbH) [50] • Direct Metal Printing (DMP by 3D Systems Corporation) [47, 51] • Electron Beam Additive Manufacturing (EBAM) [52] • Electron Beam Melting (EBM by Arcam AB) [53] • High Speed Sintering (HSS) [54] • Laser Metal Fusion (LMF by TRUMPF) [55] • LaserCUSING ® Concept Laser GmbH [50] • Micro Laser Sintering (MLS by EOS GmbH) [56] • Polymer Multi Jet Fusion (MJF ™ Hewlett-Packard) [57] • Selective Electron Beam Melting (SEBM) [58, 59] • Selective Heat Sintering (SHS) [60] • Selective Laser Melting (SLM) [50] • Selective Laser Sintering (SLS ® 3D Systems Corporation) [50] The classification of PBF technology is based on the processed material. Polymers and metals are the most common materials processed with this technique. Carl R. Deckard from

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Table 1.1 A chronological history of key VPP processes

1 Discovery Year

Event

Commercialization Year

1975

• Swainson invented the 2PP process

1986

1981

• Kodama from Japan performed stereolithography experiments to successfully print a clear polymeric part

1988

1984

1987 1991

2009

• Charles W. Hull developed the SLA process using polymeric resin • First STL file format created by 3D Systems • Cubital introduced mask-based technique the Solid Ground Curing (SGC) cure with a UV lamp • Multimaterial Stereolithography was patented by University of Texas at El Paso

2015

• Carbon Inc. developed CLIP, a high-speed VPP process

2016

• Photocentric introduced the DPP Liquid Crystal 10 3D Printer

1989

1991 2011

2015 2016

2019

the University of Texas (UT) at Austin was the first to be granted a patent for PBF in 1989 [14]. In this patent, Carl described the method and apparatus to sinter a layer of powdered material, either polymer, metals, or ceramic, to produce a fully dense part by scanning a laser beam over the layers. Initially, he and his team invented the PBF process for polymers called SLS which using a laser beam selectively sinters the mass of polymeric powder to print a part gradually layer after layer. To commercialize the system, they formed a company called Nova Automation that later became known as DTM (Desktop Manufacturing) Corporation [61]. The first commercial SLS systems from DTM was the Sinterstation 2000 marketed in 1993 [62]. Although some scholars recognized UT at Austin as the birthplace of SLS, the PBF AM process has its roots back from the 1970s. In 1979, Ross Housholder filed a patent application [11] that described a similar SLS system for molding. Due to the lack of resources, the process was not developed for commercialization. Later, DTM acknowledged and licensed the process [63], although in 1990s, DTM sold its share to BFGoodrich that eventually sold them to the AM giant 3D Systems [62]. As a result, 3D Systems acquired the key patent rights of SLS and unveiled

Event • Charles W. Hull founded 3D Systems to commercialize his VPP system • Japan’s NTT Data CMET commercialized VPP technology named it Solid Object Ultraviolet Plotter (SOUP) • Sony/D-MEC, marketed their VPP system Solid Creation System (SCS) • EOS launched its VPP system, Stereos 400 • A spin-off company Lithoz was founded from TU Vienna to launch a novel Lithography-based Ceramic Manufacturing (LCM) • Carbon Inc. launched its first CLIP system also known as DLS • EnvisionTEC commercialized continuous Digital Light Manufacturing based on the DLP process of Carbon 3D • Photocentric launched an LCD based ceramic lithographic 3D printer

the Sinterstation Pro in 2005 as a large-frame laser-sintering machine with part breakout, powder handling and recycling facilities [64]. In 2013, 3D Systems launched the Direct Metal Printing (DMP) process, a PBF method for metals and alloys where fiber laser beams selectively fuse the metal powder to produce the part layer-by-layer [47]. Figure 1.2 shows a 3D Systems’ DMP machine and a Sinterstation 2500 SLS machine. In Asia, Farsoon technology notably promoted the SLS processes from China to a worldwide audience. Having served as a technical director of DTM corporation in early 1990s, Dr. Xu Xiaoshu gained huge experience and expertise in SLS technology. In 2009, he founded his own company Farsoon technology to offer industrial grade polymer and metal laser sintering systems in China. Their systems use CO2 or fiber (single/dual/quad) lasers depending on the materials and applications. Farsoon technology offers an open platform system which provides the users access to the key parameter settings in the system based on the required application and material requirement [65]. In 1993, Electro Optical Systems (EOS) GmbH in Germany developed a similar type of laser-based PBF system to produce parts by selective sintering polymer and metal

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a)

b)

Fig. 1.2 PBF for metals, Prox DMP 320 high precision industry-grade machine introduced in 2016 (a) [66], PBF for polymers, Sinterstation 2500, 3D Systems, earlier edition (b) [35]

powders of low-medium melting points [67]. In 1994, they launched the EOSINT P350 machine for polymers. In the same year, they commercialized the EOSINT M160 system for metals which they called Direct Metal Laser Sintering (DMLS) [68]. EOSINT systems use either CO2 of Neodymium-doped Yttrium Aluminum Garnet (ND:YAG) laser emitting in the infra-red region that locally fuses the powder materials to bind the individual grain [69]. In 1995, EOS introduced EOSINT M250, claimed to be the first generation of commercial DMLS machines [63, 70, 71]. The EOSINT M250 was based on EOS’ polymer-based PBF systems that used a CO2 laser system and a vacuum system [67, 72]. Likewise, the EOSINT MXXX systems evolved gradually in terms of the laser system intensity, layer thickness, materials, etc., which was reflected by the addition the EOSINT M270 in 2004 with a solid-state Ytterbium fiber laser system [63]. In 2013, EOS launched the EOSINT M400 with a build volume of 400
400
400 mm3 and uses a 1000-Watt fiber laser to increase the build rate suitable for industrial production [34]. EOS also developed the Micro Laser Sintering (MLS) process in collaboration with 3D-Micromac AG. They founded 3D MicroPrint GmbH in 2013 to commercialize the process that could produce micro metal parts with high accuracy, detailed resolution, and excellent surface quality. The process uses a combination of a very small laser beam spot size (30 μm), special micro powders and with super fine layers (1–5 μm comparing to the 20–200 μm for EOSINT series [56, 73, 74]. SLM is a derivative of the PBF process where full melting of the powder bed particles takes place by using one or more lasers. This process was initially developed by Fraunhofer ILT and patented in 1996 [75, 76]. Fraunhofer ILT collaborated with Fockele & Schwarze (F&S) Stereolithographietechnik GmbH for further development of the SLM process. F&S trademarked the name SLM and first

commercialized this through delivering a machine named Realizer to Trumpf in 1998 [77]. Later, F&S and ILT included MCP HEK GmbH (now SLM Solutions GmbH) into the commercial partnership. Eventually, MCP owned the commercial rights of SLM technology and in 2006 launched SLM machines that could utilize Aluminum and Titanium alloys. MCP was renamed as MTT Technologies in 2008 and again as SLM Solutions in 2011. At that time, some shares of MTT was sold to Renishaw in the UK [78, 79]. SLM Solutions launched the SLM 500HL machine in 2012 that uses multiple lasers to increase the build rate of up to 35 cm3/h and with a build volume of 500
350
300 mm3. Two sets of lasers are used in this machine, each being 400 W and 1000 W, with a total of four lasers that can simultaneously scan the powder layer [80]. In 1993, Ralf Larson filed a patent on welding layers of metal particles using an electron beam heat source and vacuum system to create 3D parts [81, 82]. The work was conducted in collaboration with Chalmers University at Gothenburg in Sweden [82–84] that created the idea of Electron Beam Melting (EBM). In 1997, Arcam AB of Sweden was founded to commercialize the idea of EBM with their first machine EBM S12 being sold in 2001 and delivered in 2002 [53]. Arcam’s EBM can process tool steel powder and is also suitable for high melting temperature alloys including Titanium, Nickel, and Cobalt alloys. ARCAM’s EBM system uses a high-power electron beam of 3000 W capacity to melt powder bed layers [80]. In 2007, the Arcam A2 was developed for producing orthopedic implants that had a double stage pumping mechanism allowing a 1010 MPa vacuum system to reduce oxidation and contamination. In the following year, the Arcam A1 model introduced a multiple beam scanning mechanism that enhanced the processing speed and was dedicated for the mass production of orthopedic implants [83]. The Arcam A2 X was developed with a larger build

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History of AM

chamber for the production of large parts for aerospace industries [53]. In 2016, Arcam AB was acquired by General Electric and has continued to have a monopoly of the EBM market [85]. Concept Laser GmbH, at that time part of the Hofmann Innovation Group located at Lichtenfels in Germany, was founded by Frank and Kerstin Herzog in 2000, and is one of the leading providers of metal AM. The company commercialized a process called LaserCUSING. In this process, a laser is used to fuse each layer of the powder bed in each cross section to build the complete part in the enclosed chamber. The term CUSING comes from the letter ‘C’ (of Concept Laser) and the word “FUSING”. The special feature of LaserCUSING machines is the stochastic exposure strategy based on an island principle. Each layer of the required cross section is divided into several segments called “islands” that are selected stochastically during scanning. It is claimed that this strategy ensures thermal equilibrium on the surface and reduces component stress [86]. The first LaserCUSING system was launched in 2001 that was a hybrid system called M3 Linear that combined laser sintering, marking, and machining and started selling from 2002. The machine uses low power Yttrium Aluminum Garnet (YAG) laser which later improved in to 200 W or 400 W fiber laser in 2004 and can utilize a wide range of metal powders such as Stainless Steel, Inconel, and CobaltChromium alloys to produce fully dense parts [33, 87]. In subsequent years, the company has released more CUSING machines, M1 for small and medium part production in 2004, and M2 multi-lasers for treating Titanium alloys safely with multiple heat sources in 2007. In 2015, Concept Laser developed the largest DMLM machine for metals known as the X Line 1000R with a build volume of 630
400
500 mm3 and a build rate up to 100 cm3/h [88]. In 2016, GE acquired 75% of shares of Concept Laser GmbH [89]. Another leading German company in the machine tooling and laser technology, Trumpf, introduced the Laser Metal Fusion (LMF) process and launched its first machine TrumaForm 250 in 2003 [64, 90]. The machine uses multiple 250 W fiber lasers to increase the melting efficiency of metal powders. In terms of solid-phase sintering, Phenix Systems of France sold its first Phenix 900 system in 2002 that uses fine graded ceramic and metal powder. The company developed PX systems in three different sizes based on the applications and treated materials. Their systems use fiber laser to sinter the solid mass with or without instantaneous consolidation at the melting point. Instead of using laser or electron beam energy, the PBF process was further developed using an Infra-Red (IR) lamp as a heat source and a printhead system. In 2003, High Speed Sintering (HSS) was invented and patented [91] in the UK by Professor Neil Hopkinson from Loughborough University [54, 92]. Later, the commercialization of HSS began in 2005 with the collaboration of a ink-jet technology

9

developing company, Xaar, and the first HSS machine Velox 190 [93] was developed at the University of Sheffield in 2011 [94]. In this process, a printhead deposits an IR absorbing secondary material or an IR reactive ink over the polymeric powder bed and the IR lamp irradiates the ink causing the underlying powder to melt and sinter into a solid mass. This process shows good surface finish and is suitable for volume series production as it increases the printing speed enormously. Later, leveraging Voxeljet’s jetting printhead technology, the company also developed their HSS system VX200 platform and launched it at the Formnext Expo in 2017 [95]. Selective Heat Sintering (SHS) is another printhead-based PBF process suited for applications where complex geometries are required. SHS uses a thermal print head to sinter thermoplastic powder, whereas SLS uses a laser to sinter the thermoplastic powder. The benefits of using a thermal print head over a laser include the fact that the AM system can be much smaller in size, and the system is more affordable since thermal printheads are far less expensive to produce and maintain as compared to lasers. The technology was launched at Euromold in 2011 by a Danish company, Blueprinter, that invented and patented the SHS technology as a start-up [60, 96]. In 2014, Hewlett Packard (HP) developed the Multi Jet Fusion (MJF) technology utilizing the use of ink-jet printing heads with an integrated heater with an enhanced speed that claimed to be 10 times faster than SLS [57]. Unlike HP’s Metal Jet Printing (MJP) that is a BJ process, MJF prints functional materials onto the powder bed to fuse the selective region in layers. HP introduced the Jet Fusion 5200 to the market in 2016 [97–100]. A summary of key discoveries and commercial timeline) of PBF is shown in Table 1.2.

1.2.3

Directed Energy Deposition

Directed Energy Deposition (DED) is a process where focused energy is used to fuse the material while being deposited onto a substrate to create 3D parts layer-by-layer [101]. DED is also known as: • • • • • • • • • •

3D Laser Cladding [102]/ Laser Metal Forming [103] Cold Gas Dynamic Spray [104] Direct Laser Deposition (DLD) [50] Direct Laser Fabrication [50] Direct Metal Deposition (DMD ® by DM3D Technology, LLC) [50] Directed Light Fabrication (DLF) [50] Electron Beam Additive Manufacturing (EBAM™ (Sciaky, Inc.) [105] Electron Beam Freeform Fabrication (EBF3) [106] Focused Ion Beam Direct Writing (FIBDW) [107] Laser Chemical Vapor Deposition (LCVD) [108]

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Table 1.2 A chronological history of key PBF processes

Discovery Year

Event

1979 • Ross Housholder invented a powder bed process for molding

Commercialization Year 1993

1989 • Carl R. Deckard invented the SLS with a wide range of materials to produce functional parts • EOS GmbH developed SLS for low1993 medium melting points polymers and metals powders of

1994

1996 • Fraunhofer ILT developed and patented SLM

1997

1993 • Ralf Larson successfully used an electron beam source and a vacuum chamber for selectively sintering a printed metallic part and the novel EBM process was born 1999 • Fraunhofer ILT with the collaboration of Fockele & Schwarze (F&S) invented SLM to completely fuse the metal powder using lasers to print a part 2003 • High Speed Sintering (HSS) was invented and patented by Professor Neil Hopkinson from Loughborough University, UK • Danish company, Blueprinter that 2011 invented and patented the Selective Heat Sintering (SHS) technology as a start-up • EOS developed the Micro Laser 2013 Sintering (MLS) process in collaboration with 3D-Micromac AG

• Laser Consolidation (LC) [109, 110] • Laser Deposition Welding [111] • Laser Engineered Net Shaping (LENS ® Sandia National Labs) [50, 112] • Laser Metal/Melting Deposition (LMD) [50] • Laser Powder Forming [113] • Laser Rapid Forming [50] • Metal Powder Application (MPA, by Hermle Maschinenbau GmbH) [114] • Powder Fusion Welding [115] • Shape Deposition Manufacturing (SDM) [116] • Shape Welding [117] • Three-Dimensional Welding [117] • Wire Arc Additive Manufacturing (WAAM) [118] Perhaps the oldest example of a manual arc-based DED technique was reported as the concept of using an electric arc for the fabrication of a 3D ornamental object by depositing

Event • Carl R. Deckard and his team founded DTM corporation and commercializes the SLS process for polymeric materials • The first SLS machine Sinterstation 2000 was marketed

1998

2001

2014

• EOS launched the EOSINT P350 polymer SLS machine • The Arcam AB was founded to commercialize first EBM S12 process in collaboration with Chalmers University in Sweden • Fockele & Schwarze (F&S) trademarked SLM and commercialized first machine the Realizer • Concept Laser GmbH launched a PBF technique LaserCUSING with a novel scanning strategy to reduce post treatment residual stress of the printed parts • Hewlett Packard launched MJF by using a print head to deposit a fusing agent onto the polymer powder bed

2016

• HP marketed Multi Jet Fusion (MJF) system Jet Fusion 5200

2017

• Voxeljet launched the HSS system VX200

molten superimposed layers from a metallic electrode. This process was patented by the Westinghouse Electric and Manufacturing Corporation that later became the Westinghouse Electric Corporation in 1925 [7]. However, the concept was there which turned to the development of a first powder blown DED technique in 1971, when Pierre Ciraud filed a patent application [119] for a method of manufacturing any geometry by applying powdered material such as metal onto a substrate and solidifying it by means of an energy beam such as laser, electron, or plasma arc. In this invention, Ciraud mentioned about a control system to manipulate the paths where material deposited. In the late 1980s, Frank Arcella at Westinghouse Electric Corporation filed a patent application [120, 121] for a method called Laser Forming of near-net shapes [122], which he modified this into a laserbased DED process known as Laser Welding. In 1997, he worked with MTS Systems Corporation and started Aeromet to commercialize the process. The system was developed

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History of AM

[123–125] in collaboration with Johns Hopkins University and Penn State University funded by the US Department of Defense. They named it Lasform that was utilized for aerospace applications [126]. In the same year, Optomec launched a DED technique called Laser Engineered Net-Shaping (LENS), which was the result from the research at Sandia National Laboratories and supported by the US Department of Energy [50, 112, 127]. An Optomec DED machine is shown in Fig. 1.3. Optomec first delivered a commercial LENS machine in 1998 [128, 129] and this led to a variety of similar processes including Direct Metal Deposition (DMD), Multi-Layer Laser Cladding, Laser Metal Deposition (LMD), and Direct Laser Fabrication (DLF) [50]. Koch and Mazumder from the University of Michigan developed the DMD process [131, 132], and they filed a patent for DMD based on their Multi-Layer Laser Cladding system in 1998 [133]. This process was commercialized by the POM group in 2001 [134, 135] and later acquired by DM3D Technology in 2013 [136]. Laser Cladding was initially known as a surface hardening technique used for repairing and coating of metallic components [137]. Cladding is generally used to form corrosion protective coatings on substrates or to improve the tribological properties such as hardness, co-efficient of friction, and wear resistance of parts [138, 139]. In the 1990s, this process was adopted as a rapid manufacturing method for metallic components [102, 140]. There is also an added advantage of using cladding as a DED process for two dissimilar materials to create multi-materials

Fig. 1.3 Photograph of Optomec LENS 500 series DED machine. (Photo credit: U.S. Army CCDC from Fickr.com) [130]

11

or functionally graded structures [141]. Another useful cladding technique is multi-axis cladding that can deposit layers at any angular axis. This functionality enables DED to be more advantageous over other AM systems [142–144]. Interpass rolling [145] and Ultrasonic Vibration Assisted LENS [146] are also used for grain size refinement and to enhance the mechanical properties of the produced parts. Electron Beam Freeform Fabrication (EBF3), Electron Beam Additive Manufacturing (EBAM), or Electron Beam Layer Manufacturing are other derivatives of the DED process that feed the material in a wire form that is then melted with an electron beam. EBF3 was developed [106] and patented [147, 148] by NASA engineers in 2002. They wanted to use this technology to create parts for the space program. The process was first introduced by Vivek Davé from the Massachusetts Institute of Technology (MIT) through his doctoral thesis in 1995 [149]. Later, in 2009, an Illinois-based company, Sciaky Inc. developed the EBAM and patented [150] the process based on their electron beam welding expertise. Sciaky’s EBAM technique focused on large-scale (19 feet in length) production of high-value metallic parts for aerospace applications [151]. Some of the more traditional processing techniques transformed to a more established DED process from 1990s. For example, Laser Chemical Vapor Deposition (LCVD) was developed in the 1980s, but has now shown potential to build 3D parts, which is called 3D-LCVD micro-additive manufacturing [108]. In this process, a laser beam is focused on the build surface to raise temperature high enough, which thermally decompose a special gas compound introduced in the build chamber. This special gas then deposits half of itself onto the build surface, while the other half combines with a reducing chemical in the air like hydrogen to form a secondary gas compound. LCVD can be utilized efficiently with higher resolution to print micro features including thin coils, highly elastic springs and thin tubes which are applied to make micro-motors [152], microsolenoids, and electromagnets [101, 108]. Three-dimensional welding has its roots in the 1960s in Germany and is now being used in AM [117]. From 2010, researchers have also started to explore the use of cold spray techniques as an alternative to thermal-based DED methods [101, 153]. Today, the DED market has expanded with even more manufacturers. Laser-based DED systems include those being offered by BeAM, Trumpf, Formalloy, DMG Mori, InssTek from Korea and Relativity. In terms of electronbeam DED systems, this technology is being offered by Evobeam GmbH. Finally, Norsk Titanium, WAAM, GEFERTEC, Prodways, and Lincoln Electric utilize plasma arc-based techniques [154]. Today’s DED systems are attached to four or five axis robotic arms that can print complex and curved structures and can automatically switch to milling or CNC integrated systems for post-

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Table 1.3 A chronological history of key DED processes

Discovery Year

Event

1971 • Pierre Ciraud invented a powder blown DED process and system depositing the molten material on a substrate using beam energy to print 3D objects • Frank Arcella patented a method 1989 called Laser Forming of near net shapes 1993 • Vivek Davé from MIT invented the EBF3 process using electron beam energy and wire feed materials 1997 • Frank Arcella in collaboration with Johns Hopkins and Penn State Universities developed Laser Forming process using powder feed nozzle • Sandia National Laboratories 1998 developed the LENS process

Commercialization Year 1997

1998

2001

2009

2013 2015

1998 • Koch and Mazumder from University of Michigan developed the DMD process based on multi-layer Laser Cladding process • NASA developed EBF3 for space 2002 applications

Event • Frank Arcella and his team founded Aeromet to first commercialize their LasForm process • Optomec and Sandia National Laboratories first delivered the LENS process • POM group collaborating with University of Michigan commercialized DMD • Sciaky Inc. developed and commercialized EBAM based on electron beam welding for large aerospace parts production • DM3D LLC acquired the POM’s DMD technology • DMG Mori launched a powder blown hybrid DLD process Lasertec 65 3D integrated with a five-axes milling system

2010 • Scientists found novel DED technology based on cold spray techniques alternative to the fusion based existing DED

processing. For instance, DMG Mori’s hybrid blown powder Direct Laser Deposition (DLD) machine, the LASERTEC 125 3D Hybrid is a developed version of LASERTEC 65 3D Hybrid marketed in 2015, consists of a DED nozzle and equipped with a five-axis milling unit that was introduced in 2019 [155, 156]. These Hybrid CNC-DED systems fully integrate the capabilities of both additive and subtractive manufacturing that can be further exploited to increase productivity and competitiveness in the market. It also offers multi material production capability, high-performing CAM software, and an in-situ process monitoring camera [157]. In general, the application of DED falls in to three categories including Big-Area Additive Manufacturing (BAAM) using high power systems, repair [158], and precision manufacturing with lower power systems. High powered DED systems are suitable in automotive, aerospace, marine and construction applications [159]. The use of DED has gained popularity in the biomedical industry, specifically for dental [160], orthopedic, and cardiovascular [161]

applications. Biocompatible parts that are produced with porous Ti-6Al-4V using LENS can support cell growth of implants and having a pore size of 200 μm or larger [162]. Also, in-vivo biocompatibility studies with porous Ti-6Al-4V processed by DED showed that a pore volume fraction of 0.40 as the upper limit can effectively accelerate the healing process through biological fixation [162]. An emerging application of DED is creating novel alloys and functionally graded structures for its ability to equip with multi feeding systems for mixing of the elemental or alloyed powders [163]. A summary of the discoveries and commercial timeline of DED is shown in Table 1.3.

1.2.4

Material Jetting

In Material Jetting (MJ), particles usually in the form of photopolymer resin, are deposited through an ink-jet technology layer-upon-layer to form high-resolution 3D parts [164]. Material Jetting and its derivatives are known as:

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History of AM

• • • • • •

Aerosol Jet ® (Optomec, Inc.) [128] Ballistic Particle Manufacturing (BPM) [165] Drop On Demand Material Jetting (DODMJ) [166] Laser-Induced Forward Transfer (LIFT) [167] Liquid Metal Jetting (LMJ) [168] Multi-Jet Modelling (MJM by 3D Systems Corporation) [169] Multi-Jet-Printing (MJP by 3D Systems Corporation) [170] Nano Metal Jetting © (XJet [171] NanoParticle Jetting ™ (XJet) [172] PolyJet ® (Stratasys Inc. [173] Printoptical © Technology (Luxexcel) [174] ThermoJet Printing by 3D Systems Corporation [175]

• • • • • •

MJ was developed in 1984, through the concept of Ballistic Particle Manufacturing (BPM) by William E. Masters, also known as Bill Masters [176]. Bill patented his first AM technology as a Computer Automated Manufacturing Process and System (CAMPS) methods in 1987 [177]. He founded the company, Perception Systems Inc. and continued the research and development of the process [165]. Later, he changed the company’s name to BPM Technology Inc. In 1996, he shipped the first BPM machine, Personal Modelers Beta before winding down his business the following year [33, 176]. This technology can also be used to build parts in wax, metal, and ceramic including derivatives such as DODMJ, LMJ, MJM, NanoParticle Jetting, and Nano Metal Jetting. An independent US-based company, Sanders Prototype Inc. developed a 3D wax printer using ink-jet technology to create master molds and patterns for investment casting. Their first machine was made in 1994, known as the ModelMaker that was adopted by the jewelry industry. In 2000, the company was renamed as Solidscape [178] and grew to hone their expertise in pattern making for detailed design of jewelry, expanding its application for the dental industry. Solidscape’s wax printers utilize a Drop-OnDemand (DOD) MJ technology [179] that has evolved with high precision by integrating rotating milling blades [180]. The DOD MJ technology is typically used to produce patterns for lost-wax casting, investment casting and mold making applications [181]. Founded in 2009, Luxexcel also developed a DOD MJ technology that can be used to print optical lenses [182]. In 2017, Luxexcel introduced its platform of industrial grade 3D Printers, lens design software and workflow integration tools which allows for the production of 3D printed ophthalmic quality lenses [183]. The lenses are built in the shape according to the prescription without requiring any polishing. In 2011, Solidscape was acquired by AM market leader Stratasys [33, 184]. In 1996, another AM market leader, 3D Systems, brought the MultiJet-Printing (MJP) [47] process to the masses in which MJP uses a piezo printhead technology

13

to deposit materials ranging from polymers, elastomers, multi-material composites and wax [170]. MJP is also known as MultiJet Modelling (MJM) [169] or ThermoJet Solid Object Printing [175]. ThermoJet’s piezoelectric printhead was three times faster than MJP techniques [185]. In 1996, 3D Systems introduced its first MJ platform, the Actua 2100, which used an inkjet mechanism to directly print wax only materials. This was superseded in 1999 by the 3D Systems ThermoJet platform and evolved into its MultiJet Printing (MJP) process that still exists today and includes photopolymers [184]. In 1998, Israeli company Objet Geometries developed a similar method called PolyJet [186]. PolyJet is similar to the MJP, and they both create high-resolution photopoloymeric parts. However, the printhead design is slightly different from each other depending on the type of material being cast or printed by these technologies. Additionally, the support materials used in PolyJet are different from MJP systems [187]. The first AM machine from Objet was the Quadra platform, which had 1536 nozzles within the printheads to simultaneously print the build material and support material. In 2004, another variation of MJ, Aerosol Jet technology was released by Optomec for printing electronic components. In 2012, Objet merged with Stratasys [188], which led to the Stratasys’ Objet Connex series of AM machines that incorporate multi-material printing using MJ technology. The company markets this as “Digital Materials” that is capable of combining two or more PolyJet photopolymers in specific concentrations to create a composite material with hybrid characteristics. The J750 from Stratasys is able to use a maximum of six materials within a single build with various combinations and has more than 360,000 different color options [184]. A Stratasys’ Objet machine is presented in Fig. 1.4. In 2015, one of the co-founders of Objet established a new company XJet in Israel and announced a novel MJ technology called NanoParticle Jetting (NPJ). NPJ uses a printhead to dispense nano-ceramic particle inks to create a ceramic green part with an enhanced surface finish. NPJ is also known as Nano Metal Jetting (NMJ) that can make fully dense metal parts with a high level of surface quality. XJet utilized the technology “inkjet-printable nanoparticle suspensions” patented by ExOne as a leading expert in Binder Jetting technology [189], in their NPJ systems Carmel 1400M and Carmel 1400C for metal and ceramic printing respectively [190–192]. The current MJ market players include Stratasys, 3D Systems, Indigo, Keyence, and Mimaki from Japan, XYZPrinting from China, XJet, and Xaar [193, 194]. Direct Material Jetting has also been the focus of research at the University of Nottingham. In 2017, researchers at this institution have pioneered a breakthrough method for 3D Printing fully functional electronic circuits that contain electrically conductive metallic inks and insulating polymeric inks using a single inkjet printing process [196]. The University of

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Fig. 1.4 Stratasys Objet 30 Prime rapid-prototyping MJ machine at UBRUN, with excellent print quality and able to print flexible rubber-like materials [195]

Table 1.4 A chronological history of key MJ processes

Discovery Year

Event

1987 • William E. Masters first developed MJ technology known as BPM 1987 • William E. Masters was awarded a patent for his discovery of the BPM 1998 • Israel-based company Objet developed PolyJet technology using photopolymers

Commercialization Year

Event

1994 • US company Sanders Prototype Inc. (later known as Solidscape) launched the 3D wax-based inkjet technology called the ModelMaker 1996 • William E. Masters after founding BPM Technology Inc. shipped the first BPM machine, Personal Modelers Beta

2012 • Stratasys released Objet Connex for first multimaterial ink-jet printer

• 3D Systems introduced the MJP to market

2015 • Israel based XJet introduced a novel MJ technique known as NPJ

1999 • 3D Systems introduced TJP which uses a piezoelectric printhead for faster printing

2017 • University of Nottingham developed DMJ for conductive electric circuits • Xaar collaborated with the global chemical company BASF to develop low-cost MJ photopolymer technology 2020 • Fraunhofer IKTS developed MMJ for ceramic parts based on DOD

• Objet’s ProJet printer Quadra platform with 1536 nozzles that could print build and support materials together is launched 2011 • Solidscape was acquired by AM market leader Stratasys 2012 • Objet merged with Stratasys and releases Stratasys’s Objet Connex for multi-materials printing 2017 • Luxexcel released the DOD MJ process for printing ophthalmic quality lenses

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History of AM

15

Nottingham is also part of a collaborative project that started in 2015, with Canon Production Printing (formerly Océ, specializing in printheads) and the Atomic Weapons Establishment (AWE) to develop a bespoke multi-metal MJ technique known as MetalJet printing [184, 197]. In 2017, UK-based company Xaar that specializes in industrial inkjet printheads, announced a collaboration with global chemical company BASF to promote research and development regarding the MJ process for photopolymers, specifically to improve material properties and lower costs for industrial part manufacturing [184]. In 2020, a team from the Fraunhofer Institute for Ceramic Technologies and Systems (IKTS) revealed a novel Multi Material Jetting (MMJ) system that was able to combine multiple materials into a single additively manufactured part. Based on thermoplastic binder systems, MMJ utilizes highperformance materials such as ceramics and metal, combining different materials and their various properties into a single product. The material slurry is first loaded onto a microdosing system (MDS) to commence the manufacturing process. The slurry is then melted in the MDS at a temperature of around 100 degrees Celsius to enable the substance to be released in tiny droplets [48, 198]. A corresponding software ensures that the precise positioning of the droplets are deposited one by one via a high-precision, computer-controlled process. Gradually, the part is built up at rates of up to 60 mm and 1000 drops a second. The system works with droplet sizes of between 300 and 1000 μm, creating deposited layers with heights of between 100 and 200 μm. The maximum size of parts that can currently be manufactured is 20
20
18 cm3 [199, 200]. A summary of key chronological facts of MJ is shown in Table 1.4.

a)

1.2.5

Material Extrusion

The Material Extrusion (MEX) process involves using a filament material that is selectively deposited through a nozzle or orifice [201]. MEX and its derivatives are also known as: • Extrusion (Solid) Freeform Fabrication (EFF) [202–204] • Freeze-form Extrusion Fabrication (FEF) [205] • Fused Deposition Modeling (FDM ® by Stratasys Inc.) [206] • Fused Filament Fabrication (FFF) [207] • Glass 3D Printing (G3P) [208] • Liquid Deposition Modeling (LDM) [209] • Direct Ink Writing (DIW) [210, 211] • Micropen Writing [212] • Plastic Jet Printing (PJP by 3D Systems Corporation) [213] • Robocasting or Robotic Deposition [214, 215] MEX was invented in 1988 by Scott Crump based on the use of candle wax and a hot glue gun while he was making a toy. He subsequently named the process Fused Deposition Modelling (FDM) [216] and in the following year, Scott founded the company Stratasys and filed a patent based on this process [206]. In 1992, Stratasys launched their first automated FDM machine called the 3D Modeler [217, 218]. An example of a Stratasys MEX machine is shown in Fig. 1.5. Sandia National Laboratories also developed another method known as Robocasting that could deposit ceramic slurry in layers through an orifice. The method was patented in 1997 [214] that eliminates the requirement of molds and

b)

Fig. 1.5 Stratasys Dimension Elite machine at UNIZAG-FSB, useful for prototyping printing fine detail in medical and electronic application (a) [36], Markforged Mark Two industry-grade MEX machine for printing composite materials at AIDIMME (b) [35]

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dies to fabricate ceramic parts, making it faster and more cost effective than traditional processes [215]. Taking advantage of Stratasys’s FDM patent that expired in 2005, Adrian Bowyer at the University of Bath in the UK initiated the RepRap project (Replicating Rapid Prototyper) [207]. His team worked to promote the ME process and to make the technology available more widely. They called the process Fused Filament Fabrication (FFF) and created an opensource FFF machine that was capable of printing parts of the machine to replicate itself. The first printer, known as RepRap 1 “Darwin” was produced in 2007. The “parent” machine was then used to replicate other parts, resulting with the RepRap 2 “Mendel” that was released in 2008. This event inspired companies worldwide to also design and fabricate their own ME machines. Several companies such as MakerBot from the USA, and Bits from Bytes from the UK emerged through this period. MakerBot was founded in 2009 and became the largest entry-level MEX machine producer that eventually merged with Stratasys in 2013. Other machines those were also launched from other suppliers include Prusa i3, Hangprinter, RepRap Fisher, Snappy, Morgan, Ormerod. These were developed when the original patent expired, widening access to MEX technology for amateurs. The F410 is another MEX printer for business and education, developed by US-based company Fusion3 and founded in 2012. The machine costs $4999 US dollars with a fast print speed of 250 mm/s and achieving a print tolerance of 0.003 inch with a 20 μm layer resolution [219]. MEX is often used to produce thermoplastic parts although other materials such as metals [209], ceramics [205, 214], clay [220], wood [221], composites [209, 222]

and biomaterials [202] have been used. In 1995, Fraunhofer Institute for Applied Materials Research (IFAM) developed a MEX process called Multiphase Jet Solidification (MJS) to fabricate metallic and ceramic parts. MJS uses low-melting point alloys or a powder-binder mixture that is extruded using an automatic nozzle system to print a green part, followed by debinding and sintering [223]. Similar systems were developed, for example, in 2000 by Rutgers University in New Jersey, to print multi-material ceramic parts for actuators and sensors by laying up green ceramic rods [224, 225]. A collective effort from Drexel University, Philadelphia and Technical University of Denmark in 2005 [226] and Politecnico di Milano, Italy in 2015 [227] developed separate MEX systems introducing extruders with the nozzles to print metal or ceramic parts from granules or pellets. In the same year, MIT released its MEX system that is able to produce transparent parts made up of glass [208]. Another ceramic-based MEX method is Freeze-Form Extrusion Fabrication (FEF) that uses a paste ceramic feedstock to print 3D parts [205]. The process was developed at Missouri University of Science and Technology, that led to the launch of Rolla in 2000, based on the Rapid Freeze Prototyping technique [228, 229]. Liquid Deposition Modelling (LDM) is another form of MEX that can print various types of materials including clay, ceramics, composites [230], wood [221], edible materials [231] and biomaterials [232]. This technology [233] has inspired many manufacturers such as Eponymous Architecture in Italy to launch its ClayXYZ in 2017, Dutch manufacturer VormVrij’s LUTUM V4 ceramic printer in 2018 [234], and Italian company WASP that offers large scale ceramic 3D Printing for construction [235].

Table 1.5 A chronological history of key ME processes Discovery Year

Event

1988 • Scott Crump invented the FDM process 1995 • Fraunhofer IFAM developed MJS for metals and ceramic printed parts 1997 • Sandia National Laboratories developed Robocasting 1998 • Carnegie Mellon University developed a hybrid ME technique SDM with CNC/Milling for ceramics 2005 • Adrian Bowyer and his team from University of Bath, UK developed FFF as an open-source ME technique 2015 • MIT researchers developed and patented the method and apparatus for the ME of glass

Commercialization Year

Event

1989 • Scott Crump started Stratasys and filed a patent for FDM 1992 • Stratasys launched its first FDM system 3D Modeler 2007 • The first ME rapid prototyping printer RepRap 1 ‘Darwin’ is released 2009 • MakerBot founded to develop and launch affordable ME printers 2013 • Arburg Freeformer was launched by the German company Arburg Additive that print parts from plastic granules using droplet mechanism 2017 • Eponymous Architecture Firm launched ClayXYZ 3D Printer can print clay materials for art and architecture

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History of AM

MEX has been widely adopted for fabricating meso and micro structure parts [211]. For instance, Direct Ink Writing (DIW) [210], Micropen Writing/ Micropenning uses paste as the feedstock instead of ink [236]. DIW is from the family of Robocasting developed by the Sandia National Laboratories in 1996, which uses a slurry-based ink to print generally ceramic materials [237]. However the DIW implementation in developing micro structures can be traced back to early 1996 by a Japanese researcher, Makoto Fukushima [238]. Over the time, the DIW technique grew and now is being used in printing multi-material 3D patterns and microelectronic applications [239]. As such, the Micropenning system was developed and commercialized by Ohmcraft Inc. in 2004 [240] to print resisters. In 1998, hybrid MEX systems that integrate CNC or milling was proposed and tested at Carnegie Mellon University and they called this Shape Deposition Manufacturing (SDM) [241–243]. However, the process was expensive and slow due to the alternate number of steps required for deposition and shaping involved. In 2015, some commercial providers proposed their MEX systems that could be adapted for metals and composites. For example, MetalX by Markforged (shown in Fig. 1.5) [244] and ExAM by AIM3d [222] with its Composite Extrusion Modelling (CEM) have been made available in the market. Investing substantial time in R&D from 2004, Arburg Additive introduced a novel MEX technique, known as ARBURG Plastic Freeforming (AKF). They introduced the industry-grade machine ARBURG Freeformer in 2013 and developed it further in 2017. Having 65 years of experience in injection molding, Arburg developed a process that is able to print the plastic parts by depositing droplets precisely using the granules as feedstock and it can print two materials simultaneously [245, 246]. A summary of the commercial timeline of MEX is shown in Table 1.5.

1.2.6

Sheet Lamination

In Sheet Lamination (SL), sheets of material are bonded together to form a part layer-by-layer followed by a shaping process [247]. SL and its derivatives include: • Computer-Aided Manufacturing of Laminated Engineering Materials (CAM-LEM) [248] • Laminated Object Manufacturing (LOM) [249] • Plastic Sheet Lamination (PSL by Solidimension Ltd.) [250] • Selective Deposition Lamination (SDL by Mcor Technologies Ltd.) • Stratoconception [251] • Ultrasonic Additive Manufacturing (UAM) [252] • Ultrasonic Consolidation (UC) [253] One of the common SL processes is Laminated Object Manufacturing (LOM). The LOM process was first

17

developed by Michael Feygin and patented in late 1980s [254–257] followed by founding a company named Helisys. In 1991, they started selling a machine that could make 3D parts using rolls of paper and a CO2 laser cutter [33]. The company eventually folded and later was reformed as Cubic Technologies. In 1999, a company from Israel called Solidimension (now Solido 3D) developed a system very similar to LOM using sheets of PVC plastic rather than paper [33]. Solido 3D Printers are based on the use of Plastic Sheet Lamination (PSL) and is able to produce parts made with a combination of Poly Vinyl Chloride (PVC) and a proprietary adhesive that results in rugged, yet inexpensive models [250, 258]. In 1999, a company in the USA called Solidica (now Fabrisonic) patented a new hybrid method [259] that used metal tapes and films joined using ultrasonic vibration, and then transferred to a CNC machine to remove surplus material. The process was called Ultrasonic Consolidation (UC) or Ultrasonic Additive Manufacturing (UAM) invented and patented by Dawn White [259, 260]. Solidica first sold its commercial UAM equipment called the Formation Machine Suite. Around 2007, the Edison Welding Institute (EWI) and Solidica started a collaboration to redesign the weld tooling to remedy the bond quality limitations and to expand the availability of weldable metals for the process through very high powered UAM [261]. In 2011, Fabrisonic LLC was formed to commercialize the improved UAM process, known as the Sonic Layer Machine Suite [262]. This process allows flexibility to combine dissimilar materials to produce functionally graded structures, creating internal cooling channels in structures, or to embed electronics or sensors into a part. In 2005, Japanese company Kira started production of a paper-based LOM machine called the PLT-20 KATANA but using a steel cutter rather than a laser. The Selective Deposition Lamination (SDL) process was invented in 2003 by Dr. Conor and Fintan MacCormack as brothers. The MacCormacks wanted to address the soaring prices of 3D Printers by using accessible materials, supported by an affordable AM process with a low operating cost. The result was SDL and their vision to make 3D Printing accessible to all was achieved in the founding of Mcor Technologies. In 2008, Mcor Technologies launched their first SDL machine called the Matrix that deposited individual sheets of A4 paper rather than rolls of paper and selectively glued those sheets that was then cut using a steel cutter. This process allowed Mcor to later develop full-colored parts by printing on the paper before being glued down. Mcor Technologies developed three 3D Printers – the Mcor IRIS, Mcor ARKe, and Matrix 300+  all of which utilize the SDL process. The Mcor IRIS was the world’s first full-color SL printer while the Mcor ARKe was the world’s first full-color desktop SL printer. The Matrix

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300+ can only print white 3D models [263]. Figure 1.6 shows an Mcor IRIS machine. A novel laminated rapid tooling process called Stratoconception [265] was also developed and patented by C. Barlier much earlier in 1991. This process exhibited potential in making various forming and casting dies including cooling channels of complex shapes [266]. The latest developments of SL are able to utilize carbon fiber sheets

Fig. 1.6 Photograph of Mcor IRIS True Color SL machine, Mcor opened it to public in 2012 but now stopped production. (Photo credit: Creative Tools from Flickr.com) [264]

and various composites and these techniques are still being honed by their manufacturers and not yet widely available. Such SL processes are also known as Computer-Aided Manufacturing of Laminated Engineering Materials (CAM-LEM) developed at Case Western Reserve University in Ohio with the collaboration of CAM-LEM Inc. around 1995 [267, 268], Selective Lamination Composite Object Manufacturing (SLCOM) developed by a German company EnvisionTEC around 2016 [269], and later a US company Impossible Objects that developed Composite Based Additive Manufacturing (CBAM) in 2017 with its pilot 3D Printer called Model One [270]. CAM-LEM Inc. uses the SL process to form functional ceramic parts, specializing in microfluidic devices and applications. In this approach, individual layers are formed, then stacked and bonded together, exemplifying the “cut then stack” approach. This reduces the amount of material needed to bond the layers together, but also limits the geometries that can be built because such layers must be stackable on top of one another. For instance, it is difficult to produce overhang features if there is nothing in the layer underneath to support the new layer [271]. In 2016, Giant Composite Prints designed the SLCOM 1 that uses engineering-grade thermoplastics and industrial composites. The feedstock for the SLCOM consists of rolls of unidirectional or multidirectional woven composites, such as Carbon Fiber, Kevlar or fiberglass that are

Table 1.6 A chronological history of key SL processes

Discovery Year

Event

Commercialization Year

Event

1988 • Michael Feygin invented LOM using paper roll and laser cutter

1991 • Helisys (Now Cubic Technologies) was formed to market the first paper-based LOM machine with a laser cutter

1991 • Laminated rapid tooling process Stratoconception was developed and patented by C. Barlier

1994 • Kira Corp. from Japan commercialized Solid Centre, a paper-based LOM machine with a steel cutter

1999 • Dawn White invented and patented the UC process 2003 • Mcor Technologies launched the SDL method, a low-cost SL using sheets of paper 2017 • Impossible Objects developed a pilot CBAM printer Model One

1999 • Israel-based Solidimension developed a similar LOM system for PVC plastic laminated parts • Dawn White started Solidica (Now Fabrisonic LLC) and commercialized their first UC machine, Formation Machine Suite • Fabrisonic LLC developed a hybrid LOM machine integrated with a CNC system using metallic foil to print laminated parts 2011 • Fabrisonic LLC developed a hybrid LOM machine integrated with a CNC system using metallic foil to print laminated parts 2016 • Composite Prints designed the SLCOM 1 based on EnvisionTEC's SLCOM to print with engineeringgrade composite parts bonded with thermoplastic materials

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pre-impregnated with thermoplastics, including Nylon 6, Nylon 11, Nylon 12, PEEK, PEKK, Polycarbonates and more [269]. These composite matrix materials deliver high quality parts suitable for use in aerospace, automotive, consumer products, sporting goods, and for medical use [272]. A summary of the commercial timeline of SL is shown in Table 1.6.

1.2.7

Binder Jetting

Binder Jetting (BJ) is an AM process of depositing powder materials followed by printing binder agents selectively onto the powder bed in layers forming a complex green part [273]. The green part is sent for further post processing to obtain the final part. Binder Jetting and its derivatives are also known as: • • • • • • • • • •

1

3D inkjet powder printing (3DIJPP) [274] ColorJet Printing (CJP by 3D Systems Corporation) [275] Digital Metal ® by Höganäs AB [276] Metal Jet Printing [277] Plaster-based 3D Printing (PP) [278] Polymer High Speed Sintering (HSS) and PolyPor C (PPC) [279] Powder Bed and Inkjet Head 3D Printing (PBIH) [280] Single Pass Jetting [281] Three Dimensional Printing (3DP) [282, 283] ZPrinting ® by 3D Systems Corporation [284, 285]

Emanuel (Ely) Sachs and Michael Cima from MIT first developed the BJ process based on ink-jet technology in 1989. They patented the process and termed this process as Three-Dimensional Printing (3DP) for tooling and prototyping in 1994 [286, 287]. Since then, the BJ process has become synonymous with the term 3D Printing, until it was later adopted as a general term that referred to all AM processes. Soligen was the first company to receive the exclusive license of MIT’s BJ in 1991 that was used in Direct Shell Production Casting [33]. It uses sand or ceramic powder to produce casting molds for the metal-casting industry [288]. A similar ceramic-based BJ system, Ceramo One was developed by a Ukrainian company, Kwambio [289]. In 1994, Z Corporation (Z Corp) was founded and they commercialized MIT’s BJ process, marketing this technology as ZPrinting. Their first printer Z402 was launched in 1996 by Z Corp [284], which produced prototypes using starch, plaster-based materials, and water-based binder. Hence, this process was also called plaster-based 3D Printing (PP). Z Corp continued to develop their BJ process and introduced the world’s first multi-colored BJ technology Z402C. A Z Corp machine is shown in Fig. 1.7. Later in 2005, they offered a highdefinition solution, Spectrum Z510, for color printing with

Fig. 1.7 A Z Corp Spectrum Z510 BJ machine at LTH, this is a highdefinition color 3D printer first commercialized in 2005 for rapid prototyping [66]

a larger build volume. In the same year, Z Corp was sold to a Danish company Contex Scanning Technologies and later in 2011, was acquired by 3D Systems. A German start-up that emerged from the Technical University of Munich, known as Voxeljet (formerly Generis GmbH) established itself in the BJ market for 20 years since 1999. Their technology was patented in 1998 [290–293] and the company launched their first sand-based BJ machine in 2002 for investment casting applications. Starting from their VX800 machine, the company has been continuously innovating and the VX4000 machine that was launched in 2011, has the capacity to print parts of 4
2
1 m3 [279]. Other developments of BJ include Voxeljet’s High Speed Sintering, PolyPor C plastic processes [294], and Hybrid processes for investment casting molds and cores [295]. Moving forward, Extrude Hone, a global supplier of machining and automation systems, received an exclusive license of MIT’s BJ technique in 1996 for printing metal, ceramic, and sand materials. In 1998, they commercialized their first metal BJ technology ProMetal RTS-300, and it was installed at Motorola’s factory. That was a novel technology at that time which was able to produce metallic green parts by printing binder into a powder bed of metal particles followed by debinding and sintering. Extrude Hone then expanded their knowledge in indirect printing and entered the sand printing market in 2002 and launched S10 for manufacturing metal casting molds and cores. Immediately, they went into licensing agreement with Genesis GmbH (which was later known as Voxeljet) continuing a collaborative development of the sand BJ technology. Later in 2005, Extrude Hone was sold to a global supplier of machine tool and industrial materials, Kennametal, and became an independent 3D

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Printing venture, ExOne Company LLC. Since then, ExOne has lead the frontline for direct and indirect BJ printing technologies for metal, ceramic, sands, and composite materials dedicated to mainly tooling and dental industries [296]. CeraNova, TDK Corporation and Therics Inc. are other users of MIT’s BJ process for electronic and pharmaceutical applications [297, 298]. Digital Metal, a subsidiary of Swedish metal powder producer Höganäs Group, took the BJ process further by focusing on precision metal AM parts. The unit was founded in 2012 and started offering metal BJ processes. In 2017, it launched the DM P2500 BJ printer, for series production of small, complex parts with a maximum resolution of 35 μm [299]. In the following year, they introduced fully automated production using a robot to handle most of the processing steps including feeding, part removal and post processing to aid a high throughput. Desktop Metal that was founded in 2015, developed a desktop version of the BJ process in 2017 known as the Studio System [300]. In the same year, they launched the Production System based on a Single Pass Jetting (SPJ) technology, claiming it to be the world’s fastest BJ process [301]. The P-50 Production System printer has a

consolidated carriage to support all key BJ steps including feeding, laying-up powders, printing, drying and curing binders to produce one single layer of the building block of a strong green part in 3 s [281]. The forefather of the BJ process, Ely Sachs from MIT is one of the co-founders of Desktop Metal. 3D Systems, a pioneer company of the VPP process, commercialised ColorJet Printing (CJP) in 1993, though it released its first CJP machine in 2013. The ProJet CJP x60 family is based on the color BJ process originally developed by Z Corp [33, 43, 302]. Their ProJet CJP machines deliver fast and high-definition monochrome for full-color CMYK parts with good scalability [275, 303]. HP Metal Jet is a BJ technology [277] based on the architecture of their polymerbased PBF technique, Multi Jet Fusion (MJF). The Metal Jet Printing technique was revealed in September 2018 by HP, with the aim of mass production with 50 times more productivity than other metal AM techniques. This process is a voxel-based BJ process with a build volume of 430
320
200 mm3 that is able to produce green parts [304]. A summary of the commercial timeline of BJ is shown in Table 1.7.

Table 1.7 A chronological history of key BJ processes

Discovery Year

Event

1989 • Emanuel Sachs and Michael Cima from MIT invented 3DP BJ process

Commercialization Year 1994

• Z Corporation was founded

1996

• Z Corporation launched the first plaster based ZPrinting machine Z402

1993 • 3D Systems developed CJP based on Z Corp printer

• Extrude Hone, later known as ExOne, received an MIT license to develop BJ for metal, ceramic, and sand casting

1998 • Extrude Hone developed metal BJ technology • Voxeljet spun-off from Technical University of Munich patented a sand-based BJ process 2002 • Extrude Hone developed sandbased BJ technique for printing casting molds • Swedish company Digital Metal 2012 developed BJ technology for precision metal parts

Event

1999

• Voxeljet company was founded, formerly known as Generis GmbH

2000

• Z Corp launched the world's first multicolor BJ printer Z402C

2003

2011

2015 • Desktop metal was founded and first developed desktop version of BJ technology

2013

2018 • HP developed voxel-based metal BJ technology Metal Jet Printing

2017

• ExOne and Voxeljet made licensing agreement in developing sand-based BJ technologies • Voxeljet launched a large build envelop printer that could print parts of 4x2x1 m with the VX4000 • 3D Systems launched the CJP printer with monochrome and CMYK prototyping • Desktop Metal launched a desktop BJ system known as the Studio System

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History of AM

1.3

21

Summary

Some scholars claimed that the idea of AM and 3D Scanning emerged in the mid-nineteenth century through the application of photography, photo-sculpting and cartography that gained the interest of the US Army in aiding operational knowledge of the local conditions. However, the growth of these techniques remained limited due to its analogue system and the absence of digital technologies. Nevertheless, the relentless efforts by researchers to discover new methods and companies seeking to commercialize these products pushed AM technology toward its digital transformation. Earlier on, Munz’s work revealed that the idea of Stereolithography, a VPP process, was an analogue approach developed as early as 1956. AM as a potential manufacturing process finally kicked off in 1976 by DiMatteo’s analogue method that was used for mold making. With the advent of digital innovation and the development of lasers, AM soon became a fully automated and an industrialized manufacturing process. Swainson, Ciraud, Housholder, and Kodama in the 1970s and 1980s pushed the technology further forward. They developed both photo-chemical and powder-bed-based techniques using non-metals and metals for tooling, prototyping, and repair. In the 1980s, the development of industrial AM took a step further with Charles W. Hull’s work resulting in the first commercial and fully digital Stereolithography machine. Hull patented his work in 1986 and founded a company 3D Systems to launch the SLA-1 in 1987. Figure 1.8 shows the first introduction and product commercialization timeline for all seven AM processes. The figure shows that the most active period in history and most of the commercialization activities started in the 1980s. This wave remained high until the early millennium and the USA, Japan, Germany, Israel, France, China, and the UK were leading countries that contributed to the growth and development of this disruptive manufacturing process. Several

Discovery

2025

Year

Acknowledgement The authors acknowledged the support from the European Commission funded project INEX-ADAM (Increasing Excellence on Advanced Additive Manufacturing) grant no. 810708. The authors are grateful to the project consortium members: UNIZAG-FSB, UBRUN, AIDIMME, LTH, and MUL for granting permission to utilize some of the images of their AM systems.

Commercialisation

References

2010 1995 1980 1965 1950

companies spawned out of this movement. Some of them sustained and grew throughout the years and others dissolved. From the year 2000 onwards, more companies emerged with innovative applications, materials, and equipment. Hybrid AM technologies emerged over time to increase its production capacity and improve the quality and reliability of the parts by integrating conventional manufacturing techniques such as CNC, milling, rolling processes with AM. It is worth noting that the commercialization process often did not take place straight after their discovery. It was down to the fact that feedstock material such as polymers, metals, and ceramics for AM was only later made more widely available by researchers. Interestingly, the commercial growth of PBF systems was quickly realized because of the foundations laid by VPP as the core principle in printing 3D objects using laser beam energy that was almost similar, except the fact that VPP uses a resin in a reservoir and PBF uses a bulk powder bed. Moreover, the need for repair and custom part production for aerospace also encouraged PBF and DED techniques to grow. The concept of DED started at the beginning of the twentieth century through fusion welding and coating technologies such as Laser Cladding. Researchers further developed the idea of shape welding to produce 3D objects layer-by-layer. For other processes, developments in the feeding mechanism, increased speed, in-situ monitoring, and improved surface finish gave rise to the popularity of MJ and BJ. Introducing a standard printhead offered faster production and a better surface finish of the printed 3D objects. Although these AM processes have seen technological developments over the past few decades, even more discoveries are still being told each year.

VPP

DED

PBF MJ ME AM processes

SL

BJ

Fig. 1.8 The first emergence and commercialization of the seven AM processes

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25 electrochemical processes. Precis. Eng. 68, 174–186 (2021). https://doi.org/10.1016/j.precisioneng.2020.12.013 153. Bagherifard, S., Roscioli, G., Zuccoli, M.V., Hadi, M., D’Elia, G., Demir, A.G., Previtali, B., Kondás, J., Guagliano, M.: Cold spray deposition of freestanding inconel samples and comparative analysis with selective laser melting. J. Therm. Spray Technol. 26, 1517–1526 (2017). https://doi.org/10.1007/s11666-017-0572-3 154. Carlota, V.: The complete guide to Directed Energy Deposition (DED) in 3D printing. https://www.3dnatives.com/en/directedenergy-deposition-ded-3d-printing-guide-100920194/ 155. Directed energy deposition - DED, LENS, EBAM. https://make. 3dexperience.3ds.com/processes/directed-energy-deposition 156. Essop, A.: DMG MORI launches LASERTEC 125 3D hybrid additive manufacturing machine. https://3dprintingindustry.com/ news/dmg-mori-launches-lasertec-125-3d-hybrid-additivemanufacturing-machine-165822/ 157. O’Neal, B.: Lasertec 125: DMG Mori releases new 3D hybrid system for maintaining & repairing parts. https://3dprint.com/ 260887/lasertec-125-dmg-mori-releases-new-3d-hybrid-systemmaintaining-repairing-parts/ 158. Saboori, A., Aversa, A., Marchese, G., Biamino, S., Lombardi, M., Fino, P.: Application of directed energy deposition-based additive manufacturing in repair. Appl. Sci. 9, 3316 (2019). https://doi.org/ 10.3390/app9163316 159. Nassar, A.R.: Directed energy deposition: Applications and outlook. https://www.laserfocusworld.com/industrial-laser-solutions/ article/14222011/directed-energy-deposition-applications-andoutlook 160. Koike, M., Martinez, K., Guo, L., Chahine, G., Kovacevic, R., Okabe, T.: Evaluation of titanium alloy fabricated using electron beam melting system for dental applications. J. Mater. Process. Technol. 211, 1400–1408 (2011). https://doi.org/10.1016/j. jmatprotec.2011.03.013 161. Cui, Z., Yang, B., Li, R.-K.: Application of biomaterials in cardiac repair and regeneration. Engineering. 2, 141–148 (2016). https:// doi.org/10.1016/J.ENG.2016.01.028 162. Xue, W., Krishna, B.V., Bandyopadhyay, A., Bose, S.: Processing and biocompatibility evaluation of laser processed porous titanium. Acta Biomater. 3, 1007–1018 (2007). https://doi.org/10.1016/j. actbio.2007.05.009 163. Ahn, D.-G.: Directed energy deposition (DED) process: state of the art. Int. J. Precis. Eng. Manuf. Technol. 8, 703–742 (2021). https:// doi.org/10.1007/s40684-020-00302-7 164. Silbernagel, C.: Additive Manufacturing 101-4: What is material jetting? http://canadamakes.ca/what-is-material-jetting/ 165. Masters, W.E.: System and method for computer automated manufacturing using fluent material. https://patents.google.com/ patent/US5134569A/en (1992) 166. Fayazfar, H., Liravi, F., Ali, U., Toyserkani, E.: Additive manufacturing of high loading concentration zirconia using highspeed drop-on-demand material jetting. Int. J. Adv. Manuf. Technol. 109, 2733–2746 (2020). https://doi.org/10.1007/s00170020-05829-2 167. Visser, C.W., Pohl, R., Sun, C., Römer, G.-W., Huis in ‘t Veld, B., Lohse, D.: Toward 3D printing of pure metals by laser-induced forward transfer. Adv. Mater. 27, 4087–4092 (2015). https://doi. org/10.1002/adma.201501058 168. Priest, J.W., Smith, C., DuBois, P.: Liquid metal jetting for printing metal parts. In: 8th International Solid Freeform Fabrication Symposium (1997) 169. Chae, M.P., Rozen, W.M., McMenamin, P.G., Findlay, M.W., Spychal, R.T., Hunter-Smith, D.J.: Emerging applications of bedside 3D printing in plastic surgery. Front. Surg. 2 (2015). https:// doi.org/10.3389/fsurg.2015.00025 170. MultiJet Printing. https://uk.3dsystems.com/resources/informa tion-guides/multi-jet-printing/mjp

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26 171. Islam, R., Sadhukhan, P.: An insight of 3d printing technology in pharmaceutical development and application: an updated review. Curr. Trends Pharm. Res. 7 (2020) 172. XJet Carmel 1400M Optimal metal AM system. https://www. xjet3d.com/products/metal-systems/ 173. Make it more realistic and accurate with PolyJet. https://www. stratasys.com/polyjet-technology 174. Luxexcel’s 3D printed prescription lenses for smart glasses. https:// www.luxexcel.com/ 175. Brooks, R.: The new model for investment casting. https://www. foundrymag.com/molds-cores/media-gallery/21931994/the-newmodel-for-investment-casting 176. Masters, W.E.: The father of 3D printing. https://billmasters3d. com/father-of-3d-printing/ 177. Masters, W.E.: Computer automated manufacturing process and system. https://patents.google.com/patent/US4665492 (1987) 178. Sanders Prototype, Inc. Changes Name to Solidscape ®, Inc. https:// www.solidscape.com/news/sanders-prototype-inc-changes-nameto-solidscape-inc/ 179. Amelia, H.: What are the material jetting 3D printers on the market? https://www.3dnatives.com/en/what-are-the-material-jet ting-3d-printers-available-290420215/ 180. 3D Printing and Casting for Jewelry Professionals. https://www. solidscape.com/ 181. Systèmes, D.: Material jetting - MJ, NPJ, DOD. https://make. 3dexperience.3ds.com/processes/material-jetting 182. Sher, D.: Getting the “insights” at Luxexcel, the only company that can 3D print ophthalmic lenses. https://www.3dprintingmedia. network/getting-the-insights-at-luxexcel-the-only-company-thatcan-3d-print-ophthalmic-lenses/ 183. Hale, M.: 3D printing: Bespoke lens breakthrough. https://www. opticianonline.net/features/3d-printing-bespoke-lens-breakthrough 184. Park, R.: The evolution of material jetting 3D printing. https://blog. grabcad.com/blog/2017/12/04/evolution-material-jetting-3dprinting/ 185. Express Pattern: ThermoJet printer. https://www.aerospaceonline. com/doc/thermojet-printer-0001 186. Gothait, H.: Apparatus and method for three dimensional model printing. https://patents.google.com/patent/US6259962B1/en (2001) 187. PolyJet vs MultiJet Printing (MJP). https://facfox.com/docs/kb/ polyjet-mjp-comparison 188. Stratasys, I.: Stratasys and objet agree to combine to create a leader in 3D printing and direct digital manufacturing. https://investors. stratasys.com/news-events/press-releases/detail/120/stratasys-andobjet-agree-to-combine-to-create-a-leader-in 189. Bai, J.A., Creehan, K.D., Kuhn, H.A.: Powder particle layerwise three-dimensional printing process. https://patents.google.com/ patent/US10040216B2/en (2018) 190. Gibson, I., Rosen, D., Stucker, B.: Material jetting. In: Additive Manufacturing Technologies, pp. 175–203. Springer, New York (2015) 191. Bai, J.G., Creehan, K.D., Kuhn, H.A.: Nanoparticle suspensions for use in the three-dimensional printing process. https://patents. google.com/patent/WO2009017648A1/en (2009) 192. Davies, S.: XJet updates product line as it prepares to showcase metal and ceramic 3D printing systems at Formnext. https://www. tctmagazine.com/additive-manufacturing-3d-printing-news/xjetupdates-product-line-as-it-prepares-to-showcase-metal-a/ 193. About XJet. https://www.xjet3d.com/about-us/ 194. Industry Growth Insight: Material jetting 3D printing market report. North America, Europe, APAC, Latin America, MEA (2020) 195. Pei, E., Kabir, I.R.: Data mapping for UBRUN (confidential). Increasing Excellence in Advanced Additive Manufacturing

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28 257. Feygin, M., Pak, S.S.: Apparatus for forming an integral object from laminations. https://patents.google.com/patent/US5637175A/ en (1997) 258. Dassault Systèmes: Sheet lamination - LOM, SL. https://make. 3dexperience.3ds.com/processes/sheet-lamination 259. White, D.: Ultrasonic object consolidation. https://patents.google. com/patent/US6519500B1/en (2003) 260. White, D.R.: Ultrasonic consolidation of aluminum tooling. Adv. Mater. Process. 64–65 (2003) 261. Graff, K.F., Short, M., Norfolk, M.: Very high power ultrasonic additive manufacturing (VHP UAM) for advanced materials. In: 21st Solid Freeform Fabrication Symposium. University of Texas at Austin, Austin (2010) 262. Company-Who are we?. https://fabrisonic.com/company/ 263. What is Selective Deposition Lamination (SDL)?. https://www. additive-x.com/blog/selective-deposition-lamination-sdl/ 264. Creative Tools: Mcor Paper 3D printer v01. https://www.flickr. com/photos/creative_tools/14964236450/in/photolist-oNkC9JoNkC9U-p5QoMp-oNkCdG 265. Stratoconception process. https://www.cirtes.com/en/technologies/ stratoconception/ 266. Thabourey, J., Barlier, C., Bilteryst, F., Lazard, M., Batoz, J.-L.: Stratoconception contribution for rapid tooling in die casting: from the design to experiments. Adv. Prod. Eng. Manag. 5, 121–133 (2010) 267. Mathewson, B.B., Newman, W.S., Heuer, A.H., Cawley, J.D.: Automated fabrication of ceramic components from tape-cast ceramic. In: 6th International Solid Freeform Fabrication Symposium. The University of Texas at Austin (1995) 268. Wei, T., Choi, S., Newman, W.S.: Development of a sheet-based material handling system for layered manufacturing. In: Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), pp. 1352–1357. IEEE 269. Molitch-Hou, M.: EnvisionTEC blows up RAPID with mega composite 3D printer and more. https://www.engineering.com/story/ envisiontec-blows-up-rapid-with-mega-composite-3d-printer-andmore 270. All About Sheet Lamination/Laminated Object Manufacturing (LOM) 3D Printing. https://www.thomasnet.com/articles/engineer ing-consulting/laminated-object-manufacturing-3d-printing/ 271. Simpson, T.W.: Additive manufacturing with sheet lamination. https://www.compositesworld.com/articles/additive-manufactur ing-with-sheet-lamination(2) 272. Selective Lamination Composites Object Manufacturing (SLCOM 1). EnvisonTec 273. Silbernagel, C.: Additive Manufacturing 101-1: What is binder jetting? http://canadamakes.ca/what-is-binder-jetting/ 274. Barui, S., Panda, A.K., Naskar, S., Kuppuraj, R., Basu, S., Basu, B.: 3D inkjet printing of biomaterials with strength reliability and cytocompatibility: quantitative process strategy for Ti-6Al-4V. Biomaterials. 213, 119212 (2019). https://doi.org/10.1016/j.biomaterials.2019.05.023 275. ColorJet Printing. https://uk.3dsystems.com/on-demandmanufacturing/colorjet-printing 276. Digital Metal ®. https://www.hoganas.com/en/services/digitalmetal/ 277. HP: HP Metal Jet technology. https://www8.hp.com/h20195/v2/ GetPDF.aspx/4AA7-3333EEW.pdf 278. Aimar, A., Palermo, A., Innocenti, B.: The role of 3D printing in medical applications: a state of the art. J. Healthc. Eng. 2019, 1–10 (2019). https://doi.org/10.1155/2019/5340616 279. The Voxeljet History. https://www.voxeljet.com/about-voxeljet/ history/# 280. Asfak, S.A., Arif, T.F., Uday, T.S., Singh, M.P.: Rapid prototyping: advancements in manufacturing technologies. Int. J. Eng. Appl.

E. Pei et al. Sci. Technol. 5(254–260) (2020). https://doi.org/10.33564/ijeast. 2020.v05i05.043 281. What is single pass Jetting™? https://www.desktopmetal.com/ resources/what-is-single-pass-jetting 282. Sachs, E., Cima, M., Williams, P., Brancazio, D., Cornie, J.: Three dimensional printing: rapid tooling and prototypes directly from a CAD model. J. Eng. Ind. 114, 481–488 (1992). https://doi.org/10. 1115/1.2900701 283. Sachs, E., Cima, M., Cornie, J.: Three-dimensional printing: rapid tooling and prototypes directly from a CAD model. CIRP Ann. 39, 201–204 (1990). https://doi.org/10.1016/S0007-8506(07)61035-X 284. 3D Printing History at MIT. https://www.ryanwkendall.com/ uploads/1/3/3/4/133493762/3d_printing_history.pdf 285. Iliescu, M., Nutu, E., Tabeshfar, K., Ispas, C.: Z printing rapid prototyping technique and solidworks simulation: major tools in new product design. In: 2nd WSEAS International Conference on Sensors, and Signals and Visualization, Imaging and Simulation and Materials Science (SENSIG’09/VIS’09/MATERIALS’09), pp. 148–153. World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin (2009) 286. Sachs, E.M., Haggerty, J.S., Cima, M.J., Williams, P.A.: Threedimensional printing techniques. https://patents.google.com/pat ent/US5340656A/en (1994) 287. Cima, M., Sachs, E., Fan, T., Bredt, J.F., Michaels, S.P., Khanuja, S., Lauder, A., Lee, S.-J.J., Brancazio, D., Curodeau, A., Tuerck, H.: Three-dimensional printing techniques. https://patents.google. com/patent/US5387380A/en (1995) 288. Powder Binding 3D Printers. https://www.additive.blog/knowl edge-base/3d-printers/powder-binding-3d-printers/ 289. Jamie, D.: Ceramo one: The industrial ceramic 3D printer by Kwambio. https://www.3dnatives.com/en/ceramo-one-3d-printerkwambio-050120184/ 290. Hoechsmann, R., Ederer, I.: Method for producing components by build-up technology. https://patents.google.com/patent/ DE19723892C1/en (1998) 291. Ederer, I., Hoechsmann, R., Kudernatsch, A.: Production of casting molds comprises depositing particulate material on support, applying binder and hardener to form solidified structure in selected region, and removing solidified structure. https://patents.google. com/patent/DE19853834A1/en (2000) 292. Ederer, I., Graf, B., Hoechsmann, R., Kudernatsch, A.: Device for building up models in layers. https://patents.google.com/patent/ DE10047614C2/en (2002) 293. Ederer, I.: Method for producing three-dimensional components. https://patents.google.com/patent/US9505176B2/en (2016) 294. HP Multi Jet Fusion and voxeljet High Speed Sintering in comparison. https://www.voxeljet.com/case-studies/consumer-goods/hpmulti-jet-fusion-and-voxeljet-high-speed-sintering-in-comparison/ 295. Additive Hybrid Manufacturing for the casting. https://www. voxeljet.com/3d-printing-solution/sand-casting/ 296. Our Story. https://www.exone.com/en-US/About/Our-Story 297. Mirzababaei, S., Pasebani, S.: A review on binder jet additive manufacturing of 316L stainless steel. J. Manuf. Mater. Process. 3, 82 (2019). https://doi.org/10.3390/jmmp3030082 298. Licensing 3DP technology. http://www.mit.edu/~tdp/licensees. html 299. Digital Metal: Additive manufacturing of small and complex metal parts. (2013) 300. Stark, A.: Desktop Metal launches breakthrough technology. https://www.etmm-online.com/desktop-metal-launches-break through-technology-a-999653/ 301. Kolodny, L.: Desktop Metal reveals how its 3D printers rapidly churn out metal objects. https://techcrunch.com/2017/04/25/desktop-metalreveals-how-its-3d-printers-rapidly-churn-out-metal-objects/?guce_ referrer¼aHR0cHM6Ly9lbi53aWtpcGVkaWEub3JnLw&guce_

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referrer_sig¼AQAAAIQYQ_Zzog-MUPfsxaxTuRfv-0OuYvrKHC_ pFLIZdqTrPMVC1h-5xRT2WBwL-i5HBmxed-EGGj2 302. Milestones in 3D printing – From an idea to a disruption. https:// www.3dprintbureau.co.uk/milestones-in-3d-printing-from-anidea-to-a-disruption/ 303. ProJet CJP 860Pro - Color 3D Printer. https://uk.3dsystems.com/ 3d-printers/projet-cjp-860pro 304. Griffiths, L.: HP launches metal jet 3d printing technology and production service. https://www.tctmagazine.com/additivemanufacturing-3d-printing-news/hp-metal-jet-3d-printing-produc tion-service/

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Israt Rumana Kabir is a Lecturer in the Department of Engineering at the University of Hertfordshire, UK. Main roles include teaching Mechanical Engineering with research interests on functionally graded additive manufacturing (laser-based), applications of modelling and simulation techniques for advanced and digital manufacturing processes and sustainable manufacturing.

Eujin Pei is a Reader in Additive Manufacturing and Associate Dean for the College of Engineering, Design and Physical Sciences at Brunel University London. He is the Director for the BSc Product Design Engineering program. He is a Chartered Engineer (CEng), Chartered Environmentalist (CEnv), and Chartered Technological Product Designer (CTPD). His research focuses on Additive Manufacturing and chairs the UK national standardization committee for AM (BSI AMT/8), as well as chair for the international standardization committee for AM data and design (ISO TC261/WG4).

Bastian Leutenecker-Twelsiek is Professor of Product Development and Rapid Prototyping at the Düsseldorf University of Applied Sciences (HSD) and Head of the Institute for Product Development and Innovation (FMDauto). In the research area of product development, the main focus is on Additive Manufacturing. In this area Prof. LeuteneckerTwelsiek concentrates on unlocking the potential of additive manufacturing to develop new products and implement innovative solutions. Special attention is paid to the design process with the implementation of additive design and the transfer of design expertise. Practical and project-based teaching are important aspects in industrial projects as well as research-related teaching. Before his appointment at HSD, Bastian Leutenecker-Twelsiek was Head of Consulting and Materials for Additive Manufacturing at TRUMPF SE þ Co KG. He completed his mechanical engineering studies at the Karlsruhe Institute of Technology and his doctorate at ETH Zurich in the field of design for additive manufacturing.

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Economics of Additive Manufacturing Christoph Klahn

, David Butler

, and Eujin Pei

Contents 2.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

2.2

Business Models in an AM Ecosystem . . . . . . . . . . . . . . . . . . . 32

2.3

Value Clusters of AM in a Focal Firm . . . . . . . . . . . . . . . . . . . 33

2.4 2.4.1 2.4.2 2.4.3 2.4.4 2.4.5 2.4.6 2.4.7

Costs of AM Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Labor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cost Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Benefits of AM in the Product Life Cycle . . . . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

34 35 35 35 35 35 39 40

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Abstract

Additive manufacturing (AM) is different from other traditional production technologies. The introduction of AM parts into a product or a production process may have implications on cost structure, value creation, and revenue streams. This chapter discusses the cost and benefits associated with AM processes and products. The first half of the chapter discusses the costs of AM processes with a detailed description of cost drivers of metal and polymer C. Klahn (*) Karlsruhe Institute of Technology, Institute of Mechanical Process Engineering and Mechanics, Eggenstein-Leopoldshafen, Karlsruhe, Germany inspire AG, Zurich, Switzerland e-mail: [email protected] D. Butler Department of Design, Manufacturing, and Engineering Management, University of Strathclyde, Glasgow, UK e-mail: [email protected] E. Pei College of Engineering, Design and Physical Sciences, Brunel University London, London, UK e-mail: [email protected]

AM. The main contributor of successful AM products are the unique benefits derived from using AM. They are often needed to compensate for higher costs and lower productivity compared to conventional mass production. The second half of the chapter discusses business opportunities and value creation for a local firm that uses AM and in the context of an AM ecosystem. All considerations of the economics of AM should include a wider view on the life cycle of a product, since the introduction of AM shifts costs and benefits between the product life phases. Keywords

Additive manufacturing · Life cycle analysis · Business · Cost models · Life cycle cost analysis

2.1

Introduction

Additive manufacturing (AM) is well-known for its key characteristics “complexity for free” and “lot-size-independence.” Both characteristics originate from the different cost structure compared to conventional manufacturing. The cost drivers of many traditional production processes favor the mass production of simple parts while the cost of AM are mainly related to limited part volume. The different cost structure has implications on business models and product development. A mere exchange of manufacturing processes in an existing business is rarely beneficial because AM processes are typically slower and more expensive than conventional processes. Successful AM implementations build on the key characteristics of the freeform manufacturing process to access new value propositions and those that were previously prohibited due to the cost of conventional manufacturing. AM is not an isolated manufacturing process. The technology and new business models require and foster a wide range of opportunities for supporting and enabling businesses. This includes machine and material manufacturers, software development,

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_2

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engineering, and manufacturing service providers. This chapter provides a holistic overview on the economics of AM. Section 2.2 introduces the wider ecosystem of AM which consists of companies that support AM operations or benefit from AM. The opportunities for value creation in the context of a focal firm are described in Sect. 2.3. Section 2.4 describes the cost structure of an AM in-house production. Finally, Section 2.4.6 describes the assessment of benefits along the product life cycle (Table 2.1).

2.2

Business Models in an AM Ecosystem

The commercial ecosystem of AM in Fig. 2.1 is described by Piller et al. [27]. Each of the stakeholders in the figure represents a viable business opportunity and contributes to the success of AM. Piller et al. [27] proposed the structure of the ecosystems in terms of general suppliers of machines, systems and materials, the stakeholders in realizing a specific part through design/scanning, production and distribution, and finally the consumption/use of the part. The most visible stakeholders of the ecosystem are machine manufacturers, because they are actively marketing their machines by showing the advantages of the AM process. System engineers support the implementation of AM machines into a production process chain by customizing AM machines and automating pre- and post-processing steps. AM materials are Table 2.1 Abbreviations CNC PBF-LB/M PBF-LB/P LCA LCC OEM PA12

Computer numerical controlled Laser-based powder bed fusion of metal Laser-based powder bed fusion of plastic Life cycle analysis Life cycle cost analysis Original equipment manufacturer Polyamide 12

Machines & systems

Materials

provided by chemical companies and material suppliers. Material suppliers buy alloys or polymers and process them into usable feedstock material for AM processes. Today’s demand from the AM industry does not justify the development of AM-specific recipes and the building of production plants. The drawbacks are suboptimal processing properties of standardized materials and a low priority of AM applications in case of global shortages. Such a global shortage occurred in 2012 for polyamide PA12, which is the most important and commonly used material in laser-based powder bed fusion of plastics (PBF-LB/P) and an important material used in the automotive industry. A fire at Evonik’s plant for a chemical component of PA12 disabled half of the worldwide production capacity of PA12 [12]. The segments of design/scanning, production, and distribution collectively provide AM products to customers. Section 2.3 describes the value creation at an original equipment manufacturer (OEM) operating new product development and order fulfilment in-house. There are also service providers that support companies in the development and production of AM parts. Engineering service providers offer designing or reverse engineering of the 3D model of a product. There are also platforms that offer 3D models of toys, accessories and spare parts. ▶ Chapter 7 discusses the copyright and liability implications of these platforms. New business models, not mentioned by Piller et al. [27], are companies offering frameworks for online configurators and other design platforms that allow customers to specify and design their part on a website. These digital business models are a growing sector within the AM value chain as they provide opportunities for new services and systems-level integration [13]. Production service providers support the production of AM parts either by producing AM parts or by providing access to machines and infrastructure. The most common are companies that offer AM and a varying degree of post-

Design / scanning

Production

Distribution

Consumption / use

OEMs

Machine manufacturers Product designers

Contract manufacturers

Scanning services

Digital fabrication workshops

Design sharing platforms

Machine sharing & printing services

Industrial

Chemical companies Systems engineers Material suppliers

Design marketplaces & printing services

User innovators / entrepreneurs and maker community Software / IT (e.g. 3D modelling, IP rights management, IT security) Research & education (e.g. mechanical engineering & material science, quality / testing standards, workforce skills) Policy (e.g. IP rights, CO2 regulations)

Fig. 2.1 AM ecosystem [27]

Personal / home

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Economics of Additive Manufacturing

processing steps. Networks, platforms, and communities support AM activities by connecting the stakeholders of AM to share expertise and to advocate the needs of the community. Various software companies support the AM ecosystem with dedicated tools or integrated functions for design, build job preparation, machine operation, and other tasks. Research centers advance the state of the art, while educational institutions build up a skilled workforce through teaching and training. Policy makers work on the legal and regulatory framework, standardization, and universal guidelines. This framework is the basis for industrializing AM with control over safety and regulated applications. The versatility of AM machines offers an unprecedented flexibility to the supply chain. Collaborations between different stakeholders of the ecosystem as shown in Fig. 2.1 may change between projects or even between orders. This flexibility comes at the price of reduced controllability [10, 31]. Regulated or quality-sensitive applications still require supply chains of certified suppliers. Nevertheless, Holmström et al. [16] report benefits for a centralized AM production of aircraft spare parts. A major drawback of these open and distributed manufacturing networks in the AM ecosystem is the risk of IP loss, counterfeiting, and malicious data manipulation. Gupta et al. [15] analyze the AM supply chain for security risks and identify different attack vectors. To mitigate some of these threats, different authors propose the use of blockchain technology to secure and trace the use and transfer of data between stakeholders [1, 23].

2.3

Value Clusters of AM in a Focal Firm

AM offers many benefits, and there is a long list of advantages such as weight reduction or on-demand production. Fontana et al. [14] propose seven value clusters based on contribution of value to the processes within an original equipment manufacturer (OEM). The value clusters of Fontana et al. [14] are mapped according to two main processes. New product development is a process of developing a part from the initial idea to a fully validated design that is handed over to production. Order fulfilment is the process of producing parts to fulfil customers’ orders. Order fulfilment also includes aftersales services. Recurring engineering adapts and updates existing products and is at the interface between new product development and order fulfilment. Figure 2.2 shows the value clusters of AM in new product development and order fulfilment. However, where the value lies can sometimes be ambiguous. For example, an AM injection molding tool is seen as a “production tool” for a plastic processing company, while it is perceived as an “enhanced product” for the tool manufacturer. The value cluster of “prototyping” is the oldest application of AM and has been the main motivation for the development

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of early AM technologies. AM enables fast production of visual and functional prototypes, thus allows a much quicker and iterative product development. This early validation of ideas and designs accelerates the development process and increases the maturity of the product. This value of prototyping is derived from the ability to cost-efficiently produce single parts that are designed for completely different manufacturing processes. The value cluster of “enhanced products” covers AM applications where the capabilities of AM can potentially improve the performance of the product. This is usually achieved by a function-driven design that applies AM’s larger freedom in design to closely follow an ideal solution. Numerical optimization and simulation are methods to develop and validate the theoretically best solution. The value cluster of “customization” summarizes business models that provide individualized parts to each customer. This cluster combines the advantages of complexity for free and small lot sizes. Very few restrictions in AM limit customer-specific designs, and AM can efficiently produce many similar yet customized parts. The data preparation for most AM processes is easy to automat, which make a fully automated process from design generation to the start of the machine feasible. The value cluster of “improved delivery” is closely related to customization. AM addresses the challenges of unsteady demand and high variety on manufacturing costs and lead time. A change from made-to-stock to a make-to-order becomes possible by introducing AM technologies to the supply chain. A typical example for such an application is spare parts for legacy products. A digital inventory and AM processes increase the responsiveness and reduce the number of items in stock. The value cluster of “production tools” is one of the oldest applications of AM processes for long-lasting components. Tools, jigs, and fixtures are important parts in production and assembly. They are designed for a specific step and improve its ergonomics, time, cost, and quality. The difference to other individualized parts is the amortization through an improved efficiency of a conventional manufacturing process. The value cluster of “process simplification” describes AM applications where AM technologies is able to replace sections of a process chain. The complexity for free characteristic of AM allows companies to combine multiple process steps or parts into one AM part, thus reducing part count, process steps, and waiting and assembly time. Process simplification helps to streamline an in-house production as well as a supply chain. Lastly, the value cluster of “incremental launch” is an emerging value cluster of AM. New products face many market uncertainties and require investments for production infrastructure. Launching a product with AM parts and later gradually changing to mass production technologies reduces the risk of new products in two aspects. The toolless production of small lot sizes allows fast design changes to incorporate customer feedback and to fix errors. The investment in expensive tooling for mass production is delayed

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Information

New product development

Material Outside company boundaries AM value clusters Design space exploration

Concept design Prototyping

Enhanced products Detailed design

Validation

Incremental launch

Customization

Recurring engineering

Procurement

Production

Distribution Users

Suppliers

Improved delivery Process simplification

Production tools Aftersales 24/7 Service

Order fulfilment

Fig. 2.2 Value clusters of AM in new product development and order fulfilment. (Based on [14])

until a mature design is reached and a growing demand creates revenues. In summary, the value clusters of Fontana et al. [14] are not mutually exclusive because companies can harvest AM benefits in multiple value clusters at different levels. For example, the decision to simplify the process chain by implementing AM technologies opens opportunities to improve or customize a product.

2.4

Costs of AM Processes

There are several key cost drivers that may potentially influence the economics of AM, and these can be broadly divided into five categories: machine, material, labor, energy, and indirect overheads (in the form of cost models) that are discussed in

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this section. These drivers have been reported in the literature, including Atzeni et al. [3], Baumers et al. [7, 8], Ding et al. [11], Kadir et al. [20], Lindemann et al. [25], Pereira et al. [26], Thomas and Gilbert [32], and Urbanic and Saqib [33].

2.4.1

Machine

With the push for increased industrialization of the AM process, machines have evolved to include several features that can achieve both greater throughput and confidence in the built part. These include real-time and in situ melt pool monitoring, multiple lasers, and optimized process parameters, that have all added to an increase in machine and service costs. Prices range from £150,000 to £1,000,000 depending on the process technology, part size, material type, application, and the level of automation required, thereby incurring heavy long-term investments for companies.

2.4.2

Material

Material options for metal-based AM have typically been limited to the more widely used alloys such as stainless steel, aluminum, titanium, and nickel, with the latter finding considerable interest from the aerospace sector. While the list of AM alloys had been getting longer with more specialist metals companies introducing new materials, it is still a lengthy process to quantify a new material and process. Depending on the AM process, the characteristics of the feedstock need to be controlled carefully in terms of particle shape, size, and distribution as well as level of contamination. With higher quality specifications than bulk material and lower production volumes, the cost of AM powders is significantly more expensive. As an example, the price of 316 stainless steel AM powder is approximately between 10 and 30 times that of the bulk material depending on the particle size, morphology, and size distribution. Another material-related issue with powder bed-based AM process is the requirement to fill the entire working platform with powder on each use, whereas only a smaller area will be subjected to powder melting. Thus, a significant amount of powder will not be directly affected by the beam but may have been exposed to the environment. Due to the high cost and the amount of unused powder, the powder left after removing the final part can only be reused several times without affecting in a significant way the properties [5].

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require manual intervention and monitoring. These include preparing and cleaning the machine, both before and after the build is complete. During the process, the function of the worker is to monitor the process and attend to breakdowns or software errors. Given the nature of the feedstock, specific training on materials handling as well as health and safety are necessary. The salary for such an employee can be as high as 30% more than a comparable role in a traditional manufacturing environment. Given the relatively long build times, this additional labor cost can be offset by several machines being managed by one worker.

2.4.4

Energy

The energy consumption depends on two parts of the process: the preheating setup and the build time. The duration is dependent largely on the material properties as the temperature needs to be close to that of the melting point of the feedstock. During the build process, the bed heaters need to be active to maintain a stable temperature and the melting operation will also increase the power consumption. Kellens et al. [21] investigated the power usage for an PBF-LB/M machine (Concept Laser M3 Linear) at different stages. Table 2.2 shows the machine power consumption and percentage of time for each mode during a 4-h job. The power consumption for powder spreading stage is the highest (3.45 kW), which is caused by the powder sweeper in operation. The power consumption during laser scanning is slightly lower. As mentioned earlier, preheating also generates significant energy usage (2.25 kW). The power consumption during cooling down and cleaning is much lower (0.7 kW) as compared to other modes. It should be noted that both preheating and cooling down are not influenced by a specific job.

2.4.5

Cost Models

Various cost models have been developed since the inception of rapid prototyping and have transitioned into AM. They include the major work from Hopkinson and Dickens [17], Ruffo et al. [29], Baumers et al. [6], and Lindemann et al. [24]. A review of the main cost models is presented below, based on the compilation made by Costabile et al. [9]. Table 2.2 Machine power and timeshare at different stages [21]

2.4.3

Labor

Although the actual build operation for AM is automated, there are still a number of pre- and post-build steps that will

Stage Preheating + creating inert atmosphere Laser scanning Powder spreading Cooling down + cleaning

Power [kW] 2.25 3.25 3.45 0.7

Time [%] 12 68 5 15

2

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Hopkinson and Dickens’ Cost Model One of the first cost models was developed by Hopkinson and Dickens [17] through comparing several AM technologies, including Vat Photopolymerization, material extrusion, and powder bed fusion, with a traditional injection molding process in terms of cost of production per part. This research considers three main parameters to calculate the final total cost: machine, labor, and material costs. As it was carried out in 2003, the cost of life and salaries have changed significantly since then, and the values that will be shown in tables are not applicable nowadays. Parameters considered for the estimation of machine costs are presented in Table 2.3. The authors assumed that the machines would be operating for 90% of the total time in a year and equipment would depreciate over a period of 8 years. All parameters were extracted from machine manufacturers. The labor cost that Hopkinson and Dickens calculated was cost per part, and in Table 2.4, a breakdown of costs related to manpower is shown. Some of the factors considered by the authors were that the minimum hourly wage at the time of the study was used and the working time of the labor equated with that of the machines. The cost of materials was calculated using the weight of the finished part and the supports for the manufacturing process, and the breakdown of the considered costs of subprocesses of Vat Photopolymerization and laser-based powder bed fusion of plastic is presented in Table 2.5. The variables in Table 2.5 inherit the process names from Hopkinson and Dickens [17] and use stereolithography (SL) for Vat Photopolymerization and laser sintering (LS) for laser-based powder bed fusion of plastics.

Ruffo, Tuck, and Hague’s Cost Model The model developed by Ruffo et al. [29] was an improvement of the model previously explained, focusing on the laser-based powder bed fusion of plastic process. The different aspects of this model are presented in Fig. 2.3. This model considers a higher number of indirect costs derived not only from the manufacturing process itself but also all the costs associated with the performance of the company and fixed costs. Some considerations of this study

Table 2.4 Breakdown of labor costs by Hopkinson and Dickens [17] Number per platform Platform build time Production rate per hour Hours per year in operation Production volume total per year Labor costs Machine operator cost per hour Setup time to control machine Post-processing time per build Labor cost per build Labor cost per part

Table 2.3 Breakdown of machine costs by Hopkinson and Dickens [17]

Platform build time Production rate per hour Hours per year in operation Production volume total per year Machine costs Machine and ancillary equipment Equipment depreciation per year Machine maintenance per year Total machine cost per year Machine cost per part

Materials costs for SL Material per part including support (kg) Material cost per kg Material cost per SL part Materials costs for LS Materials per part (kg) Mass of each part Volume of each part

Variable Source of cost obtained by N Maximum possible in one build T Hours R N/T HY 365
24
90% ¼ 7884 V R
7884

E

Machine purchase cost

D

E/8

M

Most comprehensive package DþM MC/V

MC MCP

T R HY V

Source of cost obtained by Maximum possible in one build Hours N/T 365
24
90% ¼ 7884 R
7884

Set

Minimum wage (5.30 € (2003)) Timed

Post

Timed

L LCP

Op
(set þ post) L/N

Op

Table 2.5 Breakdown of material costs of Vat Photopolymerization (SL) and laser-based powder bed fusion of plastics (LS) by Hopkinson and Dickens [17]

Number per platform

Number per platform

Variable N

Total build volume Mass of sintered material per build Mass of unsintered material per build Cost of material used in one build Material cost per LS part a

Variable N

Source of cost obtained by Maximum possible in one build

SLmass

Weighing finished parts

SLcost SLMCP

Quote ¼ 275.20 € (2003) SLmass
SLcost

LScost LSmass VPP TBV LSMS

Quote ¼ 54 € (2003) Weighing finished parts Found using commercial software 34  34  60 cm3 N
LSmass

LSMU

(TBV – N
VPP)
0.465a

LSMC

(LSMU þ LSMS)
LScost LSMC/N

LSMCP

Published density of unsintered LS powder is 0.45– 0.5 g cm3

2

Economics of Additive Manufacturing

37

Fig. 2.3 Cost strategic plan. (Adapted from Ruffo et al. [29])

Cost of the build

2 Build time

Direct cost

Indirect cost cost/h

Material cost Production overhead

Part volume Waste

Labour Technician salary

Facility rent Ancillary equipment Energy Administrative overhead

Machine

Labour

Purchase absorption

Hardware

Maintenance

Software

Software

Consumables

Hardware

that are different from the one carried out by Hopkinson and Dickens include a lower working time percentage of 60% which was deemed more realistic and the lowering of material costs due to the recycling of feedstock. However, some factors like pre- and post-processing, and the production in parallel were not considered. It also ignored any possible usability of the excess capacity as it was only focused on the production of a single part without analyzing the demand in the business.

Baumers et al. Cost Model The model developed by Baumers et al. [6] can be considered as a refinement process of the one developed by Ruffo et al. [29] for laser-based powder bed fusion of metal. The main difference remains in the application of energy costs as direct costs, referring them directly to the part production, and allowing a deeper study of energy factors associated to the AM machine. It also was the first time that the optimization of the production capacity was considered to optimize the energy usage. This model was an improvement of the

previous ones giving a more accurate calculation of cost by considering a more detailed division of the process, and the inclusion of optimization methods to improve machines capacity considerations, the advantage of AM technologies to develop different geometries was considered. However, this model relied again on the assumption that pre- and post-processing operations, and surface quality operations were not needed, producing a full finished part.

Lindemann et al. Cost Model The model developed by Lindemann et al. [24] was the first which included preparation and post-processing operations within the calculations of total cost per part. The parameters considered for this model were based on the time to perform the different activities through the whole process. By mapping the value chain of the development of one part, presented in Fig. 2.4, they divided the cost driving activities in four fields: preparation, production, removing of samples and supports, and post-processing. In this case, it has presented a model, which considers the entire value chain from the

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Metal additive manufacturing

Build preparation Cost drivers

Cost drivers

CAD preparation CD

Postprocessing

Manufacturing

Machine preparation CD

Quality control

Cost drivers

Build process CD

Cost drivers

Support removal CD

Surface treatment CD

Verification CD

Documentation CD

Fig. 2.4 Product value stream map. (Adapted from [24])

conception of the part to a finished product, presenting a more realistic approximation of the total cost. Consideration of energy costs as direct and fixed costs also helps in this achievement. However, the structure of the process is conceptually similar to that stated by Ruffo et al. [29], producing a model for a single part cost which dismisses the production in parallel.

Other Cost Models Several other cost models have also been developed in recent years. The regression model proposed by Rickenbacher et al. [28] took real operation data from several machines to determine the model coefficients. In this model, the cost of energy was not considered which contradicted earlier research that tended to consider it as a major cost factor. Schroder et al. [30] developed an activitytime driven model that had similarities to the model proposed by Lindemann et al. [24]. They defined seven process that generated costs including the design and planning stage and any costs associated with administration. The model included a wide variety of factors including the usage of recycled material and material waste, the degree of part complexity, and the maximum number of parts that could be produced in the same operation. Table 2.6 provides a summary of the various cost models identifying the key factors that were considered.

Baldinger’s Price Model for Buy Scenarios The previously discussed models represent the costs of additive manufacturing in a make scenario. This is a suitable approach to represent the internal costs of an in-house production. In contrast to these approaches, the work of Baldinger et al. [4] analyzes the prices of external service providers in a buy scenario. This is probably the most common sourcing for AM parts for companies. The analysis of Baldinger et al. [4] is based on 499 realworld, business-to-business offers for parts made by laserbased powder bed fusion of metal PBF-LB/M (stainless steel and aluminum) and of plastic PBF-LB/P (polyamide 12, PA12). The data was collected in 2014 on an AM marketplace website. The study confirms the cost-volume relationship in the cost models for make scenarios is handed on to buy scenarios. Offers with a small total volume do not follow the costvolume relationship and are more expensive. This volume threshold is process specific and lies around 500 cm3 for PBF-LB/P of PA12 and around 100 cm3 for PBF-LB/M of stainless steel and aluminum. The price finding is governed by the total volume VTot and the packing ratio PRavr of total volume by bounding box volume. The cost matrix indicate above the volume threshold for groups with more than five observations the price ranges in Table 2.7.

2

Economics of Additive Manufacturing

39

Table 2.6 Summary of cost models Hopkinson and Dickens [17]

Machine costs: equipment; equipment depreciation; machine maintenance; total machine cost per year; machine cost per part Production: facility; equipment; energy

Material cost: material cost per kg; volume of part; mass of sintered material; mass of unsintered material; cost of one build material; cost per part

Labor cost: operator cost per hour; setup time; post-processing time; labor cost per build; labor cost per part

Ruffo et al. [29]

General costs: number per platform; platform build time; production rate per hour; hours per year in operation; production volume per year Material: parts volume; waste

Labor: salaries

Administration: labor; hardware; software; consumables

Baumers et al. [6]

Machine-associated costs; time

Energy; price of energy

Lindemann et al. [24]

Build preparation: CAD preparation; machine preparation Premanufacturing: geometry preparation; build job setup

Weight of material; price of material Manufacturing: build process

Rickenbacher et al. [28]

Schroder et al. [30]

Design and planning

Manufacturing: process

Materials processing

Post-processing: support removal; surface treatment Postmanufacturing: removal from machine; substrate separation; support removal Machine preparation

2

Machine: purchase absorption; maintenance; software; hardware

Quality control: verification; documentation Post-processing

Manufacturing

Postprocessing and quality

Administration and sales

Table 2.7 Price per volume for laser-based powder bed fusion of plastic and of metal [4] Process PBF-LB/P

Material PA12

PBF-LB/M Stainless steel PBF-LB/M Aluminum

Min. price [€ cm3] 3

0:48 € cm

Max. price [€ cm3] 3

V Tot > 10000 cm , PRavr ¼ 0:1 to 0:5Þ

3

3

3

V Tot ¼ 1000 cm to 10000 cm , PRavr < 0:05Þ

3

V Tot

10:84 € cm 3 3 ¼ 1000 cm to 10000 cm , PRavr ¼ 0:1 to 0:5 3

7:3 € cm 3 3 V Tot ¼ 250 cm to 500 cm PRavr ¼ 0:05 to 0:1Þ

Baldinger et al. [4] propose the regression model in Eq. 2.1 to estimate the prices of PA12 CTot based on total volume VTot, bounding box BBTot and quantity of parts QTot. CTot ¼ 459 þ 0:213
V Tot þ 0:0197
BBTot þ 2:57
QTot ð2:1Þ

2.4.6

1:61 € cm

Benefits of AM in the Product Life Cycle

The costs of AM often exceed the costs of conventionally manufactured parts. This is due to the lower productivity of AM processes as compared to mass production processes, as well as the higher design effort for using AM’s freedom in

9:51 € cm

3

ðV Tot ¼ 500 cm3 to 1000 cm3 PRavr ¼ 0:05 to 0:1Þ

design to optimize the part for an application. In successful AM applications, the benefits of AM over the lifetime of a product compensate for the initially higher cost of AM parts. The benefits of AM arise mainly from the two key properties of AM. First, the little impact of the geometrical complexity of a part on its manufacturing time and costs, often referred to as “complexity for free.” Second, the cost advantage of AM for small lot sizes due to the low nonrecurring costs of setting up an AM production. Nonetheless, AM is not an isolated manufacturing process. The technology is integrated into larger frameworks and process chains. AM has the potential to add value at many instances of new product development and order fulfilment. The benefit of AM can occur at different stakeholders during the lifetime of a product. An assessment of the impact of AM therefore should cover a wider view. The

40

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use of life cycle analysis (LCA) is a standardized method that can help to evaluate the environmental impact of a product from cradle to grave or cradle to cradle. The norms (ISO14044:2006 [19] and ISO14040:2006 [18]) provide a framework for the analysis. An LCA generally consists of four steps: goal and scope definition phase, inventory analysis phase, impact assessment phase, and interpretation phase (ISO14040:2006 [18]). The key element for correct results in an LCA is a suitable definition of the system boundaries. In addition, life cycle cost analysis (LCC) quantifies and allocates costs incurring throughout the life cycle of a product [2]. The life cycle consists typically of design, manufacturing, distribution, usage and disposal and allocates costs to manufacturers, customers, users, and society. Design and manufacturing decisions usually affect other stages of the life cycle beyond design and manufacturing. A typical observation in AM are higher costs for the manufacturer due to a more complex, individualized design and higher recurring manufacturing costs, while the user benefits from a better performance and shorter lead times of AM products. A LCA or LCC assesses and quantifies these effects. The understanding of costs and benefits along the product life cycle helps a company to develop a monetarization and marketing strategy to transform customer benefits into additional revenue and profit. The impact of one part can accumulate across different products, when this part is used in the production of other parts. This is the case when AM parts improve the capabilities of a production machine, which is then able to produce better parts. In these scenarios, a single AM part can improve many parts with a significant economic and environmental impact. Figure 2.5 depicts these higher order benefits along three connected product life cycles. Each life cycle consists

r me sto t. Ma

Cu

1st order benefits

.

Mat.

d Pro

Designing company

2st order benefits

Mat.

Prod.

Use

e-o-l

-l

e-o

Customer’s customer

e-o-l

e

Use Us

Prod.

3rd order benefits

nth order benefits

Fig. 2.5 Higher order benefits along the life cycles of production system and products [22]

of material sourcing (mat.), production (prod.), product use (use), and end of life (e-o-l) [22]. The order of benefits in Fig. 2.5 refers to the distance to the decision for change. First-order benefits occur within the company that implements AM, e.g., from replacing an error prone, complex conventional process chain by a single AM process. Second-order benefits derive from the use of the AM product, e.g., a fuel saving due to lightweight aircraft brackets. These benefits are generated every time the AM product is used and accumulate through the lifetime of a product. A seemingly minute improvement to the use phase can easily exceed any first-order benefits. This effect continues when the use phase of this product is again the production of another one. An example for higher order benefits are AM injection molding inserts. The first-order benefit to the toolmaker is the ability to produce complex injection molding tools. The company is able to sell each tool for a better price. The customers are injection molding companies, and the use of each AM injection molding tool creates a second-order benefit through shorter cycle times and lower scrap rates in the production of plastic parts and an increased feasibility of complex parts. A third-order benefit occurs when the use of the injection molded plastic part is improved by the design changes made possible through the AM injection molding tool.

2.4.7

Summary

AM was initially burdened with high expectations since the early beginnings of its industrialization. Common promises include the expectation for everyone to produce virtually anything, everywhere, and the dawning of a new industrial revolution. The economic aspects of AM therefore ground this expectation closer to the reality of industrial and end user needs. The two main economic ingredients for a successful AM product is a suitable network of partners within the AM ecosystem as well as a healthy ratio of cost and benefit of a product. The section on applications (▶ Chap. 58) provides many positive examples of AM products and companies. Section 2.2 has provided an overview on the various stakeholders that support product development and manufacturing with their products and services. It is possible to consider AM like any other manufacturing technology. Nevertheless, the flexibility of AM offers new opportunities in product development and order fulfilment and along the supply chain. These opportunities are not limited to legitimate manufacturers, and there is a need to secure the digital and physical process chain of additive manufacturing against sabotage and IP loss. Section 2.3 has focused on the value creation within a focal firm. The chapter describes seven value clusters where AM has added value to the processes of new product development and order fulfilment. Section 2.4

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Economics of Additive Manufacturing

presented six cost models of AM processes and a pricing model of AM service providers. The main cost drivers of the AM process are related to the build time which is determined by the volume of the produced parts. This is a significant difference to subtractive processes, like milling, where the shape complexity and the removed volume determine machining time and cost. Hence the term “complexity for free” in AM. The mostly digital build job preparation causes little nonrecurring cost. Without part-specific investments, like tooling or CNC programs, the production of single parts and small lot sizes becomes economically feasible. Section 2.4.6 highlighted the importance to consider the whole product life cycle in the evaluation of AM. The introduction of AM often leads higher costs in the production phase while benefits occur in other phases of the product life cycle. In conclusion, the economics of AM differ from other manufacturing processes. This has many implications on how AM is implemented into a company and how AM affects digital and physical process chains. The future will tell if AM can fully establish itself by integrating with the portfolio of manufacturing technologies or if AM can expand its position within manufacturing and to contribute to the next industrial revolution.

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41 9. Costabile, G., Fera, M., Fruggiero, F., Lambiase, A., Pham, D.: Cost models of additive manufacturing: a literature review. Int. J. Ind. Eng. Comput. 8, 263–282 (2017) 10. Delic, M., Eyers, D.R.: The effect of additive manufacturing adoption on supply chain flexibility and performance: an empirical analysis from the automotive industry. Int. J. Prod. Econ. 228, 107689 (2020). https://doi.org/10.1016/j.ijpe.2020.107689 11. Ding, J., Baumers, M., Clark, E.A., Wildman, R.D.: The economics of additive manufacturing: towards a general cost model including process failure. Int. J. Prod. Econ. 237, 108087 (2021). https://doi. org/10.1016/j.ijpe.2021.108087 12. Dixon, O.: Resin crisis exposes supply chain fragility. Automotive World. https://www.automotiveworld.com/articles/93247-resin-cri sis-exposes-supply-chain-fragility/ (2012) 13. Feldmann, C., Schulz, C., Fernströning, S.: Digitale Geschäftsmodell-Innovationen mit 3D-Druck. Springer Fachmedien, Wiesbaden (2019). https://doi.org/10.1007/978-3658-25162-8 14. Fontana, F., Klahn, C., Meboldt, M.: Value-driven clustering of industrial additive manufacturing applications. J. Manuf. Technol. Manag. 29(2), 372–397 (2018). https://doi.org/10.1108/JMTM-062018-0167 15. Gupta, N., Tiwari, A., Bukkapatnam, S.T.S., Karri, R.: Additive manufacturing cyber-physical system: supply chain cybersecurity and risks. IEEE Access. 8, 47322–47333 (2020). https://doi.org/ 10.1109/ACCESS.2020.2978815 16. Holmström, J., Partanen, J., Tuomi, J., Walter, M.: Rapid manufacturing in the spare parts supply chain. J. Manuf. Technol. Manag. 21(6), 687–697 (2010). https://doi.org/10.1108/ 17410381011063996 17. Hopkinson, N., Dickens, P.: Analysis of rapid manufacturing – using layer manufacturing processes for production. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. 217(1), 31–39 (2003). https://doi.org/ 10.1243/095440603762554596 18. ISO14040:2006: Environmental Management – Life Cycle Assessment – Principles and Framework (2006) 19. ISO14044:2006: Environmental Management – Life Cycle Assessment – Requirements and Guidelines (2006) 20. Kadir, A.Z.A., Yusof, Y., Wahab, M.S.: Additive manufacturing cost estimation models – a classification review. Int. J. Adv. Manuf. Technol. 107, 4033–4053 (2020). https://doi.org/10.1007/s00170020-05262-5 21. Kellens, K., Yasa, E., Dewulf, W., Duflou, J.: Environmental assessment of selective laser melting and selective laser sintering. going green-care innovation: from legal compliance to energy-efficient products and services. In: Going Green – Care Innovation 2010: From Legal Compliance to Energy-Efficient Products and Services. Austrian Society for Systems Engineering and Automation, Vienna (2010) 22. Klahn, C., Fontana, F.: Impact and assessment of design on higher order benefits. In: da Silva, F.M., Bártolo, H.M., Bártolo, P., Almen, R., Roseta, F., Almeida, H.A., Lemos, A.C. (eds.) Challenges for Technology Innovation: An Agenda for the Future: Proceedings of the International Conference on Sustainable Smart Manufacturing (S2M 2016). Taylor & Francis, London (2017) 23. Klöckner, M., Kurpjuweit, S., Velu, C., Wagner, S.M.: Does blockchain for 3d printing offer opportunities for business model innovation? Res. Technol. Manag. 63(4), 18–27 (2020). https://doi. org/10.1080/08956308.2020.1762444 24. Lindemann, C., Jahnke, U., Moi, M., Koch, R.: Analyzing product lifecycle costs for a better understanding of cost drivers in additive manufacturing. In: Proceedings from the 23rd Annual International Solid Freeform Fabrication Symposium, Austin, TX (2012) 25. Lindemann, C., Reiher, T., Jahnke, U., Koch, R.: Towards a sustainable and economic selection of part candidates for additive

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42 manufacturing. Rapid Prototyping J. 21(2), 216–227 (2015). https:// doi.org/10.1108/RPJ-12-2014-0179 26. Pereira, T., Kennedy, J.V., Potgieter, J.: A comparison of traditional manufacturing vs additive manufacturing, the best method for the job. Procedia Manuf. 30, 11–18 (2019). https://doi.org/10.1016/j. promfg.2019.02.003 27. Piller, F.T., Weller, C., Kleer, R.: Business models with additive manufacturing – opportunities and challenges from the perspective of economics and management, Chap 4. In: Brecher, C. (ed.) Advances in Production Technology Lecture Notes in Production Engineering, pp. 39–48. Springer International Publishing, Cham (2014). https://doi.org/10.1007/978-3-319-12304-2_4 28. Rickenbacher, L., Spierings, A.B., Wegener, K.: An integrated costmodel for selective laser melting (slm). Rapid Prototyp. J. 19(3), 208–214 (2013). https://doi.org/10.1108/13552541311312201 29. Ruffo, M., Tuck, C., Hague, R.: Cost estimation for rapid manufacturing – laser sintering production for low to medium volumes. Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. 220(9), 1417–1427 (2006). https://doi.org/10.1243/09544054JEM517 30. Schroder, M., Falk, B., Schmitt, R.: Evaluation of cost structures of additive manufacturing using a new business model. Procedia CIRP. 30, 311–316 (2015) 31. Thomas, D.: Costs, benefits, and adoption of additive manufacturing: a supply chain perspective. Int. J. Adv. Manuf. Technol. 85(5–8), 1857–1876 (2015). https://doi.org/10.1007/s00170-0157973-6 32. Thomas, D.S., Gilbert, S.W.: Costs and Cost Effectiveness of Additive Manufacturing, NIST Special Publication, vol. 1176. U.S. Department of Commerce and National Institute of Standards and Technology (2014). https://doi.org/10.6028/NIST.SP.1176 33. Urbanic, R., Saqib, S.: A manufacturing cost analysis framework to evaluate machining and fused filament fabrication additive manufacturing approaches. Int. J. Adv. Manuf. Technol. 102, 3091–3108 (2019). https://doi.org/10.1007/s00170-019-03394-x

Christoph Klahn is professor for additive manufacturing in process engineering at Karlsruhe Institute of Technology. He was the head of Design for New Technologies at inspire AG, closely related to ETH Zürich, until 2021. His research explores the opportunities of additive manufacturing and their implications on the development process of devices. He works on design for additive manufacturing since 2008 and received his doctorate in engineering from Hamburg University of Technology in 2015.

C. Klahn et al.

David Butler is a Professor of Sustainable Manufacturing in the Department of Design, Manufacturing, and Engineering Management at the University of Strathclyde. His research interests include novel manufacturing processes, the economics of manufacturing, and the circular economy. He has published over 100 journal and conference papers.

Eujin Pei is a Reader in Additive Manufacturing and Associate Dean for the College of Engineering, Design and Physical Sciences at Brunel University London. He is the Director for the BSc Product Design Engineering program. He is a Chartered Engineer (CEng), Chartered Environmentalist (CEnv), and Chartered Technological Product Designer (CTPD). His research focuses on Additive Manufacturing and chairs the UK national standardization committee for AM (BSI AMT/8), as well as chair for the international standardization committee for AM data and design (ISO TC261/WG4).

3

Business Model Innovation in Additive Manufacturing Equipment Sector Sudhir Rama Murthy, Jiashun Huang, and Chander Velu

Contents 3.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3.2 3.2.1 3.2.2 3.2.3 3.2.4

Case Vignettes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emergent Firm: Stratasys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emergent Firm: 3D Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Established Firm: Hewlett-Packard . . . . . . . . . . . . . . . . . . . . . . . . . Established Firm: General Electric . . . . . . . . . . . . . . . . . . . . . . . . . .

45 45 46 46 47

3.3 3.3.1 3.3.2 3.3.3 3.3.4

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comparison of Business Models of the Four Cases . . . . . . . . Value Network as Investor Community . . . . . . . . . . . . . . . . . . . . . Open Source Design as Business Strategy . . . . . . . . . . . . . . . . . . Managerial Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

48 48 50 51 51

3.4

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

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created, the means of value capture, and the partners in the value network – the four Vs. The business models of these equipment supplier firms include equipment sales, equipment as a service, the sale of supplies and platformbased integrated solutions, among others. The emergent firms presented here are Stratasys and 3D Systems; similarly, the established firms considered here are HewlettPackard and General Electric. The chapter employs the four Vs framework to analyses how their business models have evolved. It provides an overview of additive manufacturing businesses, compares the business models in the four firms, discusses the different business models in four other nascent firms, and discusses implications for managers.

Abstract

Keywords

Additive manufacturing has grown from an initial prototyping application into a core production technology. The increasing applicability of additive manufacturing in sectors such as aviation and health care has created an attractive market for emergent and established firms alike. One can also identify a plurality of business models among these equipment suppliers. A business model articulates the customer value proposition, how value is

3D printing · Business models · Technology strategy · Emerging firms · Incumbent firms

S. Rama Murthy Saïd Business School, University of Oxford, Oxford, UK Institute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge, UK e-mail: [email protected] J. Huang School of Public Affairs, University of Science and Technology of China, Hefei, China e-mail: [email protected] C. Velu (*) Institute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge, UK e-mail: [email protected]

3.1

Introduction

Additive manufacturing (AM) is the construction of a threedimensional object through materials being added together, typically layer by layer, and it is positioned to provide a disruptive transformation in industrial production technology [1]. Since the emergence of AM technologies in the 1980s, AM has developed rapidly and evolved into a viable industrial manufacturing solution to drive digital manufacturing [2]. As of 2019, the global market of the additive manufacturing industry, including hardware, software, materials and services, is estimated to be worth over 9 billion dollars [3]. Understanding the additive manufacturing industry requires an appreciation of the business models of the firms involved [4]. While additive manufacturing makes technological advances for production, it still requires firms to operate profitable business models that deliver the

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_3

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technology to industrial and hobby customers alike. While some firms in additive manufacturing have emerged exclusively to operate in this industry, other firms are established players in other sectors but drawn to the potential of AM. We term these “emergent firms” and “established firms”, respectively. Together, they create a vibrant AM industry characterized by a plurality of business models among competing firms. The literature discusses the impact of additive manufacturing on the production and process innovation and its influence on business models and business model innovation [5–7]. Klöckner et al. [4] discussed the various business models that could emerge from the combined use of blockchains and additive manufacturing technology, such as distributed manufacturing. Since designing a suitable business model is critical for the development of an emerging industry, there is growing consensus that more studies on the business models of additive manufacturing should be conducted. For instance, Bogers et al. [8] argued that additive manufacturing would alter business models in the consumer goods industry. They also demonstrated that additive manufacturing makes the business model more consumercentric by shifting value-adding activities from the manufacturer to the consumer, and compared to the conventional manufacturing sectors, the supply chains for additive manufacturing were more decentralized. Rayna and Striukova [2] identified that rapid prototyping and tooling was not disruptive for business models but raised competition. However, they indicated that additive manufacturing and home fabrication could significantly disrupt business models. Holzmann et al. [9] conducted an empirical study on the business models of the additive manufacturing industry and concluded two distinct business model patterns, the “low-cost online business model” and the “technology expert business model”. Studies have argued that business models have agency to shape actions and influence the actions of constituent stakeholders, both with and across the networks of firms, which in turn shapes the business model [10]. Studies have emphasized the market-creation aspect of additive manufacturing. For instance, Hartl and Kort [11] showed different possible market structure outcomes for the possible market entry of a firm with additive manufacturing technology. Building on two game theoretical models, Kleer and Piller [12] investigated the market dynamics of additive manufacturing and derived propositions in terms of how user adoption of additive manufacturing influenced the structure of the market. A business model is a representation of a firm’s activity system, seeking to connect the internal perspective pertaining to resources and routines with the external perspective relating to partners, markets and customers [13–15]. Hence, the business model articulates how the firm implements its strategy and operates in the market.

S. Rama Murthy et al.

To achieve this, a business model needs to clarify the firm’s value proposition to the customer. The business model usually consists of four components, including value proposition, value creation, value capture and value network [16]. The four Vs are part of the complex system of business models, as shown in Fig. 3.1, which demonstrates what value is proposed to connect its customers, how value is created, how value is captured and also what network is interrelated in linking its partners [16]. These can be summarized as the four key components of a firm’s business model. Business models help us to understand how value is created by the firms, the capture of value in terms of revenue streams, the value proposition of firms, and the partners in the value network, in order to achieve their business strategies in the additive manufacturing industry. This chapter showcases the importance of business models for understanding the additive manufacturing industry. Business models not only explain the revenue streams of additive manufacturing but also offer insights into the structure of the industry itself. This chapter delineates the business models of emergent and established firms in the AM industry in terms of the four Vs outlined above. Four case vignettes are presented: two each for emergent firms and established firms. The emergent firms presented are Stratasys and 3D Systems – their business models illustrate how they first sought to develop the market for additive manufacturing before pivoting their business models for economic viability. The established firms presented are Hewlett-Packard (HP) and General Electric (GE) – their business models instead illustrate that these firms adopted additive manufacturing to advance their broader corporate strategy.

Value network

Value proposition

Value creation

Business model

Value capture

Fig. 3.1 The four Vs business model. (Source: Adapted from Velu [16])

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Business Model Innovation in Additive Manufacturing Equipment Sector

Taken together, the actions of such emergent firms and established firms explain the business rationale for the structure and relationships in the additive manufacturing industry. The remainder of this chapter is as follows. Section 3.2 offers four case vignettes. Section 3.3 discusses the business model design in these four firms and four other nascent firms and the managerial implications. Section 3.4 presents the conclusion.

3.2

Case Vignettes

Additive manufacturing went through a phase of market awareness and exuberance, which saw increasing stock prices for manufacturers, attracted substantial funds for acquisitions and mergers and triggered intensive competition in the industries among different types of business [17]. To compare the difference in their business models, we selected firms that could provide the contrast between emergent and established firms, reflecting the various iterations of the business activities. In this section, we examine four firms, including two emergent firms and two established firms, to provide the case vignettes of business model innovation in the additive manufacturing sector. In the first case, we examine one of the emergent firms, Stratasys, a global leader in 3D printing and additive solutions, materials and services. In the second case, we examine the other emergent firm, 3D Systems, the inventors of 3D printing and a worldwide provider of 3D printers, materials, CAD software, and a parts-printing service. In the third case, we examine the business model innovation in an established firm, HP, a mature information technology company that developed and provided a wide variety of hardware components, software, and services. In the last case, we examine the other established firm, GE, a multinational conglomerate that operates through multiple segments: aviation, health care, power and energy, digital industry, venture capital, and finance.

3.2.1

Emergent Firm: Stratasys

Founded in 1989, Stratasys is an American–Israeli manufacturer of 3D printers and 3D production systems for in-office prototyping and direct digital manufacturing. The early core technology provided by Stratasys is the Fused Deposition Modelling (FDM) technique, which is now prevalent across the three-dimensional printing sector. Following the successful invention of this technology, Stratasys has developed ways in which shapes could be created accurately, layer by layer, ultimately aiming to automate the manufacturing process. Since selling its first product, the 3D Modeler, in 1992, Stratasys has gone on to create the first thermoplastic for threedimensional printing, and got listed on the NASDAQ in 1994. To obtain and establish competitive advantage in rapid prototyping, Stratasys acquired the rapid prototyping intellectual

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property of IBM and employed 16 former IBM engineers who had been developing a small 3D printer based on an extrusion system. FDM by Stratasys became the best-selling rapid prototyping technology in 2003. Stratasys has since become one of the most innovative companies in additive manufacturing, introducing the first three-dimensional printer for production in 2008. By merging with Objet, a privately held additive manufacturing company, which distributed 3D printers worldwide, Stratasys consolidated its position as a market leader in 2012. Apart from technology, their combined marketing and sales capabilities extended the geographic reach of the company. Their industry customers were different too – Stratasys catered to Caterpillar, Xerox and Honeywell, while Objet served Adidas, Intel and Mercedes; their combined entity thus had an improved market share. Stratasys operates in the automotive, aerospace, medical and industrial sectors. It has also explored applications in entertainment and consumer goods. As an early company in additive manufacturing, it had the added burden of educating the market and raising awareness among design and student communities. While the company’s initial business model was based on the sale of printers, it has increasingly servitized its value proposition to its customers. Servitization is the process of shifting a company’s offerings from the traditional sale of goods to a bundle of products, services, and ongoing support [18, 19]. The company has developed its broad expertise in additive manufacturing technologies through large-scale acquisitions. These acquired companies have added significantly to the patent portfolio held by the company. Stratasys has spent over $2.2 billion on acquisitions, working out at an average of approximately $200 million per acquisition. Some of the major acquisitions by Stratasys were Makerbot, Solid Concepts, and Harvest Technologies. The company has explored business-to-consumer and business-to-business segments differently. It offered desktop printers to hobbyists and manufacturers for the purpose of making plastic models and prototypes – its acquisition of Makerbot in 2013 at $403 million was carried out to improve this business. Stratasys launched Makerbot retail stores in several major US cities to target the relevant consumer segment. Another attempt to reach the consumer segment was through a retail printing partnership with UPS and FedEx, whereby Stratasys sold printed parts to consumers through UPS and FedEx locations. By 2017, Stratasys had curtailed its ambitions for these desktop printers, focusing on professional printers instead. Its experiments with professional printers for the business-to-business segment have been more successful. Stratasys started developing its direct service bureau, RedEye, in 2005, through which it offered the sale of printed products to industry clients. Its later acquisitions of Solid Concepts and Harvest Technologies have expanded this direct service bureau. Industry clients can order a small number of prototypes, or large-volume production runs

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through this direct manufacturing. In 2011, the company explored the monthly leasing of printers with supplies, and built a digital platform through acquisitions. Since 2015, Stratasys has also offered consulting services to help manufacturers via its acquisition of a consulting firm, Econolyst [20]. Stratasys has been building its expertise in various additive manufacturing technologies, while experimenting with diverse sectors, market segments and business models. Some of these experiments have been more successful than others. Today, Stratasys manufactures in-office prototyping and direct digital manufacturing systems, and it prioritizes the professional market segment. Its collaborations are primarily for design software.

3.2.2

Emergent Firm: 3D Systems

Another pioneering firm in additive manufacturing is 3D Systems, an American technology company founded in 1986. 3D Systems became one of the first 3D printing companies, after its co-founder Chuck Hull filed the patent for stereolithography apparatus (SLA) in 1984. Prior to the introduction of SLA rapid prototyping, it was complex, timeconsuming, and also costly to produce concept models. The innovation of SLA reduced the amount of resources needed and increased the quality and accuracy of producing the concept models; it also made it feasible for commercial applications. 3D Systems mainly offered rapid prototyping through its SLA technology. It is a design-to-manufacturing solutions provider that sells additive manufacturing printers, scanners, and feedstock materials; it also offers a printing service. The early offering of the company was in rapid prototyping through its stereolithography technology, where 3D Systems helped companies to rapidly design and develop prototypes before committing to costly production. The initial years of additive manufacturing coincided with the early years of the company itself. 3D Systems, therefore, had to educate manufacturers, engineers and designers through technology demonstrations and educational events. Over the decades, 3D Systems adopted an aggressive acquisition strategy. It acquired more than 50 companies when the additive manufacturing sector was exuberant, but most of these were small-scale acquisitions, averaging less than $5 million per acquisition. These acquisitions helped 3D Systems to build its digital platform, through which the firm has interacted with its clients and more broadly shaped its business model. 3D Systems has long explored revenue streams from services to complement its sale of hardware. This can be seen in two facets of the company’s strategy: the digital platform and material sales. The digital platform has enabled a direct manufacturing service for 3D Systems and driven

design productivity for clients. Taken together, this has helped in educating designers and enhancing the market. As early as 2008, 3D Systems enabled designers and engineers to experience additive manufacturing through Pro-Parts, its online rapid prototyping and manufacturing parts service with online pricing guidance, for non-commercial parts [21]. Acquisitions such as Geomagic (in 2013) and Cimatron (in 2015) helped 3D Systems to improve its CAD/CAM expertise to span design, scanning, and manufacturing across industry sectors, including die and mould, tooling, and functional end-use applications. Software has also helped with productivity enhancement for clients. In 2018, it partnered with Dassault Systèmes, the publisher of Solidworks CAD software, offering 3DXpert as complementary software to help designers optimize designs for additive manufacturing. It has helped its clients to streamline 3D scanning and printing for plastic and metal additive manufacturing. Such a digital platform also helped it to offer a manufacturing service bureau. For example, its 2014 acquisition of Robtec, a Brazilian additive manufacturing service bureau, expanded its Quickparts service offerings to Latin America. 3D Systems has since launched e-commerce sites for its industry printers. The other non-hardware revenue stream is from the materials business. This is similar to the traditional 2D desktop printer model, where the bulk of the revenue is derived from feedstock sales. Printers planted at client sites can later be harvested through materials sales [22]. This approach has been developed further over the years. In 2020, the company completed material testing to ASTM and ISO standards and made the data available to manufacturers [23]. 3D Systems has also built collaborations beyond software. It has had a long-standing collaboration with BMW, including on-demand manufacturing services for 3D Systems to print design and functional prototype parts, tools, and fixtures for BMW [24]. In the defense sector, 3D Systems has collaborated with aviation firms and even US Navy shipbuilding. The 3D metal printer at the shipbuilding site produces marine-based alloy replacement parts for castings, as well as valves, housings and brackets [25]. Its emphasis in recent years has been its Figure 4 Production platform for industry customers, who can use its 3D systems software and its broad range of materials.

3.2.3

Established Firm: Hewlett-Packard

Hewlett-Packard’s ambition is to disrupt the industrial and manufacturing sector and to become a key player in the Fourth Industrial Revolution through additive manufacturing [26]. Hewlett-Packard (HP) is a Silicon Valley technology pioneer, founded in 1939. The Hewlett-Packard Company (1939–2015) offered hardware, software, and services to a

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wide range of customers. In 2015, the Hewlett-Packard Company bifurcated into HP Inc. and Hewlett Packard Enterprise. HP Inc. focuses on personal computers, printers, scanners, and other hardware devices, including additive manufacturing printers. Hewlett Packard Enterprise focuses on servers, data storage, and cloud computing. For HP Inc., the traditional rivals in printer making have been companies such as Canon and Xerox. The traditional 2D printer business model has relied on providing the initial hardware at a low price, with the bulk of the revenue accruing from the necessary complementary products and services, in this case, the ink cartridges as consumable supplies. However, emerging technology such as additive manufacturing required a different business model design from HP. For instance, firms with emerging technology in additive manufacturing needed to invest more not only in technology research and development but also in educating the market, while established firms usually need to maintain the advantages in their business models and may extend their services to enrich their value networks. The company’s broad vision is to usher in the Fourth Industrial Revolution through technology disruption driven by additive manufacturing. HP has been scoping out the additive manufacturing industry for many years. As far back as 2010, HP entered an agreement with Stratasys, a pioneer in fused deposition modelling technology, for the latter to manufacture HP-branded 3D printers. They used FDM technology patented by Stratasys, and the devices were desktop printers for the prototyping of small build sizes. HP marketed and distributed these products globally through its vast sales channels. It hoped to reach 3D designers who were using HP’s 2D printers. This agreement with Stratasys was discontinued in 2012, and in 2013, HP announced its plans to develop its own technology and manufacture its own device for additive manufacturing. With the benefit of hindsight, we can identify two limitations in the collaboration between HP and Stratasys. First, they were using FDM, a type of legacy technology with a print quality not well suited to production applications. Second, the market for desktop printers, which could be catered to by this collaboration, was not becoming mainstream, as initially predicted. We can now see that industrial-grade applications in the business-to-business market were a better target for companies to pursue. In 2014, the parent company split into two, with additive manufacturing falling under HP Inc. HP initially planned to build on its printer heritage and to make up for revenue shortfall in its core computing business [27]. The company today offers additive manufacturing capability through its Multi Jet Fusion (MJF) technology, which offers engineering-grade materials with great overall properties at the site of the client, thereby bringing the client into the Fourth Industrial Revolution. These products offer two uses for the customer: in-house rapid prototyping and final part

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production. The company offers a 3D-as-a-service subscription business model. This facilitates automatic replenishment of 3D supplies, tracking of billing and usage, and support services, including a pay-per-build service. This relies on the use of hardware, data, software and services. HP is developing two key collaborations: materials and software. The company has been developing an open materials platform engaging with over 50 materials manufacturers, including BASF, Arkema, Evonik and Lehmann & Voss. This offers a wider portfolio of materials to HP’s customers through its printers. Innovative specialty chemicals companies can generate revenue for themselves through this open materials platform [28]. Similarly, HP has also collaborated on software. Siemens is a seller of product lifecycle management software. HP and Siemens collaborate on additive manufacturing factory optimization, performance analytics, and data intelligence. HP has also collaborated with Dassault Systemes, the publisher of the Solidworks 3D modelling program, which is popular among designers and engineers, to help them reimagine products for additive manufacturing production. It is also important to understand the choices that were available to HP and the strategic rationale behind choosing how to participate in additive manufacturing. HP chose to focus on developing the technology and offering the hardware, while letting other companies capture revenue in materials and software. The core competency of HP guided the company to offer a hardware platform upon which other companies could offer material choices.

3.2.4

Established Firm: General Electric

General Electric (GE) is arguably one of the longestestablished technology companies in the world, founded in 1892 [29]. Its key segments in the twenty-first century are aviation, health care and power. GE has been exploring additive manufacturing applications in aviation and health care. Because of its long history in these sectors, it has a deep understanding of customer needs, quality requirements and part certification. GE’s approach is characterized by a reduction in engineering costs for high-value complex metal parts [30]. Its foray into additive manufacturing can be illustrated through its applications in aviation. General Electric is using additive manufacturing to produce complex fuel nozzles for its next-generation commercial jet engine in partnership with French firm Snecma. Each of these engines has up to 20 such fuel nozzles. By employing additive manufacturing in its design of jet engines, GE could reduce the number of components from 900 to just 16, making the LEAP engine 40% lighter and 60% cheaper; the reduction in components also reduced the number of suppliers GE depended on [31]. This LEAP engine is used in the

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Established firms

Emergent firms

Airbus A320neo. Similarly, GE went from having approximately 800 parts to fewer than a dozen parts in its turboprop engine [32]. As a designer of aircraft engines, GE benefited from a one-third reduction in development time for the engine [31]. By using additive manufacturing for castings, rather than a ceramic mold, GE’s production process became more efficient. More broadly, since GE’s set-up expenses have been reduced, additive manufacturing is well suited to short production runs. This efficiency improvement results in cost savings for GE when producing aviation parts. The additive manufacturing business model is also applied in General Electric’s health-care business. GE is applying additive manufacturing to the manufacture of ultrasound probes, which are used to produce ultrasound imagery of patients [33]. GE employs additive manufacturing to reduce the time it takes to cut and refine patterns on the probe face. The cost reduction is a benefit for GE when delivering these products to its regular health-care clients. While HP chose to partner with materials developers and software companies, GE chose to acquire instead. In 2016, GE acquired Arcam and SLM for around $1.4 billion. Arcam had invented the electron beam-melting machine for printing metals and also produced advanced metal powders. SLM produced laser machines for metal-based additive manufacturing. Both firms were also serving the aviation and health-care sectors, where GE has interests. The Arcam investment was intended to grow the company’s additive manufacturing base outside GE and across multiple industries. Arcam continues to be based in Sweden, specializing in orthopedic implants and aviation. Its business model is based on the sale of its additive manufacturing machines at client sites [34], unlike the GE aviation example. These acquisitions also boosted GE’s in-house research expertise on

1986: 3D Systems is founded 1989: Stratasys is founded

2001: 3D Systems starts aquiring various companies

materials and digital productivity. GE was a supplier of additive manufacturing parts to its clients but a customer of additive manufacturing technology itself. Bringing Arcam and SLM in-house therefore reduced the design and material costs for GE [35]. Further insights into this are available. In 2013, GE acquired the Italian company Avio Aero, which had been a supplier of mechanical transmission systems to GE for around three decades [36]. Avio Aero was itself a client of Arcam for additive manufacturing machines. In 2016, GE’s acquisition of Arcam expanded its business boundary to include its earlier tier-one supplier, Avio Aero, and in turn its tier-two supplier, Arcam. A timeline highlighting the key events for Stratasys, 3D Systems, HP and GE are shown in Fig. 3.2.

3.3

Discussion

3.3.1

Comparison of Business Models of the Four Cases

Additive manufacturing has grown from an initial prototyping application into a core production technology. Such growth and acceptance of additive manufacturing as a core technology is in part to do with the design of appropriate business models to create and capture value from the technology. Our case vignettes show that the delivery of the customer value proposition of additive manufacturing technology informs the design and evolution of the business models. We studied two emergent firms and two established firms, and how they adopted additive manufacturing technologies and designed and evolved their business models. Next, we compare compare and contrast their respective

2008: 3D Systems offers an online rapid prototyping service called proparts for designers and engineers

2005: Stratasys develops RedEye, a direct service bureau

2012: Stratasys merges with Objet

2013: Stratasys acquires B2C firm Makerbot for $403 millon, 2015: shrinks its B2C ambitions by 2017 Stratasys offers 2012: 3D Systems launches the Cube consulting printer for B2C market, exits the B2C services market by 2016

2010: HP sells HP-branded 2013: HP Stratasys-made printers, announces plans to discontinued in 2012 develop its own technology and manufacture its 2011: GE develops own device for additive manufacturing additive processes for ultrasound manufacturing transducers

2016: GE uses additive manufacturing for nozzles in LEAP jet engine and turboprop engine 2016: GE acquires Arcam and SLM for $1.4 billion

Fig. 3.2 A timeline of Stratasys, 3D Systems, HP and GE in additive manufacturing sector

2016: HP invites materials firms onto an open materials platform 2017: HP unveils a 3D open materials and applications lab for partners to use

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approaches and discuss why the business model lens is important to better understand how, and why, new technologies such as additive manufacturing come to be adopted as a core technology. We first compare the business models of the emergent firms with the established firms. Then, we compare the business models of the two emergent firms and then the established firms among themselves. Table 3.1 provides the summary of the business models of these four firms. Let us first compare the business models of the emergent firms with the established firms. The emergent firms, Stratasys and 3D Systems, were start-ups from the very beginning of the development and commercialization of additive manufacturing. Hence, their business model design had two principal phases. The first phase was the market awareness phase, and the second was the market maturation phase. Both Stratasys and 3D Systems had to develop their business models in the market awareness phase, where the principal objective was to educate the market about the benefits of additive manufacturing. This took the form, for example, of Stratasys opening high-street branches through its Makerbot subsidiary, where customers could learn and use additive manufacturing technologies. 3D Systems and Stratasys also pivoted their business model from merely selling printer equipment to a bureau model whereby 3D printers are rented to third-party firms to deliver printing services to their customers. For example, Stratasys rented additive manufacturing machines at UPS and then FedEx stores in order to entice customers to use the service to print

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and send objects to friends and family. The business model for such awareness-building activities often did not generate sufficient income to be viable on its own, and they were eventually closed down, although they did help to educate the market about the benefits of the technology. On the other hand, both HP and GE entered the market for additive manufacturing in a more mature phase when customers were more aware of the benefits of the technology. In the case of GE, this was driven by the needs of its own aviation and health care businesses, while for HP the stagnating revenue from its core printing business prompted the firm to build a business to disrupt the manufacturing sector, as it was beginning to embrace industrial digital technologies. We now compare the business models of the two emergent firms between themselves. Stratasys and 3D Systems initially focused their business model design on addressing market awareness. Subsequently, the firms went on to develop their business models to cater for their relevant customer segments. For example, 3D Systems had more revenue from services compared to Stratasys [37]. To gain competitive advantage, Stratasys decided to acquire Econolyst, an additive manufacturing consultancy and research firm, to complement the sales of additive manufacturing machines. In addition, the distribution of the machines was an important aspect of Stratasys’s business model. The importance of distribution, together with the complementary nature of the technologies and customers, prompted Stratasys to integrate with Objet through a reverse takeover in 2012.

Table 3.1 Comparison of business models Firm Stratasys

3D Systems

HP

GE

Value proposition Customers can install additive manufacturing capability at their site or digitally order parts to be printed and shipped to them 3D Systems offers an additive manufacturing platform, including hardware, materials and software support Manufacturing clients derive better design capability through the installation of additive manufacturing capacity at their site

Clients of GE benefit from parts that are more durable, lighter and efficient

Value creation Stratasys develops technologies, produces machines and manages the online platform for direct digital manufacturing

Value capture Stratasys generates revenue from equipment sales and shipping printed parts and through support services

Value network Collaboration with design software firms

3D systems develops the technologies and maintains online platforms for support

Revenue is from printer sales and services, with an emphasis on services

Collaboration with design software firms, materials firms and customers through on-demand manufacturing

HP is developing its multi jet fusion technology, which is the basis for its hardware products. These hardware products are a platform upon which other companies – such as material developers and software developers – provide their offerings GE is developing in-house equipment that it uses to make advanced components for its clients

Revenue is generated from the sale of hardware and through a 3D-as-a-service model

HP concentrates on hardware while collaborating with materials companies through an open platform, partnering with software companies for CAD and product lifecycle software

Additive manufacturing improves production efficiency and reduces production costs within GE’s factory when making parts for clients. This offers cost savings for GE

GE leveraged the network of collaborators through its acquisition of Arcam and SLM

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Comparing the business models of the two established firms between themselves also provides some interesting lessons for business model design. GE was driven primarily by the need to build internal capability for using additive manufacturing technology that was becoming core to its aviation and health-care businesses. For example, in aviation, because of the increasing pressure to reduce costs in a competitive marketplace, GE needed to make its engines cheaper and also more reliable. Additive manufacturing provided the core technology to make more efficient parts, such as fuel nozzles, and also to reduce the number of parts in the engine to increase its efficiency and reduce maintenance costs. GE’s increasing reliance, in terms of the provision of maintenance services, on a subscription model for its engine meant that having more reliable engines would increase GE’s own profitability. Hence, the purchase of Arcam brought with it a network of complementary partners in its value network, which in turn complemented GE’s capabilities in design engineering. HP, meanwhile, intended to disrupt the manufacturing industry with an industrial additive manufacturing proposition. Since HP did not have core capabilities in the production process itself, it had to build relationships with other complementary providers such as materials and software design capabilities.

3.3.2

Value Network as Investor Community

There are also other emerging companies in additive manufacturing that adopt different business models, including Desktop Metal, Ultimaker, Prusa, and Carbon. Founded in 2015, Desktop Metal is one of the more recent start-ups in additive manufacturing. With deep links to research conducted at MIT, it is an American company that has long focused on the printing of metals. Metal printing has typically been unsuited for office spaces where engineering and design teams work; apart from the cost being prohibitively high, the process is potentially dangerous when lasers are used to melt metals at high temperatures. Desktop Metal overcomes these challenges to make metal 3D printing affordable and accessible [38]. Desktop Metal offers two different technologies – one for desktop prototyping in the office, and one for shopfloor production. Its office-friendly offering [39] does not use lasers or hazardous materials and is compatible with standard wall outlets. It is based on a proprietary technology where the printer extrudes a mixture of metal powder and polymers to build up a shape, which is then placed in a furnace to burn away the polymers and compact the metal particles together. The metal is fused into shape without reaching its melting point [40]. This desktop office offering has been shipped since 2017 [39]. Its offering for the shopfloor was launched in 2019, to enable high volumes of affordable production [41]. While GE prioritized high-end

machines, Desktop Metal did not pursue the same market. Its competition was more from established metal-processing technologies. Desktop Metal’s technology can print steel, aluminum, copper, and even alloys. It has now expanded beyond metals and into materials such as carbon fiber, photopolymers – through its acquisition of EnvisionTec – and even wood as a material [42]. Given the company’s focus on metals, it is unsurprising that its customers are from the automotive and aerospace sectors. Its customers include BMW, Honda, and Lockheed Martin [43]. However, this might be set to change in the future. In 2021, Desktop Metal acquired EnvisionTEC and gained a foothold in the healthcare space for dental, orthodontic, and otolaryngology applications where EnvisionTec has strengths [44]. The revenue streams are from the sale of hardware, materials, and software-as-a-service that helps design optimal parts. The sale of the printer hardware opens the recurring revenue stream from materials and SaaS. A key highlight of Desktop Metal is that its investor community is also its value network. When it was still a private company, its investors include potential customers and other technology companies such as Ford Motor Company, BMW iVentures, Stratasys, and Google Ventures. Ford’s engineering team started working with Desktop Metal in 2016. Ford became an investor in 2018 and was among the first customers for Desktop Metal’s officefriendly version [45]. Similarly, BMW became an investor in 2017. Stratasys, which was an investor since 2015, became a distributor of Desktop Metal in 2017. In December 2020, Desktop Metal was publicly listed on the New York Stock Exchange through a Special Purpose Acquisition Company [46]. Another company that merits attention for a similar reason is Carbon3D Inc. Carbon is a Silicon Valley-based company founded in 2013, which again illustrates an overlap between its value network and its investor community. Carbon employs a layerless 3D printing technology called Continuous Liquid Interface Production. This polymer-focused technology employs light and oxygen to grow shapes from a pool of resin. It uses a photosensitive resin which reacts to ultraviolet light and oxygen, thus growing the solid object out from the liquid bath of resin [47]. This printing technique has often been compared to imagery from the Terminator movie franchise [48]. Carbon supplies the liquid resins needed for using its technology. Carbon has also partnered with other firms such as Kodak to jointly develop materials for this purpose. In the strictest sense, such a production technology would not be adding multiple layers of material. Conventional layer-upon-layer additive manufacturing takes many hours to produce parts and are mechanically weak. Carbon’s technology can draw complex solid parts from the resin at rates of hundreds of millimeters per hour, which is faster than its competitors. Carbon offers 3D printing of high resolution at a speed 25–100 times faster than traditional

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stereolithographic printers and other processes of its competitors [49]. The materials compatible with this production technique include stretchy elastomers and high-temperatureresistant resins [50]. Given the uniqueness of its technology, Carbon provides the hardware, software, and the materials to its customers. All Carbon materials are sold as liquid resins. Its digitally manufactured polymer parts have been adopted by various companies. For example, Ford has used this technology to make brake brackets, auxiliary plugs [51]. Another key market for Carbon has been in dental healthcare. Carbon has a presence in the dental market through its partnerships with denture providers to produce customized parts. Key collaborators are Dentca, Dreve, and Core3d. Carbon has also developed new dental resins to support its customers. As was the case with Desktop Metal, the value network of Carbon overlaps with its investor community. Carbon remains a venture-capital backed company and has not been publicly traded as of 2021. Its investors include Sequoia Capital, Google Venture, GE, Autodesk, Fidelity Management & Research, Adidas, BMW, and Johnson & Johnson [52, 53]. Adidas and Johnson & Johnson are also partners in other ways to Carbon – the first 3D printed midsole by Adidas is one such example [54].

3.3.3

Open Source Design as Business Strategy

By adopting the business model of open source, source code is open to the public, so that individuals and companies could review, modify, enhance, and use. Increasingly companies have adopted the value proposition to introduce open design projects in promoting the engagement of online user communities, and also to accelerate the transition to local manufacturing and digital distribution [55]. Ultimaker is a Dutch 3D manufacturing company founded in 2011. The products of Ultimaker are manufactured in the Netherlands, the US and Singapore. In its business model, Ultimake creates its value via providing products with open design projects in automotive, architecture, healthcare, education, and small-scale manufacturing. Unlike in-house design, Ultimaker captures its value by combining open design in the process of making fused filament fabrication 3D printers, developing additive manufacturing software, and selling branded additive manufacturing materials. With a distinctive characteristic that allows printers to move the print platform rather than the nozzle in the vertical movement, and also allows users to back up their files to the cloud, Ultimaker could make additive manufacturing easy and hassle-free. Although Ultimaker has a relatively shorter history, it has developed a value network that allows companies and individuals to participate in the design process, and design information can diffuse both inward and outward within a project management team or the user community [56]. Prusa is

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another newly established company that has a business model based on open innovation with source files being publicly available. Prusa is a Czech company started back in 2009, Prusa Research, which consists of open-source fused deposition modelling 3D printers. Its design files are publicly available through Prusa Research, and GitHub. Prusa’s business model creates value by introducing an open-source philosophy that leads to a whole wave of clones with a significantly reduced price. Prusa delivers its service with comparable low-cost, and its open design approach allows for broad co-creation, which attracts a large number of users in education and also small-business ventures [57]. In its value networks, companies and individuals can easily use Prusa for their construction and modification of products and services. With the support of an open source architecture, enthusiasts and professionals from the manufacturer or the community can collaborate with ease, making troubleshooting simpler and allowing DIY enhancements in both hardware and software of additive manufacturing [58].

3.3.4

Managerial Implications

There are a number of managerial implications for incumbent and emergent firms. First, for emergent firms, the need to build business models to increase market awareness is critical. In the case of both Stratasys and 3D Systems, this involved adopting business models, which enabled customers to obtain the benefits of additive manufacturing by de-risking the technology for them. This was done by enabling customers to solve particular problems such as the design of bicycle parts through retail additive manufacturing stores without having to own the machine but using it on a pay-as-you-go basis. Such gradual use of additive manufacturing enabled 3D Systems and Stratasys to help build the market for the underlying machines. Once the market became aware of the benefits of additive manufacturing, customers began to demand solutions based on their experience of adopting the technology. Hence, both 3D Systems and Stratasys decided to build their capabilities both organically and through acquisitions across the spectrum of the product-services architecture needed to serve their customer base. Second, the two incumbent firms followed a wait-and-learn approach to their additive manufacturing strategies. In the case of GE, it was increasingly evident that additive manufacturing could provide the basis for not only reducing the costs of production but also become a key differentiator for its aviation and health-care businesses. For example, in aviation, the purchase of Avio Aero by GE, together with its increasing use of additive manufacturing technology, prompted its strategic move to acquire Arcam. GE’s acquisition of Arcam as a basis for entering the additive manufacturing market was crucial to building the key

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capability to both differentiate its existing products and develop new products with unique functionalities. Building its own capabilities organically would have been too slow. Moreover, GE and Avio Aero were already customers of Arcam, which gave the firm the insights and technological knowhow it needed on the usefulness of the underlying additive manufacturing technology of Arcam and its network. In contrast, HP had knowledge of the printing business and needed to diversify into what it perceived to be an adjacent market, as it knew the principles of the printing business well. Hence, after a period of learning about the additive manufacturing industry through its alliance with Stratasys, HP decided to embrace the manufacturing industry with its own additive manufacturing offering. However, in order to be credible, it had to offer an integrated product–service offering to the market; hence, it needed a whole network of other firms such as BASF and Siemens to be able to provide complementary products and services. Third, the four more-recent emerging firms, Desktop Metal, Carbon, Ultimaker, and Prusa, demonstrate more diverse business models. There firms run different business models in order to compete with the established firms and emergent firms. While Stratasys and 3D Systems spent much of their efforts on educating the market, consumers, manufacturers, students, and investors, this was not a major focus for Desktop Metal and Carbon. There was little need to convince the investors about the potential of the technology and the applicability to their industry – Desktop Metal and Carbon could instead use their value network as their investor community as well. An innovative approach to the value network is also seen with Ultimaker and Prusa, which are exploring value co-creation in additive manufacturing, through open- source design. As the additive manufacturing industry matures, one can expect continued innovation with business models, from both emergent and established firms alike.

3.4

Conclusion

This chapter has provided an overview of case vignettes to illustrate the rationale behind additive-manufacturing-based business model design. We have shown how the strategies of firms to create and deliver customer value proportions helped them to develop their business models accordingly across the key components of value proposition, value creation, value capture, and value network, respectively. There were differences between the established and the emergent firms in terms of business model design strategies. The emergent firms had to develop their business model to help develop the market before redesigning them to make them economically viable. The established firms were able to wait and learn and develop their business models to complement and extend their existing businesses. The research in additive

manufacturing and business model design is very much at a nascent stage, with much more still to be investigated regarding how, when, and why business model innovation is required for additive manufacturing technology-based strategies to contribute to creating competitive advantage. Also, our focus of this chapter is primarily on the B2B sector although we mention some aspects of the B2C sector, while the differences between the B2B and B2C markets still needs more investigation in future studies. We hope that our chapter provides some of the principles for scholars and managers to think about business model design and evolution as firms adopt new technologies. Acknowledgments Chander Velu would like to acknowledge funding from the Engineering and Physical Sciences Research Council (EP/R024367/1 and EP/K039598/1). Jiashun Huang would like to thank funding from Science & Technology Innovation Strategy and Soft Science Research Fund of Anhui (202006f01050001).

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Sudhir Rama Murthy is a Research Associate at the Institute for Manufacturing, University of Cambridge, where he explores how manufacturing operations can cope with global uncertainties. Previously, he was a Research Fellow with the Saïd Business School, University of Oxford, where he researched corporate interventions to tackle societal and environmental concerns. His interests include corporate strategy and sustainable industrialization. He holds a PhD in Engineering from the University of Cambridge.

S. Rama Murthy et al.

Dr. Jiashun Huang is a Research Professor at the School of Public Affairs, and the Institute of Intellectual Property, University of Science and Technology of China. He is also a Senior Research Associate at the Labour and Worklife Programme, Harvard University. He holds a DPhil from the University of Oxford.

Chander Velu is Professor of Innovation and Economics in the Cambridge University Engineering Department where he heads the Business Model Innovation Research Group. He is a Fellow at Selwyn College, Cambridge. Chander has an interest in innovation and technology management with a specific focus on exploring the antecedents and consequences of business model innovation. Prior to joining the Institute for Manufacturing, he was a member of the faculty at Cambridge Judge Business School. Chander has worked as a consultant with PricewaterhouseCoopers and Booz Allen & Hamilton in London.

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Implementation of Additive Manufacturing in Industry Daniel Omidvarkarjan, Ralph Rosenbauer, Christoph Klahn Mirko Meboldt

Contents

, and

Abstract

4.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

4.2 4.2.1 4.2.2 4.2.3

Current State of AM Adoption on an Industry Level . . . Aerospace Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medical Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Automotive Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

56 56 57 58

4.3 Challenges of AM Adoption at a Firm Level . . . . . . . . . . . . 4.3.1 Technology-Related Factors and Challenges of AM Adoption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Organization-Related Factors and Challenges of AM Adoption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3 Adoption Factors and Challenges Related to the Firm’s Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.4 Implications of Implementation Challenges on the AM Adoption Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

58 59 59 60 60

4.4 Case Studies of Successful AM Adoption in Industry . . . 61 4.4.1 Implementation of AM at a SME . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 4.4.2 Implementation of AM at a Large Technology Corporation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.5

Key Strategies for the Focused Adoption of AM . . . . . . . . 65

4.6

Role of Change Management for AM Adoption . . . . . . . . 66

4.7

Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Although numerous successful showcases demonstrated the technological readiness of Additive Manufacturing (AM), its adoption continues to pose a major challenge to industrial organizations. Firms are required to consider a wide range of implementation factors, including AM technology, supply chain, operations, organization, and strategy. This section provides an overview of the AM adoption process. A review of the varying levels of AM implementation is given for the different manufacturing industries. Typical challenges and pitfalls of AM adoption are presented along the AM value chain. Two examples of successful implementation pathways are described to show key factors that enable firms to overcome the hurdles of AM adoption more efficiently. This includes, for instance, a systematic overview of AM-related competences (typical AM learning curve) that firms need to master to fully industrialize AM applications. Within this context, the role of change management is discussed, as stakeholders may hold reservations against the fundamental transformations implicated by the adoption of AM.

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Keywords D. Omidvarkarjan (*) IWK Institute for Material Science and Plastics Processing, RapperswilJona, Switzerland e-mail: [email protected] R. Rosenbauer ETH Competence Center for Materials and Processes MaP, ETH Zurich, Zurich, Switzerland C. Klahn Karlsruhe Institute of Technology, Institute of Mechanical Process Engineering and Mechanics, Eggenstein-Leopoldshafen, Karlsruhe, Germany inspire AG, Zurich, Switzerland e-mail: [email protected] M. Meboldt Product Development Group Zurich pd|z, ETH Zurich, Zurich, Switzerland

Additive manufacturing · AM adoption · AM implementation · Change management · Implementation challenges · Digital process chain

4.1

Introduction

Since the emergence of Additive Manufacturing (AM) in the 1980s, the global AM industry has consistently been growing as an increasing number of organizations have adopted the technology for their products and services [1, 2]. For the past 31 years, the average annual growth rate of the global AM industry amounted 26.7% [3]. In 2019 alone, the overall AM market grew to a size of $11.867 billion, representing a

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_4

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21.2% growth compared to the previous year [3]. While in the beginning, prototyping or cosmetic models represented the leading fields of AM application, in 2019 AM was mostly used for the production of end-user parts (30.9%), followed by functional prototyping (24.6%) and education and research (13.3%) [3]. These numbers indicate that AM has started to transform into a mature manufacturing technology, which has been adopted by pioneers for the production of final products. Yet on a broader scale, the adoption of AM is still at an early stage [4–6]. For many industrial organizations, the introduction of the technology still represents a major challenge [7]. Within this chapter, key aspects of the AM adoption process are presented. Section 4.2 provides an overview of the current state of AM adoption for the different manufacturing industry sectors. Typical challenges and pitfalls of implementing AM are outlined in Sect. 4.3, covering the whole value chain from product development, over operations, supply chain to customer interaction, and AM business models. Two exemplary adoption pathways are presented in detail in Sect. 4.4. With reference to the two case studies, Sects. 4.5 and 4.6 summarize key factors that enable organizations to overcome hurdles of AM adoption more efficiently. Section 4.7 provides a discussion on managerial implications and future research potentials for the field of AM implementation.

4.2

Current State of AM Adoption on an Industry Level

When comparing the different manufacturing industries (see Fig. 4.1), varying levels of AM adoption can be found. The aerospace and medical industry constitute the most mature sectors when it comes to AM implementation [3]. Both Fig. 4.1 Maturity of AM implementation across different manufacturing industries. (Informed from Fontana [9])

verticals started from very early on to include AM into their value creation process and acted therefore as main drivers for the industrialization of AM in general [8]. Within this section, the current state of AM adoption is presented for the manufacturing industries aerospace, medical, and automotive. The description includes an overview of how far the respective sectors have progressed regarding AM adoption, what challenges they faced and how they were able to overcome them.

4.2.1

Aerospace Industry

When 3D Systems released the first commercially available stereolithography machines in the late 1980s, various firms of the aerospace sector (such as Pratt & Whittney) belonged to the first customers [8]. In the subsequent decades, all major aerospace companies in the USA and Europe have adopted AM for their products and systems, making it one of the leading industry verticals regarding AM implementation. Boeing, for instance, started in the 1990s to use polymer AM parts for non-structural applications. Since then, the use of AM spread throughout their product portfolio, including also final production parts of both plastics and metal [3]. By now, Boeing has installed more than 60,000 flying parts in 16 different commercial and military aircrafts [3]. To coordinate the implementation of AM on a corporate level, Boeing introduced a top-level organization specifically focused on AM in 2018. A similar development can be seen at Airbus. Their A350 model contained already more than 1000 individual components manufactured using AM by 2015 [8]. General Electric began in the early 2010s to heavily invest into metal AM. After intensive internal research and development and several significant acquisitions (e.g., AM

Experimental Early mainstream Early adoption (laboratory environment) (production demonstrated) (low rate production)

Metal

Electronics

Mature (full rate production)

Medical Automotive

Aerospace

Industrial goods Consumer goods

Polymer

Aerospace Automotive Industrial goods Consumer goods

Medical

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machine manufacturers and service providers), numerous showcases and product releases followed [9]. Compared to other industry verticals, the aerospace sector especially benefits from AM’s capability to generate highly complex structures, since their parts typically need to meet extreme functional requirements (e.g., in terms of mechanical strength, fatigue, or temperature resistance) [10]. Conventional machining is reaching its limits for such applications due to the high degree of material waste (up to 95%) [11], especially when considering the high material price of the specialized raw materials used in the aviation industry. In addition, functional integration enabled by AM is also highly relevant for aircraft components, since it further reduces part costs and weight, while also eliminating potential sources of error in assembly and production [10]. By combining lightweight materials such as Titanium or Aluminum alloys with highly optimized designs, the weight of structural aircraft parts such as brackets can therefore be significantly reduced, often times down to 50% of the original mass [12, 13]. With fuel expenditures dominating the operational costs (up to 25%) [14], the use of AM for structural components therefore results in large cost savings over the aircraft lifetime. Also from a supply chain perspective, AM offers significant advantages to the aviation industry. With low production volumes and long product lifetimes being common in the aerospace industry [15], AM represents an economically viable alternative to traditional machining technologies, since it enables the direct fabrication of parts and their rapid replacement in case of failure. Overall, the aerospace sector acted therefore as a main driving force for the industrialization of AM in general [8]. Several innovations in advanced AM materials such as Scalmalloy have been initially developed for use in aerospace applications [16]. Furthermore, the aerospace industry contributed greatly to the topic of AM qualification, since their parts are subject to the very high certification hurdles [17]. AM quality procedures initially developed for aviation applications are increasingly used in other industry sectors as well.

4.2.2

Medical Industry

Some of the most successful examples of AM implementation have emerged from the medical industry [18]. This is due to the fact that medical applications provide particularly good preconditions for the use of AM. On the one hand, there is the need for patient-specific solutions, which are based on the individuality of human bodies as well as disease patterns [19]. On the other hand, three-dimensional data sets are readily available, for example, from computer tomography or magnetic resonance imaging [8]. These can be used as a basis for the design of individual solutions produced with AM [20]. A positive factor in this context is that as early as

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1985, a now widely used exchange standard was created with the Digital Imaging and Communications in Medicine (DICOM) format, which has significantly supported the introduction of a digital process chain [21]. Also surface scanning (via photogrammetry, structured light scanning or laser scanning) is becoming more common, enabling the rapid and cost-effective capture of patient-specific external features [20]. Because of these two beneficial characteristics, AM has been used in a wide range of medical applications for decades. One of the earliest examples is the production of implants using AM, dating back more than 20 years [3]. Despite their advantages, such as an improved connection between bone and implant due to a rough surface, the introduction of AM implants is hampered by the complex approval process [22]. This area of concern is increasingly being considered, resulting in the US Food and Drug Administration (FDA) issuing a guidance document on the use of AM for medical device manufacturing in 2017 [23]. In other medical fields such as dentals or hearing aids, AM has surpassed the stage of niche application, disrupting existing value chains and significantly altering established workflows [24]. Whereas before, mostly manual crafting by highly skilled individuals took place, the introduction of AM enabled a largely automated process [25]. As a result, AM has by now become the industry standard for many dental products such as copings. These are load-bearing structures for bridges and crowns that are manufactured in large quantities either directly from Cobalt Chromium alloys (CoCr) using Laser Powder Bed Fusion (PBF-LB/M) or through an indirect casting process with PBF-LB/M master moulds [3]. PBF-LB/M is also used for the production of dental implants made from Titanium, which are inserted directly into the jaw. In addition to these two metallic AM use cases, there is also a large market for polymeric AM applications within the medical industry [19]. These include, for instance, dental aligners produced by thermoforming over AM patterns or earpieces for hearing aids. Their success can be explained by the creation of a fully digital process chain [26]. By combining AM’s freedom of design with an highly automated design and production process, the parts are perfectly fitted to the patient’s anatomy while being economically viable. As a reference, 99% of hearing aids on the global market are manufactured with the aid of AM already from 2016 onwards [18]. In this context, the relatively small part dimensions, high variety of shapes, and high selling price are ideal for the serial production with AM. These successful examples with high market penetration demonstrate the importance of selecting products suitable for AM at the present stage of AM maturity. In addition, AM has also started to make its way into regular hospitals. Here, first applications often start with the use of existing three-dimensional data sets for the creation of physical models for surgery planning and support [18]. In addition, such models can also be used for the education of

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medical students and patients briefing [27]. They are particularly well suited as a first step for the implementation of AM, as they are not associated with high requirements on material and part properties. More demanding applications within the hospital context are drilling templates or patientspecific medical instruments, due to their contact with the surgical site [19]. For the near future, it is expected that falling costs of AM will make an increasing number of medical products economically viable for AM. Further perspectives for the use of AM in the medical field arise from bioprinting, i.e., AM with embedded living cells. This process is intended to enable the production of tissue, e.g., for reconstructive surgery. So far, this process is still in the early stages of development and has not yet reached serial application [28].

4.2.3

Automotive Industry

The automotive sector constitutes the largest end-user of AM with a market share of 16.4%, surpassing other industry verticals such as consumer goods (incl. electronics, 15.4%), aerospace (14.7%), and medical products (incl. dental, 13.9%) [3]. Furthermore, it has been one of the earliest adopters of AM with first investments dating back more than 30 years ago [3]. Nevertheless, there are only few serial applications of AM in the automotive sector, especially compared to other industries such as medical products. So far, they are limited to low-volume productions of high-end models. These include, for example, window guide rails for the BMW i8 Roadster produced with Multijet Fusion (MJF) [29] or metal brackets for its retractable roof [30]. The latter part is considered in academic literature to be the first series application in the automotive sector [8]. This discrepancy between largest AM market share and low penetration of series applications can be linked to the characteristics of the automotive industry: With few exceptions, automobiles are mass-produced goods. This combination of high production volumes, large part dimensions, and very strict requirements on costs make the economical series production with AM hardly possible. Moreover, fuel savings enabled by lightweight design are not as significant for cars due their shorter lifespan, especially compared to airplanes. For this reason, the use of AM in the automotive industry is limited to applications such as rapid prototyping or jigs and fixtures for production and assembly [8]. A certain exception to this are cosmetic AM end-user parts that can be personalized through configurators. Such are offered to customers, for example, by MINI [31]. Another important niche is motorsports, where very small part quantities are present and lightweight design is a key requirement. A further promising application field of AM in the automotive industry is the

production of spare parts. This applies in particular to interior components, which are only required in very small quantities at the end of the product life cycle. Here, a new production runs would often times no longer be economically feasible. Overall, the automotive industry thus provides an interesting perspective on AM implementation. It shows that being an early adopter of AM does not necessarily correspond to a high level of series production, since other factors (in particular the cost structure and economical viability) play a central role.

4.3

Challenges of AM Adoption at a Firm Level

Even though the maturity of the technology has been affirmed with aforementioned success stories on an industry level, the adoption of AM is still a major challenge for both large corporations or small- and medium-sized enterprises (SME) [5]. Overall, the key issue of AM implementation is the limited amount of AM expertise that is available at the beginning of the adoption process [32]. The implementation of AM is therefore first and foremost a learning process in which firms are required to advance their AM knowledge through active learning [33]. As the AM ecosystem is still evolving at high speeds, firms find themselves in a dynamic environment that requires constant knowledge advancement [32]. In comparison to the introduction of other manufacturing technologies, the adoption of AM stands out due to the distinct characteristics of the process. As manufacturing costs are in theory independent from both geometrical complexity and production quantities, AM fundamentally differs from conventional production techniques, leading to a paradigm change in manufacturing [8, 34]. Furthermore, AM offers an unprecedented potential for seamlessly integrated, digital process chains, enabling decentralized supply chain networks and novel value creation models [9, 35]. The implementation of AM leads to a wide scope of innovations which can range from incremental improvements to disruptive implications that change entire industry dynamics [36]. As a result, firms are often times overwhelmed by the opportunities and potential implications of AM adoption. They are required to consider numerous factors along the whole AM process chain, including technology, strategy, supply chain, operations, and organization [37]. This section provides a description of recurring challenges firms typically face when implementing AM. A selection of them is depicted in Table 4.1, illustrating the range of potential issues firms are confronted with when adopting AM. In the following, the most relevant challenges of AM adoption are elaborated in detail, including a description of potential developments from industry and academia that address those issues.

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Table 4.1 Common challenges of AM adoption Challenge to AM adoption Limited process predictability and repeatability Characterisation of materials and processes is still at an early stage Need for post-processing with high resulting costs High cost of investments, operations and maintenance Few standards and part certification procedures Lack of clear AM adoption strategy on firm level Inability to identify value-adding applications Lack of adapted business models that tailor to AM potentials Lack of accurate cost-calculation models Uncertainty around ownership of digital designs that leads to unclear product protection Limited knowledge of AM technology and design Lack of highly skilled AM personnel as dedicated educational tracks are missing Unstandardized data transfer that leads to insufficient accuracy and quality of design files Lack of integrated digital process chain from designer to machine Customers not yet familiarised with AM parts (shapes, materials, surfaces, haptics)

4.3.1

Area Technology

References [38]

Technology

[39]

Technology

[32, 38]

Technology

[38]

Technology

[32]

Organisation

[37]

Organisation

[32, 40]

Organisation

[40, 41]

Organisation

[40]

Organisation

[40]

Organisation

[42]

Organisation

[7, 37]

Environment

[32]

Environment

[32]

Environment

[43]

Technology-Related Factors and Challenges of AM Adoption

As depicted before, AM offers unique technological capabilities that fundamentally distinguish it from conventional manufacturing processes. These include for instance the ability to manufacture highly complex structures in low product quantities, the reduction of waste, simplification of supply chains, increased flexibility and customisation [32, 34, 39, 42]. Nevertheless, several technological limitations and drawbacks are also present for AM. They are mostly related to the materials and process that are utilised. AM is still a relatively slow manufacturing process with lower throughput compared to traditional production technologies [6, 9]. For certain applications, the maximum achievable part dimensions may be not sufficient due to limitations of commercially available AM machines. Furthermore, the selection of AM materials is still rather limited compared to conventional production technologies [44], inhibiting the realization of certain applications or requiring substantial redesign to

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account for the change of material [6]. Due to limited process predictability and repeatability [38], part properties may deviate between different machines of the same AM process or even between batches of the same system. As a consequence, applications with very strict requirements or regulations, such as in the aerospace industry, require great efforts in characterization and validation [45]. Due to the need for postprocessing [32], AM is still associated with a high degree of manual labor, especially for metal based process that use support structures. Overall, the initial and recurring costs of AM represent one of the most dominant barriers of AM adoption [46]. Firms need to invest into equipment, training, machine maintenance, and operation, requiring large financial support for an extended time frame [47]. While these technological challenges may seem daunting to an individual firm, the aforementioned showcases of the industry overview from Sect. 4.2 demonstrate that AM as a technology is already mature enough for certain applications. Recent reviews (e.g., [46]) underline the consensus that the technological benefits of AM greatly outweigh its limitations and drawbacks. Companies are required to carefully judge whether their respective use case is technically feasible and economically viable. Furthermore, recent developments and innovations from both industry and academia are constantly reducing the limiting factor of AM as a technology. These include novel materials, improved AM processes, or software tools for design and simulation [48]. Especially the latter factor experienced a large degree of innovation in the recent years. Automation of design is increasingly becoming more available through improvements in topology optimisation and generative design [49]. Furthermore, there is an increasing amount of software solutions that bridge the entire AM process chain, improving the end-to-end information and data flow across firm boundaries. In addition, supporting technologies of the AM ecosystem are also progressing. For instance, non-destructive testing plays an increasingly important role for the characterization of input materials and parts built by AM, enabling a closed loop monitoring system for the detection of defects generated during the building process [50]. In the past years, an increasing amount of standards have been published by both the International Organization for Standardization (ISO) and the American Society for Testing and Materials (ASTM). In 2020, more than 25 technical standards from ASTM are active with more than 50 additional being under way [51]. It is expected that this development will further improve the quality consistency of AM [48].

4.3.2

Organization-Related Factors and Challenges of AM Adoption

In addition to the aforementioned technology-related adoption factors, the implementation of AM also requires

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consideration of business and social aspects within the adopting organization [52]. This is due to the fact that the implementation of AM typically comes with a need for organizational change, for instance regarding a firm’s strategy, structure and processes [53]. Within this context, firms show varying degrees of organizational readiness for such transformations. This includes for instance a firm’s willingness to adopt AM, or on the contrary, the degree of rejection against change [46]. Depending on the respective organizational culture (e.g., in terms of innovativeness, vision, or strategy), the AM implementation process is facilitated or impeded [46]. Due to the overall importance of change management for AM implementation [33], Sect. 4.6 provides a deep dive on this topic. In addition to a firm’s organizational culture, its prior experience and competence regarding similar digital technologies plays also an important role for the adoption of AM [46]. Firms benefit if their existing production and IT systems are compatible to the digital process chain of AM. Within this context, a strong internal alignment between the research and development (R&D), manufacturing and IT department is also beneficial, as the implementation of AM requires a strong interconnection of those organisational functions [47]. A high degree of technological awareness enables firms to keep up with the most recent developments within the AM ecosystem [47]. With regards to workforce, it can be noted that skilled employees are of utmost importance for the AM implementation process. With AM being only gradually included into the curricula of engineering studies, there is a need for professionals with a deep knowledge of AM [6]. The lack of such trained human resources has an immediate impact on the implementation success, as the inability to identify value adding applications or properly design AM components obstructs the adoption progress [32, 40]. As a consequence, significant reskilling or training might be necessary [46, 54]. Within this context, a firm’s top management is typically required to support the implementation plan [46]. By providing commitment and financial support, executives can act as a driving force behind the implementation process. Moreover, they can contribute by enabling effective knowledge sharing and facilitation between the different stakeholders within an organization [47].

4.3.3

Adoption Factors and Challenges Related to the Firm’s Environment

Firms rarely act as isolated players, but are rather embedded into a market environment with suppliers, partners, competitors, and customers. For this reason, additional adoption factors and challenges can be found outside the boundaries of a single organization. In general, adequate market support is a critical factor for AM implementation [47]. This includes for instance trading partner readiness, meaning that suppliers,

service providers, and vendors can provide the goods and services required for the AM implementation project. Here, especially post-processing capabilities of service providers can be highlighted. Depending on the respective application and utilized AM technology, a wide range of finishing steps might be necessary, including specialized processes such as hirtisation, hot isostatic pressing, or electroplating. In addition, the openness of customers toward AM products needs to be evaluated as well. By switching to AM, a product’s shape, material, surface quality, and finishing might be subject to change. Depending on the application field, customers may distrust or even reject such changes, requiring additional clarification or training [43]. Despite those issues, a firm’s environment can also act as initial trigger or facilitator for the AM implementation process. Organizations that find themselves in turbulent market conditions can choose to adopt AM in order to gain a competitive advantage over their competitors [46]. Governmental organs can facilitate this process by providing regulatory support, funding opportunities or training initiatives. The European Union (EU), for instance, has provided funding for AM related research and development from as early as the 1980s [3]. Alone between 2007 and 2019, more than €320M have been awarded [3]. In addition to EU-wide projects, numerous national and regional AM initiatives can be found in the most of the developed countries.

4.3.4

Implications of Implementation Challenges on the AM Adoption Process

As seen before, the implementation of AM comes with a wide range of challenges and hurdles. These barriers can be related to factors of technology, organization, and environment. The following subsection discusses the implications of those challenges on the AM adoption process. Unaware of the consequences and hurdles of AM adoption, firms often times choose an unsystematic and nonstrategic technology push approach for their first AM project. Here, organizations attempt to showcase AM’s design potentials in highly complex demonstrator parts [53]. As a result, the degree of technological innovation greatly outweighs the market-driven motivation for such applications. A viable business case is therefore often times missing. This poses a significant risk to long-term implementation success, as these applications may not adequately address actual customer needs. The high degree of complexity poses an additional challenge for industrialization. This is due to the fact that technological competences regarding AM are lacking at the beginning of the AM adoption process. Such implementation projects typically result in complex demonstrator parts, while serving no or only limited business value. The acquired learnings are therefore limited to the technical domain, since a validation on the market is lacking.

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In addition to the misleading approach of choosing overly complex parts for the first implementation project, another common pitfall is using AM as direct substitution for existing parts. In this scenario, firms attempt to manufacture given designs by means of AM. As the original parts are optimized for the respective traditional manufacturing process, the resulting AM components are often times more expensive and inferior in quality, while offering limited added value. This is mainly due to the higher cost structure of AM compared to conventional technologies. For this reason, the use of AM is in most cases only justified by providing additional benefits such as added functionality, reduction of weight or customization. For both scenarios, a failed AM implementation project can have major consequences for the future adoption of the technology in the target organisation. Based on underwhelming experiences, the initial AM implementation project is usually abandoned, often times resulting in a long term, negative perception of the technology’s potential within the firm. Future AM implementation efforts may be avoided with reference to the failed attempt as the technology had already shown to have no potential – regardless of the reasons for which the pilot project failed [33].

4.4

Case Studies of Successful AM Adoption in Industry

In the following section, the AM adoption process of two exemplary firms is presented to showcase how the aforementioned barriers of implementation can be addressed. The first case study is related to a SME within the field of consumer goods, which used laser-based powder bed fusion of polymers (PBF-LB/P) for the manufacturing of end-user products. The second case study considers the implementation of AM in a large, global technology corporation with focus on

Phase 1: Q4 2015 Non-critical accessories (single component) e.g. lens shades, caps

Phase 2: Q3 2016 Single customer request (structural assemblies) e.g. stiffening frame

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metal AM for technical components. Both firms have chosen a structured approach for the adoption of AM. By analyzing the implementation pathways of the two firms in retrospective, key strategies for the adoption of AM can be deducted.

4.4.1

Implementation of AM at a SME

ALPA Capaul & Weber Ltd. is a Swiss SME that operates in the field of high-end cameras for professional users. The firm’s main offerings are modular camera platforms that integrate various components such as lenses and digital backs from third party providers. The products are characterized by low product quantities and are targeted toward the premium segment for which high expectations regarding finishing and precision stand out. In the past, the firm mostly used high precision, subtractive manufacturing with external service providers to address customer needs. The high reliance on conventional manufacturing in combination with small product volumes posed a major challenge for the company. It inhibited the firm’s new product development (NPD) to pursue exploratory product concepts in new markets, to upgrade current products after market introduction and to offer tailored solutions for individual customers [9]. To address those challenges, the firm started to introduce AM back in 2015. Since then, the company continually increased the level of AM adoption through several implementation phases (see Fig. 4.2). In the following, a brief overview of the firm’s AM adoption history is given with focus on lessons learned at every phase.

Phase 1 In the first implementation phase, the firm started out with non-critical accessories such as covers and lens shades. These products are characterized by a limited degree of functional requirements, but a high demand for finishing and haptics. To

Phase 3: Q3 2017 Standard modules (high user interaction) e.g. battery holder

Phase 4: Q2 2018 Adaptable modules (multifunctional, customisable) e.g. cage with integrated cooling

Fig. 4.2 The firm introduced AM through a series of four implementation phases. (Adapted from Ref. [9]. Photos © ALPA Capaul & Weber Ltd., reprinted by permission)

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fully implement both products, the firm needed to acquire AM-related competences along the whole value chain. Within R&D, basics of Design for AM (DfAM) were introduced through educating engineers with focused trainings. By collaborating with an external AM supplier from the beginning, first experiences regarding material, manufacturing processes, and finishing were gained in a guided manner. On the sales side, the firm needed to establish customer acceptance for the AM parts as the materials, surfaces, and haptics differed substantially from conventional alternatives.

Phase 2 After successfully launching its first AM product, the firm translated the newly gained AM competences towards more demanding applications. For a single customer request, a stiffening frame for a photogrammetric camera was developed [55]. The product combined AM with various conventional parts and demanded much stricter functional requirements. To satisfy those, the firm needed to advance its competence in DfAM by expanding to structural AM assemblies and by including AM specific fastening features. The development and validation of such features required extensive functional prototyping, which in turn highlighted the need for a labelling convention for part tracking in operations. Furthermore, communication routines with the AM supplier were established to enable fast and responsive feedback loops between product design and manufacturing. Phase 3 This phase dealt with the development and introduction of the firm’s first videography system. For this product, the AM parts (camera cage & battery holder) represented central portions of the product system with a high degree of customer interaction and functional integration (including electronics, cabling, and fasteners). For the first time, the firm used an Agile development approach to address the uncertainties of the emerging target market. Within short sprints of 5–6 weeks, product increments were designed, built, and tested with lead customers. The vastly increased development pace required a high degree of parallelization in R&D. AM features were separately iterated and merged after successful testing. The resulting increase of prototyping frequency and quantity posed new pressure on the supply chain of AM prototypes and products. The firm therefore introduced automation into the ordering process in the form of a fully integrated order management system for AM parts. Remote feedback acquisition tools were used to feed lead user reviews to designers in R&D. Phase 4 Within phase 4, the firm’s videography system was substantially redesigned after a first market launch. The upgrade included a thermal management solution within the AM

D. Omidvarkarjan et al.

camera cage. Control electronics, interfaces like AM switches and special features such as noise and vibration suppression were integrated into the AM design. The range of employed AM features inspired the firm to use a feature database as a repository for recurring AM design building blocks [56]. Furthermore, individualization was introduced in the form of a customizable top handle. Due to sudden variation of product designs, new quality control procedures were needed. Furthermore, part sets were introduced to optimize the ordering of final product assemblies. On the sales side, the need for an adapted business model was identified as individualization and constantly evolving product designs showed to be incompatible to the prior existing business model.

4.4.2

Implementation of AM at a Large Technology Corporation

The second case study analyzes the implementation of AM at Siemens, a global technology corporation headquartered in Munich and Berlin, Germany. The company and its spin-offs are active in the digital transformation of various sectors, such as industry, infrastructure, mobility, the energy transition and healthcare systems. Regarding AM, Siemens acts as provider of AM industrialization, automation, and software products, while its spin-off Siemens Energy AG is a user and service provider of the technology. The following section provides an overview of selected implementation projects from Siemens and discusses driving factors of AM adoption for large corporations. Overall, Siemens has started to implement AM at the end of the 1990s within the context of corporate research activities. Based on these experiences, first application cases emerged at Siemens in the field of hearing aids, electronic casings, and energy systems [57]. For the latter, AM was initially used for rapid prototyping such as the functional testing of turbine components. Compared to conventional processes, AM enabled Siemens to shorten lead times, allowing for more cost-effective evaluations of new designs. Having acquired first experiences with AM, Siemens shifted to first applications outside of rapid prototyping [58]. Figure 4.3 illustrates selected implementation pathways of such AM applications at Siemens. The repair of burner tips using PBF-LB/M belonged to the earliest uses cases in that phase (first row in Fig. 4.3). These components are an integral part of gas turbines [59]. Due to excessive heat and combustion, the tip of the burner is typically subject to erosion. After a certain number of operating hours, the burner tip therefore needs to be repaired. To do so, the damaged tip is milled off in a first step [59]. Afterwards, conventional welding can be used to rebuild the front section of the part. Due to the complex shape of the component, the

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Technical effort / complexity of product is increasing 2015 Integration of lattice structures for in-process burner tip internals cooling

2017 AM-burner enables path to hydrogen combustion for major CO2 emission reduction

2012 Large integrated swirler (casted part) with internal fuel channels

2014 Adaption to AM design rules: Simulation & business case refinement

2017 Industrialized production process in service shop scope

2011 Water cooled burner tip: Component re-design with conformal cooling

2014 Re-design of other burner parts after successful AM part operation

2016

2020

2014

2015

2016

Business complexity / adaption is increasing

2007

2013 Re-design of 300 mm burner front (13 parts to 1 part)

Rapid burner repair (30 mm hybrid PBF-LB/M) 2008 Small swirler casted / welded copied

Demonstrator part: Polymer arm rest with customer specific switches

Internalization: Setup of own production capacities

“Combi burner”: optimized CFD for several media

Qualified processes and increasing AM spare part portfolio

Concept for hybrid AM: PBF-LB/M + WAAM 2019 First regulatory approval of highly-loaded and safety relevant AM part for trains

Fig. 4.3 Overview of selected AM implementation projects at Siemens. (Figure courtesy of Christoph Kiener; photos © Siemens, reprinted by permission)

Fig. 4.4 Conventional burner (a) and redesign for AM (b). (Photo © Siemens, reprinted by permission)

Fig. 4.5 Combustion swirlers redesigned for AM. (Photo © Siemens, reprinted by permission)

traditional process was time-consuming and costly. By switching to AM, Siemens was able to drastically speed up the rebuilding process, reducing the overall turnover time by 70% [59]. To do so, the leading Siemens AM facility at Finspång, Sweden, worked closely together with the AM machine supplier EOS [59]. Together with support from the AM original equipment manufacturer (OEM), Siemens modified existing PBF-LB/M machines (M280 Custom) to house the milled-off burner tips. Reassured by the successful implementation, Siemens engineers increased the technical complexity in the subsequent years by completely redesigning the burner for AM (see Fig. 4.4). The updated design includes lattice structures to improve part cooling and to stiffen the

structure while minimizing the weight of the component. In addition, the total part count is reduced from 13 individual components and 18 weld seams down to one single unit. A similar implementation pathway can also be found for other AM applications at Siemens, such as combustion swirlers (second row in Fig. 4.3 and Fig. 4.5). These are complex, formerly casted parts used for mixing fuel and air in combustion systems. This application was selected through a systematic part identification process, since its size, material and costs were highly compatible to AM. The swirlers were among the first industrial use cases of PBF-LB/ M at Siemens and acted as a catalyst to fully industrialize the PBF-LB/M business at the corporation, which led among

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STAR-CCM+

Velocity: Magnitude (m/s) 5.0000

4.0000

3.0000

2.0000

1.0000

0.00000 Z X Y

Fig. 4.6 Fluid simulation of the burner tip. (Photos © Siemens, reprinted by permission)

others to the acquisition of the AM service provider Material Solutions Ltd. The development of burners for thermochemical conversion represents a more design-driven phase of AM adoption at Siemens (third row in Fig. 4.3). The part is used to produce synthetic gas in a thermo-chemical process at temperatures above 1300
C with pressures between 30 and 80 bar [60, 61]. Due to the complex fluidics, conventional gasification burners consist of numerous components (almost 50 parts, among them some high-alloy items with long lead times), which need to be joined in a time-consuming and expensive welding process [62]. Furthermore, evaluations have shown that the conventional design was limited in regards to cooling capabilities. Starting in 2011, Siemens engineers therefore started to address those limitation by investigating the potential of AM for this particular application [60, 61]. In a first step (first box of third row), the outer ring of the burner tip was re-designed including thin-walled conformal cooling built with PBF-LB/M [63]. Based on the positive results (over 5000 operating hours at customer site), the team continued to utilize AM also for the second, inner ring of the assembly starting from 2014 (second box of third row).

AM’s potential for enhanced cooling and radical new fluid guidance made it clear that a complete redesign of the system was required [64]. Inspired by AM’s freedom of design and biomimicry, a fennel-shaped burner was finally developed in 2016. The design includes a complex system of internal channels and guiding vanes (depicted in Fig. 4.6). By using parameter optimization in combination with computational fluid dynamics, different variants of the system could be generated and evaluated in an automated workflow [62]. In a next step, Siemens is currently investigating the combination of multiple AM processes such as Wire Arc Additive Manufacturing (WAAM) with PBF-LB/M for this application (fourth box of third row). Thereby they react to recent improvements of WAAM. The goal is to exploit the strengths of the respective processes to further improve the costs and performance of the burner tip. In addition to the energy sector, further AM implementation projects were also conducted in the field of public transportation and mobility (trains, trams, subways), especially in the field of spare part services. Here, Siemens experienced additional business complexity due to the formal quality assurance required in the mobility sector. Other than in gas turbine applications where design integrity is granted

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according to Machinery Directive in a company-internal engineering approval process, railway systems additionally require regulatory conformance and approval depending on the area of application. To address this, first AM applications centered around lightly loaded interior equipment (e.g., customized driver armrest with switches as depicted in Fig. 4.3) and moved stepwise towards highly loaded and regulated parts. As spare part services are subject to constantly changing parts in small lot sizes, generic approaches of quality assurance were needed to ensure short lead times and high availability. When comparing the various implementation streams at Siemens, it can be seen that both the product and business complexity continuously increased with every adoption phase. With regards to the technical dimension (horizontal axis in Fig. 4.3), early iterations of the different parts showed only limited use of AM without major modifications of material, design, or process. With increasing levels of AM implementation, the scope and depth of AM utilization expanded (e.g., by completely redesigning products and manufacturing workflows for AM). A similar trend can be seen for the business complexity (vertical axis in Fig. 4.3). Later iterations of the different implementation projects increasingly addressed novel business opportunities enabled by AM, such as the individualization of products or by offering the acquired AM expertise as a service to other firms. As a large technology corporation, Siemens is able to cover a broad range of the AM value chain, effectively representing two different roles in the AM industry. Through Siemens AG, they are providing automation technology, software solutions, and consulting services for AM, while their spin-off Siemens Energy AG acts as AM end-user and service provider. In addition to the constant rise of product and business complexity, software has also become increasingly important to Siemens with progressing levels of AM implementation. The shift from prototyping, over repair to serial production would have not been possible without a strong foundation in software solutions. To design and manufacture AM components in the context of serial applications, a whole range of software tools are necessary, ranging from design, simulation to shop floor management (e.g., PLM, CAD, CAM, CAE, and digitalization software for AM end users). Through Siemens Digital Industries, the corporation is providing a digital thread over the entire AM process chain, enabling seamlessly integrated workflows for better efficiency and increased scalability. Throughout this adoption process, there has been a vivid exchange on a corporate level at Siemens. After the success of the early implementation projects, corporate-wide AM ideation challenges were initiated to foster the exchange of

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AM related competences and experiences. These were supported by the management from very early on, underlining the importance of executive sponsoring.

4.5

Key Strategies for the Focused Adoption of AM

As seen for the two case companies, the chance for a successful adoption of AM within a firm is influenced by various implementation strategies. The following section describes four key factors of such an adoption approach. This set of strategies is not meant to collectively exhaust all aspects of AM implementation – the motivation is rather to provide practical recommendations and general guidelines that can be used by firms interested in the adoption of AM. 1. To fully industrialize AM, firms need to acquire a wide range of AM related competences throughout the adoption process. This know-how is not restricted to technical areas, as seen for the first case company (depicted in Fig. 4.7). It typically includes aspects from all organizational functions, meaning R&D, operations, or marketing and sales. By using an iterative, trial-and-error adoption approach, the steep AM learning curve can be broken down into smaller, manageable portions [2, 4, 32]. Within the first case study for instance, the company started its AM adoption process with parts of very limited complexity, enabling it to quickly acquire the necessary expertise. After fully implementing the application from end to end, the firm moved to more complex cases. Such early demonstrators do not necessarily need to be part of final products but can also be internal applications such as jigs and fixtures. Using AM for the production of simple spare parts is also a common pilot project that enables firm to gather first experiences without requiring a wide range of knowhow. 2. Throughout this iterative process, successful market launches help to create a self-sustaining adoption environment by providing additional revenue streams. This is of high importance as the adoption of AM is typically a longterm, capital intensive process [47]. AM applications should therefore be primarily motivated by a valid customer need and convincing business case to increase the chance for a successful market launch [53]. Opposed to the aforementioned technology push from Sect. 4.3.4, such an approach can be characterized as market pull strategy. 3. Collaborations with external partners are of high importance within the context of AM adoption [2, 52, 53, 65]. They can be strategically employed to fill in competence gaps or lack of expert know-how, for instance, regarding

4

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Phase 2

Phase 3

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xx

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Database for AM features

Operations

Selection of AM supplier, material, processes, finishing

Labelling convention for part tracking

Automation of prototyping order process

Optimisation of supply chain (part sets)

Marketing & sales

Customer acceptance for AM products

Feed single customer request directly to R&D

Remote feedback acquisition

Adapted business model

Fig. 4.7 Overview of product complexity and acquired AM competences across the different implementation phases of the first case company

specific AM processes or materials. In addition, firms do not need to heavily invest into their own AM machinery and material by collaborating with manufacturing contractors. Other partners could include for instance academic institutions. Opposed to large corporations with internal research departments, SMEs are typically more required to engage in external collaborations [65]. The presented SME collaborated for instance with both contract manufacturers and academic institutions, enabling it to quickly bring in experts when required. Especially the interaction between the firm’s design engineers and machine operators from the production partner proved to be valuable to quickly review and optimize part designs for manufacturability. 4. The digital process chain plays an important role for the value creation with AM, as all AM processes draw upon digital 3D models to build physical parts. Ideally, such a digital thread spans the entire process from end-to-end: starting from modelling or scanning, over analysis and simulation to build planning and fabrication [35]. It is therefore suggested that firms invest into the digitization of their process chain to enable a seamless integration within and outside of the company’s boundaries. For instance, the company of the first case study connected and automated individual process steps such as part ordering, increasing the efficiency and throughput of the AM supply chain.

4.6

Role of Change Management for AM Adoption

As described in the previous sections, numerous barriers of both technical and organizational nature hinder AM adoption within a firm. Furthermore, AM implementation is characterized as learning process that requires openness and willingness to acquire new competences and skillsets. Existing products, structures and ways of doing are often times questioned to fully exploit the technology’s potential. It is therefore no surprise that employees may hold personal reservations against such fundamental transformations [33]. Thus, change management plays a significant role within the AM adoption process as it addresses those reluctances. These can be divided into a technical and personal dimension, as shown in Fig. 4.8 [33]. The horizontal axis considers how individuals assess AM’s technological potential for their organization, ranging from low to high potential. The vertical axis relates to personal reservations that individuals may hold. Depending on the respective role, individuals may not be affected, may personally benefit (positive impact) or even suffer drawbacks (negative impact) from the implementation of AM. The prescribed matrix provides an orientation on how existing reluctances can be addressed: For technological

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Fig. 4.8 Degrees of personal assessment regarding AM adoption. (Adapted from Klahn et al. [33])

67

Positive Sceptics 99.8 %

6 Ï

0

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316L / 1.4404 according DIN EN 10088-3

11 Ð

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10 Ï

d < 200 µm

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1 Ï

+ + + + + ++ ++ ++ + + + ++ + + + ++ + + + ++ + ++ + +++ ++ +

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No errors according DIN EN ISO 6520-1 No errors according DIN EN ISO 6520-1 No errors according DIN EN ISO 6520-1 No cracks according DIN EN ISO 6520-1

7%

Size of solid inclusions connectet to surface

General tolerances DIN ISO 2768 class H/K/L General tolerances DIN ISO 2768 class H/K/L General tolerances DIN ISO 2768 class H/K/L Leakage rate ≤ 0.001 mbar * l / s at 6 bar No errors according DIN EN ISO 6520-1 Cleanliness according ISO 18413

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+

+

Fig. 46.7 House of quality for the LPBF process

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Part and Process Qualification for Serial Production

Colum No. Direction for optimising

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met, each of which is obtained using the method of CTQ trees (Figs. 46.6 and 46.7). Subsequently, in step 6, the direction for changing or optimizing each CTQ is fixed based on the entered target values (Figs. 46.6 and 46.7). It can be defined whether the optimization should maximize or minimize the value of a one-sided CTQ or whether a specific target value is to be achieved. For example, a CTQ with a one-sided specification limit for the Laser Beam Melting (LBM) process is the size of the gas inclusions for which maintaining below an upper specification limit of d < 200 μm is required. If instead an attributive CTQ or a two-sided continuous CTQ with both, a lower and an upper limit is present, typically a target value or specific limits are to be met. An example of a two-sided CTQ for the considered LPBF process is the CTQ hardness, for which the tolerated range must be maintained within the specification limits of 200
H
230 HV. To evaluate the strength of the relationship between the customer requirements and the CTQ quality characteristics, step 7 states the relationships within the matrix (Figs. 46.6 and 46.7). A classification is made between strong (9), moderate (3), weak (1), and no (0) relationships. The relationship strength indicates how strongly the respective CTQ quality characteristic contributes to the fulfilment of a customer requirement. In the next step 8, the technical relevance for each individual CTQ is determined by linking the weighted customer requirements with the associated values in the relationship matrix (step 7) for each individual CTQ and thus prioritizing them. In the roof of the house of quality in step 9, the dependencies between individual quality characteristics are identified, taking into account the target values (step 5) and the direction of change (step 6), so that it becomes clear when quality characteristics influence or conflict with each other. In the laid out HOQ for the present LPBF process, the technical importance ranking highlights the top priority for improvement of the process for the CTQs relative density, size of gas inclusions, 0.2% yield stress, tensile strength, Young’s modulus, elongation at break and hardness with a priority of greater-than-or-equal to 5% each. This is also underlined by the positive to strongly positive correlations of these CTQs with other quality characteristics. This means that optimization of the abovementioned CTQs, according to the direction of change, positively influences the fulfilment of the technical target values and specifications of other CTQs. For this reason, in the further course, these CTQs will be focused on for short- and long-term improvement activities for the LPBF process (Table 46.3). At the end of the define phase, the result should be that the project topic has been precisely defined and the initial situation and the objectives are quantified. In addition, the savings potential should have been estimated and quantified, the Six Sigma project is sufficiently organized, and the roles are clear. The results and determined information of the define

C. Emmelmann and C. Daniel Table 46.3 CTQs for short- and long-term improvement activities for the LPBF process CTQ Relative density SG Size of gas inclusions d Young’s modulus E Tensile strength Rm 0.2% yield stress Rp0.2 Elongation at break A Hardness H

Unit [%] [μm] [GPa] [MPa] [MPa] [%] [HV]

Specification limits >99.8% 99.8% (cf. specification limit in Table 46.3), this results in a P/T ¼ 14.85%. Thus, with reference to the measurement scatter on the tolerance, the measurement system is still in the tolerated range for the measurement of the relative density, since 10% < 14.85% < 30%.

46.3.2 Gage R&R 46.3.3 Process Capability Analysis When performing analyses based on numbers, data, and facts, it is very important that these are also reliable. For this reason, analyses of measurement systems are performed. Since the scatter of the measuring system is added to the actual process scatter, it must be ensured that the scatter of the measuring system is significantly smaller than the scatter of the process [12, 13]. For the evaluation of measurement systems and measurement processes within the scope of Six Sigma projects and under series conditions, the gage repeatability and reproducibility study (Gage R&R) is wellestablished [19]. This tool examines the measurement system with regard to repeatability and reproducibility. The parameter %R&R (repeatability and reproducibility) indicates how well the component scatter can be determined and describes what percentage of the measured process scatter is caused by the measuring system alone. This provides information about how well the measured data can be used for the analysis [12].

After measurement systems have been analyzed, process capability is determined and quantified to describe the quality of a process and its result. The metrics of a process capability analysis express how safe and reliable a process is with regard to the specification limits. The characteristic values determined in this course allow to compare processes and their results with each other. Process capability analyses are also used outside the Six Sigma methodology. For example, customers often demand proof of process capability from their suppliers [12]. The process capability analysis for an LPBF process, exemplary presented below, was performed based on 24 build jobs manufactured over a 6-month period. During this period, six build jobs containing test specimens were taken as a control sample, thus determining the short-term process capability over the first build job and the long-term

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capability over all build jobs. The test specimens manufactured in each case enable the measurement of the specified CTQs for the LPBF process (see Table 46.3). In addition, corresponding potential influencing factors for the build jobs were registered in parallel. For manufacturing of the six build jobs, the system technology and setup shown in Table 46.4 was used. The samples taken from the process originate from a consistent configuration, i.e., they always contain the same test specimens in the same build job arrangement (Fig. 46.8). The test specimens are arranged in five groups on the build platform, with one group positioned in each quadrant of the build platform and one in the center of the platform, in order to be able to detect influences on the process result due to the part position on the build platform. The manufactured reference specimens are used to measure the CTQs. The CTQs 0.2% yield stress, tensile strength, Young’s modulus, and elongation at break are determined by tensile testing according to DIN EN ISO 6892-1 [23]. For this purpose, 25 round tensile specimens were utilized per build job. For

Table 46.4 System technology and setup for build jobs System parameter Machine type Laser source Max. build dimensions Manufacturing parameters Material Layer thickness Powder mean particle size Coating system Process gas

Value Concept Laser M2 2x YLR cw 400 W 250 mm  250 mm  280 mm OEM Standard AISI 316L Stainless Steel 45 μm 35 μm Rubber Argon

1

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Round tensile specimens

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z

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14

18

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24

22

Build platform (250 mm × 250 mm)

Fig. 46.8 Build job arrangement for test specimens

Gas flow

all test specimens, the vertical build direction was fixed, since this represents the worst case for the direction of loads in the application case. The round tensile specimens are machined by turning to the required dimensions according to DIN 50125-B [24]. Furthermore, to measure the CTQs relative density and hardness, 30 cubes were manufactured per build job. The cubes are each built up to 3 cubes on top of each other in the buildup direction with 20 mm distance in between (Fig. 46.8). The cubes have an edge length of 10 mm. To determine the CTQ relative density, a micrograph is taken for each cube. In addition, the CTQ hardness was determined via Vickers hardness testing according to DIN EN ISO 6507-1 [25]. The hardness tests were performed with a test force of F ¼ 98.07 N at an exposure time of t ¼ 10–15 s on the ground surfaces of the cubes. With the basis of measurement data collected in this way, process capability indicators such as Cp and Cpk as well as DPMO, PPM, and first-pass yield can be calculated using statistical software tools, here Minitab 19, and converted into a sigma level with the aid of tables [12, 19]. The sigma level, in particular, is an indicator that describes the process quality and is therefore used in the following to characterize the LPBF process. The sigma level expresses how many standard deviations are between the mean value of the process results and the upper or lower specification limit [12]. To calculate a process capability, a distribution model is always used, since samples can never correspond exactly to the entirety of a process but always stand for it as representative [12]. It is important to check whether the distribution applied fits the data sufficiently well. The model of the normal distribution used in the present case is tested in each case by Anderson Darling test and is transformed if necessary [12, 13, 19]. In this way, the short-term sigma level Zσ is determined for the first build job and, beyond that, the long-term sigma level ZLT for each CTQ is determined over all build jobs (Table 46.5). The difference between the short-term and long-term sigma levels, the sigma shift ΔZ, is a measure of the change in the process over time with respect to the size and location of its scattering range relative to the specification limits and thus represents a parameter for process stability [12, 19]. With regard to the expectation for the process capability of the short-time sigma level, only scattering that is inherent to the process is expected for the first build job (within-subgroup variation). Therefore, for example, aging effects of the powder do not come into account here, since only new powder was used for the first build job. In contrast, for the long-term process capability also, between-subgroup variation is expected. The results of the process capability analysis for the LPBF process investigated are shown in Table 46.5. The analysis shows a short-term process capability of Zσ > 4.5 σ for the CTQs relative density, 0.2% yield stress, and tensile strength. However, the process shows a high sigma shift of up to ΔZ ¼ 4.4 σ for these CTQs. This indicates a shift of the

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Table 46.5 Process capability analysis for the LPBF process CTQ Relative density SG Size of gas inclusions d Young’s modulus E Tensile strength Rm 0.2% yield stress Rp0.2 Elongation at break A Hardness H

Sigma shift ΔZ 3.1 σ 0.5 σ 0.2 σ 3.1 σ 4.4 σ 0.7 σ 0.6 σ

Long-term sigma level ZLT 1.8 σ 2.4 σ 0.6 σ 4.1 σ 5.4 σ 1.1 σ 3.8 σ

Short-term sigma level Zσ 4.9 σ 2.9 σ 0.8 σ 7.2 σ 9.8 σ 0.4 σ 4.4 σ

46 Fig. 46.9 Short-term sigma levels and sigma shift of the LPBF process

5 4 1

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Good Very good (4.5 s) (6 s)

Short-term sigma level Zs a) Process out of tolerance / improve process parameters / check suitability of input variables / improve monitoring of input variables b) Improve process parameters / check suitability of input variables / improve monitoring of input variables c) Improve process parameters / check suitability of input variables d) Improve monitoring of input variables e) Target for process

mean and an increase of the scattering range over time and thus an instability of the process with respect to these features. The CTQ hardness shows a long-term process capability of ZLT ¼ 3.8 σ and can be regarded as stable due to a low sigma shift. The remaining CTQs size of gas inclusions, Young’s modulus, and elongation at break show long-term process capabilities of ZLT < 1 σ and are thus not capable and strongly in need of optimization. Especially the CTQ elongation at break shows a negative sigma level, which means that the LPBF process is not capable regarding this CTQ and is even outside the range tolerated by the customer. The described initial situation highlights the potential for optimization of the LPBF process and its process capabilities regarding the CTQs. Consequently, different measures can be derived for the improvement of the LBPF process with

regards to the respective CTQ. A high shift ΔZ, above the usual moderate shift of ΔZ ¼ 1.5 σ [12, 19], indicates instability and that the control of the process and input variables needs to be improved. On the other hand, a low short-term sigma level ZLT indicates that control variables of the process need to be optimized and the general suitability of input variables such as the properties of the powder need to be investigated and modified if necessary. The combination of a high short-term sigma level ZLT and a low shift ΔZ represents the target zone for the CTQs. At a short-term sigma level Zσ ¼ 6 σ with a shift of ΔZ
1.5 σ, which corresponds to a long-term sigma level of ZLT  4.5 σ, processes are commonly considered best in class [26]. Figure 46.9 displays the short-term sigma levels and sigma shift of the present LPBF process.

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As a result, at the end of the measure phase, the most important output metrics have been identified and quantified. In addition, measurement systems have been reviewed and improved where necessary, thus ensuring data reliability. First significant analysis results are available for the initial situation of the LPBF process, so that further steps can be planned and implemented in the following phases for the most important inputs.

46.4

Analyze Phase

After the process capability has been determined in the measure phase with regard to the specification limits of selected CTQs and thus the initial situation of the LPBF process to be improved has been described, the task in the analyze phase is to identify the causes that are responsible for the deviations in the process. In order to be able to improve process capability in this way, it is necessary to uncover relationships between potential influencing factors and process results. Typically used tools of the analyze phase are, depending on the use case, analysis of variance (ANOVA), hypothesis testing, correlation analysis, cross-correlation analysis, or regression. Also methods of design of experiments (DoE) are used by means of active data collection [13, 19]. For the generation of DoEs, different types of experimental designs are existent, such as full and partial factorial experimental designs or Taguchi designs [19]. Especially for specific process development in AM, DoE methods have already been applied in numerous cases [11, 27, 28]. Preliminary to the statistical analysis, the 5M method (here machine, method, medium, material, and man) [29] is used for the investigated LPBF process to analyze which root-causes could be possible sources of errors and scatter for the process and thus cause an impact on the CTQs. Using this process-oriented analysis, causes of influence on the CTQs of the LBPF process under investigation are systematically identified. In the following, the abovementioned potential influencing factors on the LPBF process (cf. Sect. 46.3) are analyzed with regard to their effect on the CTQs. For the CTQs relative density, size of gas inclusions, 0.2% yield stress, and elongation at break, the effect of the potential influencing factors ambient temperature, humidity, and machine downtime between process starts are investigated by means of an ANOVA. In the analysis, it is important to take into account that statistical tests can prove that there is a significant effect for an influencing factor in relation to the measured values of a CTQ. However, statistical tests cannot detect the cause of this effect. Furthermore, if no significant effect is found, this does not mean that there is none present but only that no influence can be proved with the available data [12].

46.4.1 5M Method In preparation to the statistical analysis, a process-oriented analysis can be conducted to identify further possible influencing factors as well as causes for errors and deviation of the quality characteristics from their specifications. The process analysis thus provides a basis for the in-depth analysis of further primary and secondary causes in the causeeffect context. For this purpose, the LPBF process is divided into its individual process steps, and for each step, influencing factors are systematically collected using the 5M method, so that they can be transparently listed in a cause-effect diagram (Fig. 46.10). 5M stands for the root causes machine, method, medium, material, and man. Furthermore, the influencing factors can be categorized into three groups: control variables, disturbance variables, and constants. This allows prioritizing influencing variables for further procedure. In an industrial environment, criteria for the prioritization can be seen in technological and economic aspects, taking into account how much effort is required to influence disturbance variables in particular [12, 13]. For the LPBF process under investigation, influencing variables were collected comprehensively, based on analysis of the detailed process steps [10]. In Fig. 46.10, influencing variables are listed in extracts, which can be assigned to the category of disturbance variables. Prioritization can be used to determine in which order and with which measures the influences and their causes are to be addressed in the improve phase. In this context, the process-oriented analysis contains a large number of disturbance variables for the LPBF process in the medium (environment). These disturbance variables, such as humidity or oxygen, are present in different process steps and at different areas in the LPBF process. They act both indirectly on the inputs, such as the powder and the inert gas, and directly in the process chamber atmosphere on the melt pool. In addition, these disturbance variables are currently only insufficiently monitored, so that they have an uncontrolled effect on the process. The control and monitoring of disturbance variables from the medium (environment) thus represents a great potential for reducing scatter of the CTQs over time.

46.4.2 Analysis of Variance (ANOVA) In the ANOVA, it can be tested whether the mean values of independent groups differ in a statistically significant way from each other. The statistical basis of the ANOVA is the F-test. In this, the ratio of two variances is used to determine a value from the F-distribution, which in turn provides the pvalue. The p-value represents the probability that a difference between categories occurs only by chance [12, 13, 19]. If the p-value is smaller than the previously set significance limit (typically 5%), the relationship between input and output

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Machine • Planarity build platform

791

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• Competency and experience

• Planarity powder bed

• Machine downtime • Leak tightness build chamber

• Cleanliness build chamber

• Quality consciousness • Condition and constitution

Environmental condition each at the LPBF machine and in process chamber • Cleanliness build chamber • Humidity • Chemical composition of gas atmosphere • Vibrations Material

Condition of powder • Chemical composition • Humidity • Distribution of particle size Process gas • Chemical composition • Humidity Medium

Fig. 46.10 Disturbance variables for the LPBF process

variables is statistically significant. If the p-value is above the set limit, no correlation may be assumed [12, 13, 19]. As described in the measure phase, the acquired measured values of the LPBF process include the CTQs for each production run as well as the associated potential influencing factors, of which the most significant ones are exemplarily analyzed in the following. With regard to the influencing factor ambient temperature at the production site during the production run, two groups can be distinguished, one with temperatures T < 25  C and one with T > 25  C. Their influence on the CTQs is shown in Fig. 46.11. For the CTQs size of gas inclusions and 0.2% yield stress, there can be observed a statistically significant increase of the values with increase of the ambient temperature, while the relative density decreases with statistical significance. For the elongation at break, on the other hand, no significance can be observed. The effects on the CTQs due to changes in the ambient temperature at the production site can be caused on the one hand by an influence on system components, such as deviations in the beam path of the optical components. On the other hand, the water absorption capacity of the air increases at higher temperatures, which can affect powder properties such as flowability [5, 30, 31]. In this context, Fig. 46.12 additionally shows the influence on the CTQs of the humidity in the production environment.

In analogy to the observed trends for ambient temperature, at higher humidity, larger values occur for the CTQs size of gas inclusions and 0.2% yield stress, and lower values occur for relative density. A statistically significant difference between the lowest and highest values of humidity can also be confirmed for these CTQs. For the CTQ elongation at break, no clear trend can be recognized for the measured values and no significant difference is present. A powder analysis underlines the observed interrelationships. Parameters such as flowability, mean particle size, and the oxygen as well as hydrogen content in the powder are measured for varied humidity. The resulting p-values are below 5%, which means that these powder characteristics show a significant correlation with the humidity. An increase in the median particle size and a decrease in flowability at higher humidity can be explained by the agglomeration of powder particles due to the absorption of humidity [5, 31]. For influences on the powder characteristics, also other studies confirm that these significantly affect part properties and thus the CTQs considered here [5, 31]. In summary, by means of the described graphical and statistical analysis methods, significant effects of the selected influencing factors on the CTQs can be identified. At the same time, it has to be kept in mind that the factors for which corresponding impacts in the CTQs were identified

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T < 25 °C

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T > 25 °C

Temperature T (°C)

Temperature T (°C)

Fig. 46.11 ANOVA for influencing factor temperature

do not necessarily have to be the cause of these differences. However, the procedure supports the identification of possible causes and helps to focus on relevant variables such as humidity in the present case. On the basis of the production runs evaluated, the recommendation can be made for the exemplary LPBF process under investigation to exclude the effect of humidity at all points of the process. Therefore, technical and organizational measures must be taken to prevent the effect of humidity on the powder especially in the process steps “provide material” and “manufacture components” (see Fig. 46.3). One possible measure is to implement air conditioning in the production environment of the machine, as in this way the ambient temperature and also the humidity at the machine is controlled and monitored. Furthermore, ongoing and enhanced monitoring and data collection for the LPBF process is recommended. In this way, the data basis for the DMAIC cycle is continuously increased and the significance of comprehensive statistical analysis methods is increased, which can contribute to the discovery of further cause-effect relationships. At the end of the analysis phase, the relationships between input and output variables should have been analyzed.

Critical inputs and thus causes of errors have been identified and the inputs for the subsequent improve phase are clear.

46.5

Improve Phase

In the improve phase, the measures to be taken are described and implemented. Based on the analysis results of the previous phases, structured measures are derived, the implementation is planned and systematically carried out, and at the end their effectiveness is verified [12, 13]. In doing so, tools such as the solution selection matrix and to-do lists or creativity methods such as the 6-3-5 method, brainstorming, etc., can be used as support for structuring [12, 13]. With regard to a strategic and systematic approach, it is advisable to first reduce the scatter of the process before shifting the process position in the second step [12, 13]. For this purpose, disturbance variables relevant to the inputs of the process are converted into suitable constants, since disturbance variables can cause both a high within-subgroup variation and a high betweensubgroup variation. Consequently, these variables have a negative effect on the stability of the process and lead to

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j < 45 %

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j < 45 %

j > 45 %

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Fig. 46.12 ANOVA for influencing factor humidity

a high long-term sigma shift. Therefore, the first goal must be to reduce the scatter in order to ensure a stable and predictable process result. Disturbance variables are converted into constants, as far as this is technologically and economically feasible. Consequently, associated specifications must be defined for them and their fulfilment must be monitored permanently. Disturbance variables that cannot be converted into constants but can at least be monitored should also be defined as critical process variables with associated limit values. For the investigated LPBF process, the following strategies and measures are derived in the improve phase to stabilize the process (ZLT > 4.5 σ) and to increase the process capability (Zσ > 6 σ). Respective measures are to be seen against the background of the disturbance variables identified in the analyze phase. With regard to material disturbance variables, for example, an inspection of incoming powder should be demanded by means of an acceptance test certificate 3.1 according to DIN EN 10204 [32]. Furthermore, for the disturbance variables from the group “medium,” the production site should be equipped with a suitable industrial air conditioning system and thus the temperature and humidity can be adjusted and monitored. This has an effect in particular on the exposure of the powder to humidity and

ensures that its specified properties are maintained. For further disturbance, variables from the group “machine” measures must be defined, such as specifying and fixing the duration for preheating and flushing the build chamber. Also, standard operating procedures including work instructions, checklists, limiting samples, etc., must be defined in order to control human influences accordingly. In the case of disturbance variables for which, from a technical or economical perspective, no measure can be implemented to control them and thus convert them into a defined constant, it should be attempted to at least implement a monitoring. Thus, it is possible to intervene in case of strong temporal changes of these variables. An example for this can be seen in the machine downtime. As a result of machine downtime, influences due to oxidation processes in the powder can be brought into the process, which must be avoided. In consequence, it could be considered to transfer the machine downtime into a constant. At the same time, however, variations in machine downtime must be taken into account depending on utilization of production capacity in the serial process and for organizational reasons such as maintenance. Therefore, limits must also be defined for in machine downtime and compliance with these limits must be ensured. As a result of the implementation of these measures,

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a stabilization of the process and thus a reduction of the sigma shift can be expected. After stabilizing the process, the process location can be shifted in the case of a one-sided specification limit or centered in the case of a two-sided limit. This can be done by adjusting control variables accordingly. In this context, the relationship between suitable input and output variables should be known from the analyze phase. If necessary, this knowledge can be systematically extended by statistical design of experiments (DoE) [13, 19]. For AM, this is also already in the scope of numerous scientific studies [11, 27, 28].

46.6

Control Phase

The last step in the DMAIC procedure is the control phase, the purpose of which is to systematically and sustainably ensure the success of the project after the improvement has been achieved [12, 13]. In this way, monitoring of the improved process flow and production equipment takes place to prevent the process from drifting or scattering. For this purpose, it is necessary to install process monitoring including a control plan for the serial production process. The control plan OCAP (out-of-control-action-plan) defines all actions to be taken in case of occurrence of deviations in the control chart [12, 13, 19]. By implementing appropriate tools, it is ensured that the correct reaction can be taken when the control limits documented on the control charts are exceeded. Control charts include time series diagrams that are enriched with important additional process information. The systematic procedure ensures that, on the basis of the knowledge gained in the measure phase, specific situations can be quickly identified that lead to deviation from the desired process state. In the next step, the cause for the deviation is determined, supported by the knowledge from the analyze phase, and improvement measures are implemented. The measures are then verified and monitored according to the improve phase. In this way, the measures to be taken in the event of deviations are precisely defined. Consequently, process errors and production downtimes can be prevented and the handover of processes between different project supervisors and process owners is also simplified.

46.7

Conclusion

In this chapter, it was demonstrated how the DMAIC cycle of the Six Sigma methodology can be applied for the LPBF process in order to continuously improve it and to build up a

comprehensive process understanding for serial production. The Six Sigma approach provides insight into the initial situation of the LPBF process with regard to critical quality characteristics, identifies possible influences and causes of errors, and derives measures to stabilize the process and increase process capability sustainably. With the knowledge gained about influences and causes of errors, measures can be implemented to eliminate faulty parts. The first step is to reduce the scatter of the LPBF process, especially in between build jobs. Identified disturbance variables must be converted into constants and be monitored. If the LPBF process has been stabilized with respect to quality characteristics, but process capability is not yet at Six Sigma level, the focus should then be on adjusting control variables to shift or center the process position relative to specification limits. For use in one’s own serial production, it is also recommended to continuously expand the database using the DMAIC methodology and to analyze further relevant measurement systems as well as high-priority quality characteristics (CTQs). For these CTQs, process capability analyses should be carried out and the sigma levels should be examined. In addition, data should be collected for as many of the influencing factors as technically and economically possible in order to be able to uncover further cause-effect relationships using statistical methods. This will enable the derivation of improvement measures for continuous process improvement. In this way, a knowledge base for further component parameters, such as fatigue strength, can also be built up. Fatigue is particularly influenced by factors such as the relative density and the distribution and shape of internal defects such as pores and cracks [6]. In the railway sector, among others, fatigue strength is a decisive factor for being able to meet the future demand for AM components and enabling them to be used also increasingly in safety-relevant areas [2]. In this context, with regard to a qualification of safety-relevant components, a basis for the cyclic characterization of components made by AM has to be created and dynamic material parameters need to be determined in addition to static ones for respective application cases. Also in this environment, methodology like Six Sigma and DMAIC can provide qualification routines, which can be required for the certification of AM production sites by third parties such as certifying bodies (e.g., TÜV Süd). In doing so, the site can prove that it implements the requirements and guidelines of regulations, which ensures high and reproducible quality for AM of components. This, in conjunction with the ongoing establishment of norms and standards for AM, will contribute to the further industrialization of LPBF and AM.

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References 1. Munsch, M., Schmidt-Lehr, M., Wycisk, E.: AMPOWER report 2021. Hamburg. (2021) 2. Kunkel, M.: Approval of Safety-Relevant Components for ShortDistance Rail Traffic. Mobility goes Additive e.V, Berlin (2020) 3. Tapia, G., Khairallah, S., Matthews, M., King, W.E., Elwany, A.: Gaussian process-based surrogate modeling framework for process planning in laser powder-bed fusion additive manufacturing of 316L stainless steel. Int. J. Adv. Manuf. Technol. 94(9–12), 3591–3603 (2018) 4. Kleszczynski, S., zur Jacobsmühlen, J., Reinarz, B., Sehrt, J.T., Witt, G., Merhof, D.: Improving process stability of laser beam melting systems. In: Fraunhofer Direct Digital Manufacturing Conference (DDMC) 2014 (2014) 5. Seyda, V., Herzog, D., Emmelmann, C.: Relationship between powder characteristics and part properties in laser beam melting of Ti–6Al–4V, and implications on quality. J. Laser Appl. 29(2), 022311 (2017) 6. Stern, F., Tenkamp, J., Walther, F.: Non-destructive characterization of process-induced defects and their effect on the fatigue behavior of austenitic steel 316L made by laser-powder bed fusion. Prog. Addit. Manuf. 5(3), 287 (2020) 7. Blinn, B., Klein, M., Gläßner, C., Smaga, M., Aurich, J., Beck, T.: An investigation of the microstructure and fatigue behavior of additively manufactured AISI 316L stainless steel with regard to the influence of heat treatment. Metals. 8(4), 220 (2018) 8. Wu, A.S., Brown, D.W., Kumar, M., Gallegos, G.F., King, W.E.: An experimental investigation into additive manufacturing-induced residual stresses in 316L stainless steel. Metall. Mater. Trans. A. 45(13), 6260 (2014) 9. Wohlers, T., Campbell, R.I., Diegel, O., Huff, R., Kowen, J.: Wohlers Report 2020. 3D Printing and Additive Manufacturing State of the Industry. Wohlers Associates, Fort Collins (2020) 10. DIN SPEC 17071: Additive Manufacturing - Requirements for Quality-Assured Processes at Additive Manufacturing Centres. Beuth Verlag GmbH, Berlin (2019) 11. Van Elsen, M.: Complexity of Selective Laser Melting: a New Optimisation Approach. Katholieke Universiteit Leuven, Heverlee (2007) 12. Melzer, A.: Six Sigma - Kompakt und praxisnah. Springer Fachmedien Wiesbaden, Wiesbaden (2015) 13. John, A., Lunau, S., Meran, R., Roenpage, O., Staudter, C. (eds.): Six Sigma+Lean Toolset. Springer Berlin Heidelberg, Berlin, Heidelberg (2009) 14. Mahesh, M., Wong, Y.S., Fuh, J., Loh, H.T.: A six-sigma approach for benchmarking of RP&M processes. Int. J. Adv. Manuf. Technol. 31(3–4), 374–387 (2007) 15. Chen, J.C., Gabriel, V.S.: Revolution of 3D printing technology and application of Six Sigma methodologies to optimize the output quality characteristics. In: 2016 IEEE International Conference on Industrial Technology (ICIT), Taipei, Taiwan (2016)

795 16. VDI 3405: Additive Manufacturing Processes, Rapid Manufacturing - Basics, Definitions, Processes. Beuth Verlag GmbH, Berlin (2014) 17. VDI 3405-2: Additive Manufacturing Processes, Rapid Manufacturing - Beam Melting of Metallic Parts - Qualification, Quality Assurance and Post Processing. Beuth Verlag GmbH, Berlin (2013) 18. Deutsche Bahn AG: VTZ31 functional performance specification for the procurement of additive manufactured components and corresponding services, Frankfurt am Main (2018) 19. Allen, T.T.: Introduction to Engineering Statistics and Lean Six Sigma. Springer London, London (2019) 20. DIN EN ISO 6520-1: Welding and Allied Processes - Classification of Geometric Imperfections in Metallic Materials - Part 1: Fusion Welding (ISO 6520-1:2007). Beuth Verlag GmbH, Berlin (2007) 21. DIN 65123: Aerospace Series - Methods for Inspection of Metallic Components, Produced with Additive Powderbed Fusion Processes (DIN 65123:2017). Beuth Verlag GmbH, Berlin (2017) 22. Uhlmann, E., Pontes, R.P., Bergmann, A.: High level process map for selective laser melting/high level process map for selective laser melting. In: Kniffka, W., Eichmann, M., Witt, G. (eds.) Rapid. Tech – International Trade Show & Conference for Additive Manufacturing. Carl Hanser Verlag GmbH & Co. KG, München (2016) 23. DIN EN ISO 6892-1: Metallic Materials - Tensile Testing - Part 1: Method of Test at Room Temperature (ISO 6892-1:2016). Beuth Verlag GmbH, Berlin (2017) 24. DIN 50125-B: Testing of Metallic Materials - Tensile Test Pieces (DIN 50125:2016). Beuth Verlag GmbH, Berlin (2016) 25. DIN EN ISO 6507-1: Metallic Materials - Vickers Hardness Test Part 1: Test Method (ISO 6507-1:2018). Beuth Verlag GmbH, Berlin (2018) 26. Töpfer, A. (ed.): Six Sigma - Konzeption und Erfolgsbeispiele für praktizierte Null-Fehler-Qualität. Konzeption und Erfolgsbeispiele für praktizierte Null-Fehler-Qualität, 4th edn. Springer-Verlag Berlin Heidelberg, Berlin, Heidelberg (2007) 27. Del Re, F., Contaldi, V., Astarita, A., Palumbo, B., Squillace, A., Corrado, P., Di Petta, P.: Statistical approach for assessing the effect of powder reuse on the final quality of AlSi10Mg parts produced by laser powder bed fusion additive manufacturing. Int. J. Adv. Manuf. Technol. 97(5–8), 2231 (2018) 28. Aboutaleb, A.M., Tschopp, M.A., Rao, P.K., Bian, L.: Multiobjective accelerated process optimization of part geometric accuracy in additive manufacturing. J. Manuf. Sci. Eng. 139(10) (2017) 29. Liliana, L.: A new model of Ishikawa diagram for quality assessment. IOP Conf. Ser. Mater. Sci. Eng. 161, 012099 (2016) 30. Cordova, L., Campos, M., Tiedo, T.: Assessment of moisture content and its influence on laser beam melting feedstock. In: Euro PM2017 Congress & Exhibition, 2017 (2017) 31. Vock, S., Klöden, B., Kirchner, A., Weißgärber, T., Kieback, B.: Powders for powder bed fusion. A review. Prog. Addit. Manuf. 4(4), 383 (2019) 32. DIN EN 10204: Metallic Products - Types of Inspection Documents. Beuth Verlag GmbH, Berlin (2005)

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Prof. Dr.-Ing. Claus Emmelmann studied mechanical engineering at the University of Hannover, specializing in production technology. He then developed the Laser Zentrum Hannover on behalf of his doctoral supervisor Prof. Tönshoff and received his PhD in 1992 on the subject of “Cutting ceramics with laser radiation.” He was subsequently entrusted with business unit responsibility for the then new solid-state lasers at ROFIN-SINAR. After 10 years of successful development of this area, he was appointed as a professor at the Technical University of Hamburg. Author of more than 500 national and international publications, Professor Emmelmann founded the LZN Laser Zentrum Nord GmbH as a spin-off from the Hamburg University of Technology in 2009, serving as its CEO. From January 2018 until June 2020, he was also the Director of the Fraunhofer Research Institution for Additive Manufacturing Technologies IAPT. Today, he passes on his experience to students at the Technical University of Hamburg and is involved in national and international research and development as well as consulting projects for the transfer of knowledge and technology from photonic research to industrial laser applications.

C. Emmelmann and C. Daniel

Dr.-Ing. Christian Daniel completed a vocational apprenticeship as a Toolmaker at LEGO Werkzeugbau GmbH. Following his studies of Mechanical Engineering at the Technical University of Darmstadt, he engaged in the competence field of Laser Ablation and Additive Manufacturing (AM) at the Institute of Laser and System Technologies (iLAS), Technical University of Hamburg, and worked as head of department Mechanical Engineering and Toolmaking at LZN Laser Zentrum Nord GmbH. After completing his PhD thesis, he was Chief Engineer at the Institute of Technology and Education, University of Bremen. Since 2019, he has been a Senior Project Manager at Bionic Production GmbH, a subsidiary of Hamburger Hafen und Logistik AG (HHLA), where he is working in the fields of potential analysis for AM, AM engineering as well as qualification and approval for components from AM.

Quality Control for Additive Manufacturing

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Yahya Al-Meslemi, Kevin Ferreira, Charyar Mehdi-Souzani, Anne-Franc¸oise Obaton, Hichem Nouira, and Nabil Anwer

Contents 47.1

Introduction and Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 797

47.2

Categorization of Defects in Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 798 Geometrical Defects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 800 Internal, Mechanical, and Feedstock-Related Defects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 800

47.2.1 47.2.2 47.3 47.3.1 47.3.2 47.3.3 47.4 47.4.1 47.4.2 47.5 47.5.1 47.5.2 47.5.3 47.6

Defects Detection and Inspection Techniques for Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . End Quality Inspection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Measurement and Characterization Systems . . . . . . Test Artefacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Machine Learning for Quality Control in Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 809 Machine Learning for Quality Control Applications: In-Situ Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 810 Machine Learning for Quality Control Applications: Process Optimization and Defects Prediction . . . . . . . . . . . . 810 Key Characteristic for Additive Manufacturing . . . . . . Key Characteristics and Quality Control . . . . . . . . . . . . . . . . . Key Characteristics: Literature Review . . . . . . . . . . . . . . . . . . Key Characteristics for AM: Application Case in Porosity Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 813

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 813

Abstract

Additive Manufacturing (AM) has experienced important changes in the last years in terms of impact on product Y. Al-Meslemi · K. Ferreira · N. Anwer (*) LURPA, ENS Paris-Saclay, Université Paris Saclay, Gif-sur-Yvette, France e-mail: [email protected] C. Mehdi-Souzani LURPA, ENS Paris-Saclay, Université Paris Saclay, Université Sorbonne Paris Nord, Gif-sur-Yvette, France A.-F. Obaton · H. Nouira Laboratoire National de Métrologie et d’Essais (LNE-CNAM), Paris, France

design and manufacturing. Quality Control (QC) remains the main barrier for broader adoption of AM. Recent roadmaps and industrial practices attest to the need to address the lack of process repeatability and high failure rates. The state of research in literature and in industrial practices reveal that new product definition, in-process monitoring, smart networked sensing, predictive modeling, learning from data (simulation and measurement), and metrological assessment are reported to reduce these barriers. This chapter discusses AM defects’ categorization, geometrical and surface measurement, AM artifacts and metrological assessment, specification/verification-related standards, and lastly, it illustrates the current challenges, prospects, and trends in QC for AM from the perspective of data analytics and machine learning. Keywords

Quality control (QC) · Defects · Porosity · Metrology · Geometrical measurement · Surface measurement · X-ray Computed tomography (XCT) · Test artefacts (TA) · Machine Learning (ML) · Key characteristics (KCs)

47.1

Introduction and Context

The achievement of the vision of smart manufacturing requires the development of several key technologies, including advanced manufacturing methods such as Additive Manufacturing (AM). In AM, layers are joint together, one upon another, using one of four joining mechanisms: binding agent, polymerization, material extrusion, and thermal fusion. For the rest of this chapter, we will focus on thermal fusion-based AM, namely Powder Bed Fusion (PBF), which is illustrated in Fig. 47.1. PBF employs an energy source, such as laser projection or electron beam, to melt metallic powder forming successive solidified layers. PBF is essential

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_47

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Fig. 47.1 Powder bed fusion process [1]

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for testing new smart materials, configuring new processes, and examining new design methodologies [1]. For this reason, the industrial sector is racing to increase the applicability of PBF from simple concept and functional prototyping to accurate direct manufacturing and tooling. To achieve this, multiple research efforts are constructing roadmaps and guidelines to tackle several challenges such as terminology standardization and process certification, process traceability, modeling/simulation, in situ monitoring, nondestructive evaluation, material availability and recyclability [2]. One of these challenges is related to Quality Control (QC). Any manufacturers that can produce high end-quality parts will gain a competitive advantage compared to other manufacturers who suffer from end quality-related inconsistencies. No two manufactured parts are the same, and this is due to the existence of numerous build-to-build variabilities, and the sum of all these variabilities constitute the difference in end quality between any two AM parts. These variabilities can be the result of any number of internal/external factors such as material deterioration and non-uniform layer deposition, improper preparation of the machine, equipment miscalibration and measurement, and the misidentification of process parameters. The effects of these variabilities can be observed in geometrical inaccuracies, inappropriate and inhomogeneous layering, defective internal structure, etc. [3]. Hence the need to apply a systematic approach for QC of AM parts. QC is indispensable for counteracting high variabilities. This requires identifying their effect on the process/product, distinguishing the different sources of these variabilities, selecting the proper measurement methods, and devising the optimal approach to control them. This chapter is divided into multiple sections: Sect. 47.2 illustrates several types of defects that can hinder the level of end quality of

Laser scanning direction

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PBF-manufactured parts; Sect. 47.3 describes the utilization of multiple measurement techniques to evaluate these defects; Sect. 47.4 illustrates the importance of applying machine learning and data analysis in QC; Sect. 47.5 introduces the concept of “Key Characteristics” in the context of AM as a mean to enhance QC process.

47.2

Categorization of Defects in Additive Manufacturing

A “defect” refers to any anomaly that can hinder end quality of AM parts. Figure 47.2 illustrates different types of these defects. They range from fractured surfaces, porous internal structure, weak resistance to loads, dimensional inconsistencies, etc. Here, the end quality is evaluated through three aspects: mechanical performance; dimensional accuracy; and surface texture. In the case of PBF, the formation of defects is attributed to the manufacturing conditions, which are selected based on the process nature, machine specifications, and the feedstock properties. If these conditions are not selected carefully, the meltpool dynamics may suffer from bubbles and discontinuities during the layering process [4], which consequently affect the geometrical/physical consistency of the manufactured parts. The characterization of these defects and their criticalness level is important as it conditions the selection of the postprocessing options, the selection of the optimization strategy, and the selection of the measurement and the nondestructive evaluation method. For instance, simple geometrical parts don’t require complicated parametric setting, unlike parts that contain embedded features or free-formed shapes, such as lattice or topology optimized structures. Also, the shape of the internal pores can be used to properly adjust the

Quality Control for Additive Manufacturing

Fig. 47.2 Examples of defects in PBF-manufactured parts. (a) Internal Cracks [5], (b)(c) Pores and Internal Voids [6], (d) Balling and Discontinuities [8], Geometrical Deviations: (e)(f) Thickness Loss [9], (g) Edge Loss [9], (h)(i) Wrapping [9]

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parametric setting of the layering process. For example, low energy density can result in the formation of lack of fusion elongated pores, and high energy density can result in the formation of keyhole circular pores. Additionally, the location of the target defect can condition the selection of the post-treatment process. Finally, the selection of the proper evaluation method is based on its detection sensitivity and on whether it can access the target defect. In some cases, these defects can be ignored if they don’t reach the critical limit. As shown in Fig. 47.3, the end quality of any PBFmanufactured part is dependent on the level of control at the different stages of the process by the different actors. The defects described in this section are observed after the

manufactured parts are removed from the build platform, although adequate observation during the layering process may facilitate the quality validation or the prediction of the evolution of these defects. Figure 47.4 illustrates a simplistic chart that explains the stages of formation of these defects, the main parameters involved, and their propagation in tracks, layers, and part levels. Following the meltpool formation, different inconsistencies may appear based on the concentration of the provided energy and on the amount of the deposited material. These inconsistencies can propagate throughout the scanning direction if the layering parameters are not adjusted to counter them. When layers are generated one upon another,

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Fig. 47.3 The Cumulative Effect of Different Process Actors on the End Quality

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thermal gradient and surface roughness may cause internal irregularities and deformation. These defects can be classified into several categories [7, 8, 9]. Here, we regrouped them as follows: geometrical defects that affect the geometry/dimensions of the PBF-manufactured parts through changes in size or shape; internal material-related defects that have an influence on the mechanical properties of the part; and surface defects that are related to the micro-scale and textures of surfaces.

47.2.1 Geometrical Defects PBF-manufactured parts may suffer from different types of dimensional and geometrical deviations, which can manifest in multiple forms, as shown in Fig. 47.5. The various geometric defects introduced in PBF are classified into in-plane and outof-plane defects. In-plane defects lead to deviations in the plane of a manufactured layer, while out-of-plane defects correspond to deviations in the orthogonal build direction [10]. The most widely known source of geometrical deviation is shrinkage, which is the result of excessive material heating

Layering parameters

Simulation parameters

Post-processing protocol

Inspection protocol

followed by a rapid cooling rate [11]. Shrinkage in the upper layers is the source of edge loss at the end of overhang areas in PBF-manufactured parts. This phenomenon is the result of an offset between the manufactured layers, and it leads to layers deformation. Shrinkage is the main cause for elevated edges and can compromise the successive layers deposition [12]. Another source of geometric deviations is non-homogeneous thermal gradient between the current built layer and the previous layers, which may result in warping and out-of-plane deformation [9]. Also, the change in the surface tension and the temperature gradient can lead to shape degradation and layer swelling. Finally, the staircase effect can lead to dimensional inconsistencies, and its impact depends on the layer thickness and on the build inclination angle [13].

47.2.2 Internal, Mechanical, and FeedstockRelated Defects Porosity The existence of porosity can be desirable in numerous applications, but in most cases, it is detrimental to the overall

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Fig. 47.4 Defects propagation in PBF process

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quality aspects of PBF-manufactured parts. The porosity is the source of internal and external defects as they act as nuclei for cracks and interlayer deformations. Internal pores are attributed to several factors: the meltpool solidification rate; the existence of unmelted particles; the inconsistencies in temperature gradient; the poor layer adhesion and inhomogeneity of layers; the choice of post-treatment process; and the poor feedstock quality. The pores in PBF-manufactured parts can be divided into feedstock-based and process-based pores [3, 14]. Feedstockbased porosity is related to the gaseous voids and inclusions inside the feedstock powder, which are entrapped in the deposited layers. Mostly, these pores are spherical in shape and can be reduced by optimizing the powder atomization process. For example, it is established that the selection of the

feedstock powder production method can largely reduce the formation of interlayer pores. On the other hand, process-based porosity can be reduced by tuning the manufacturing settings. This type of pores is the result of energy-material interaction, and this interaction depends on selecting the proper parametric operational windows. Figure 47.6 illustrates process-based porosity formation with respect to the change in the projected energy. If a suitable amount of energy is projected on the powder, a stable and a turbulent meltpool is formed, where the spatter particles are melted or ejected by the gas flow [15]. The morphology of the pores is an indicator of the process parameters that may require adjustment. For example, high energy density can eliminate small pores. But if the projected energy is excessive, keyhole pores are formed. The smoke

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Fig. 47.5 Different cases of geometrical deviation

Type of geometrical defects

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Fig. 47.6 Pores Formation Mechanism: [a] Balling, [b] Lack of Fusion, [c] Optimal Sintering, [d] Keyholes

results from the evaporation scatters projectiles on to the meltpool and affects its stability. Also, the excessive penetration creates cavities forming gas pores [16]. But, if the projected energy is not enough to fully melt the powder, then the formed meltpool will be less stable, resulting in a weak adhesion between successive layers. This lack of fusion is usually attributed to a high scanning speed, high powder deposition rate, or to a large hatching distance. In this case, the flowability of the meltpool becomes compromised, and due to the high surface tension gradients, the meltpool breaks into separated zones [17]. The effects of the porosity in PBF-manufactured parts can be variable. The existence of internal pores during the layering deposition is shown to decrease material hardness [18] and to decrease the fatigue life by acting as concentrators

of internal stress [19, 20]. Also, when the porosity reaches 1%, it can decrease the tensile strength [21]. The porosity, alongside the surface roughness, was experimentally determined to be a contributor to the propagation of cracks in laser PBF [22]. Several options can be used to evaluate the porosity. A non-expensive option to measure the porosity in manufactured parts is the Archimedes method, where the weight of the part in air and its weight submerged in fluid are compared [23–25]. However, if more information is required such as the distribution and the size of pores, Scanning Electron Microscopy (SEM) can provide information regarding surface deviation or pores location using pixels size and color as indicators of pores characteristics [26, 27]. However, SEM is a destructive method. If a nondestructive

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analysis of the internal structure is required, X-ray Computed Tomography (XCT) is better suited to evaluate the characteristics of internal defects [28, 29].

Layers’ Adhesion, Cracks, Delamination, and Balling Cracks represent a separation between successive layers. The change in the distribution of thermal gradient in the meltpool during the solidification phase is the main cause of the cumulation of internal stress. This phenomenon leads to the formation of areas inside the manufactured parts with weak adhesive bounds, which develop to internal cracks and delamination. Another source of crack formation is the low thermal gradient and lack of fusion. In PBF, inclusions can be the result of unmelted particles or contaminated feedstock that get get trapped inside the scanning track. After the manufacturing process, cracks can be initiated because of the existence of internal inclusions, which work as stress concentrators. Due to the challenge internal cracks pose, researchers investigated the formation of cracks and tested several control protocols to reduce this phenomenon [30]. Crack’s evolution was studied using statistical model to perform structural health monitoring in the aeronautical sector [31]. The effect of cracks and surface conditions on the mechanical properties during both static and dynamic loading in PBF-manufactured parts has been investigated as well [32]. Low energy sintering is the main cause for balling formation in PBF. Balling is the result of the accumulation of multiple factors, which include the lack of material in the sintered area, poor wetting conditions, and high oxidation rate [33, 34]. Due to these factors, the meltpool stability may be compromised and it may solidify into balls that form discontinuities, which act as voids and crack initiators [35–37]. The control of this phenomenon depends highly on selecting the feedstock and the processing parameters (such as laser exposure time, layer thickness, building subtract) to reach a proper powder consolidation state and avoid inhomogeneous sintering [35, 38]. Alongside producing low quality parts, the damage of ballings can extend to the manufacturing machine as it can damage the powder deposition mechanism and can increase the build time and cost. Surface and Texture Any form-related errors detected in PBF-manufactured parts are the consequence of complex interaction between the feedstock material and the energy source [39]. The material-energy interaction results in the formation of the meltpool, and if this interaction is not properly controlled, multiple defects can be introduced such as ejected particles, warping, balling, etc. [40, 41]. As consequence, the topography of the surface is dominated by weld tracks following the solidification of the meltpool, which produce a strong texture

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directionality indicative of the laser or electron beam path [42, 43]. Usually, these weld tracks are like chevron-shaped ripples and may contain small-scale thermal cracks and areas of local oxidization [44]. Also, additional high aspect-ratio singularities (deep recesses or sphere-like protrusions) are detectable throughout the weld tracks. Deep recesses could appear because of incomplete seams between the weld tracks, or because of balling phenomena or open micro-porosity [45, 46]. On the other hand, different sources contribute to the formation of sphere-like protrusions such as unmelted or partially melted powder particles, spatter particles (molten material ejected from the melt pool during beam traversal), and balling (caused by the insufficient heat in overhang areas) [45, 47]. PBF-manufactured surfaces are created through melting and re-melting the build layer and several layers underneath it. This affects the final appearance of the top surface, while forming specific recognizable patterns [48, 49]. The topography of the side surface is dominated by the presence of sphere-like protrusions, which are formed from adhered powder particles in the surrounding powder bed. This topology is also affected by multiple factors such as the local surface angle, the adhesion between layers, the consolidation rate, and the unmelted bed powder. For example, the number of protrusions rises as the build angle increases, while less proportion appears on the upwards facing. Also, the staircase effect refers to the visibly offset layers, which change with respect to the build orientation [47, 50]. In laser-based PBF, the excess projected energy acts to sinter loose adjacent powder around the build boundaries [51]. In electron beambased PBF, the build process pre-sinters a larger region around the build prior to melting the layer [11]. Defects that could appear on the side surface include pores and thermal cracks at smaller scale, and at large-scale may include large recesses due to delamination and remnants of the build supports that leave large protrusions. More specific challenges that PBF bring to coordinate metrology are related to the characteristics of manufactured part such as complex freeform shapes, surface texture with high roughness, multiple occlusions, difficult-to-access features, and wide material range with different optical and surface properties [47]. All these characteristics may contribute to measurement errors and deviations between different sensors measuring the same surface.

47.3

Defects Detection and Inspection Techniques for Additive Manufacturing

Nondestructive Evaluation (NDE) is an indispensable tool to assess the quality aspects of PBF-manufactured parts. NDE success is measured by its capability to identify the characteristics of the internal/external defects and by its

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applicability and its repeatability levels. Destructive Evaluation (DE) is not an option in the case of PBF, especially in high value and highly complex parts. The widespread of PBF is dependent on optimizing NDE protocols and on overcoming some of its limitations, including the lack of a standardized measurement protocol (compared to conventional manufacturing) and the lack of physical reference standards [52, 53]. The selection and the applicability of the NDE depends on several considerations. This includes the cost/time factor, the target quality aspect, and the geometrical complexity of the inspected part. This selection becomes limited for overly complex geometries, inaccessible regions, and thick-walled areas. Also, for selecting an effective NDE strategy, identifying the location of defects and their level of criticalness is essential, instead of implementing a full evaluation strategy. Finally, instead of a post-manufacturing NDE, in-situ monitoring can help reduce waste material and shorten production time [54].

47.3.1 End Quality Inspection

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To observe the different defects presented in the previous section, the implementation of NDE methods are necessary. In literature, several inspection systems have been used, with a particular focus on in-situ systems as they offer the possibility to proactively observe the evolution of internal structure during the layering process. Yet, the application of ex-situ control and measurement remains dominant.

X-Ray Computed Tomography XCT is a non-destructive evaluation technique. XCT has been used increasingly in many fields including geoscience studies [55], metrological applications [56, 57], building and biological materials inspection [57–59], and in several applications in the industrial sector [60]. XCT has the best inspection capabilities for assessing porosity in highly complex parts. Indeed, its spatial resolution is sufficiently enough to detect/locate/evaluate the internal flaws. However, XCT suffers from several drawbacks. The type of parts that can be inspected depends on the X-ray penetration and the chamber size. Additionally, XCT has a relative high cost and long inspection time. Data acquired from XCT requires specialized software and substantial time for image processing. These issues are influenced by several factors such as the selection of parameters, the images reconstruction, and analysis protocols [61]. Figure 47.7 illustrates the working principle of XCT systems. XCT generates successive 2D projections (radiographies) of target part, which are taken at various angles. The target part is placed on a rotating plate between a detector and

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an X-ray source. These projections are created by registering the linear attenuation coefficient of X-rays through the target part on the detector. The stack of projections is then used to numerically reconstruct a 3D model. To separate the borders of regions of different attenuation corresponding to different materials, several dedicated software can be used for internal/ external analysis and for surface determination using thresholding algorithms [62, 63]. In the case of PBF, XCT has been used in a variety of applications. One application is the evaluation of internal structures. This includes metrology, especially for evaluating internal geometries, where the usage of coordinate measuring machines is not suitable [63]. Also, XCT was used during mechanical testing to measure the mechanical performance of AM part, such as the determination of the load stress and the associated elastic modulus [64], the estimation of the

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deformation rate in real-time [65], the identification of pores propagation, and the effect of the post-treatment process [66]. Although other 3D topology measurement techniques already exist, XCT was also used and applied to measure the surface roughness and internal structures. Through the tuning of parameters such as the frame averaging and the magnification, XCT produced comparable results to traditional optical and contact profilometer measurements [67–69]. Another usage of XCT was the qualification of feedstock metallic powder and its morphological structure, which provided information regarding internal decomposition and powder size distribution [70, 71]. Similarly, XCT can be used to identify the optimal operational conditions to reduce internal defects. Parameters such as scanning strategy/orientation/spacing/speed were shown to reduce porosity and produce high dense part [72]. Other layering parameters such as layer thickness and particle size distribution have been identified as critical using XCT [73]. XCT can give indications to the stability of the process by identifying the characteristics of internal pores such as shape and position. For example, irregular keyhole pores are sign of an excessive energy input and meltpool evaporation [16]. Additionally, the effect of postprocessing methods such as hot isostatic pressing was observed on pores closure using XCT [74].

Optical Scan Technique Optical-form measurement systems present several advantages compared to single-point tactile probing systems, as they allow a faster measurement rate with higher sampling densities. Available optical-form measurement systems have seen a significant improvement in accuracy and in precision in the field of PBF. Figure 47.8a illustrates an example of an optical measurement system. Optical scan systems can be regrouped into two families: passive and active systems. Passive optical systems operate under static ambient light, but without the need to spatiotemporal modulated illumination. Most passive systems integrate one or multiple industrial cameras and image processors to recreate the 3D digital model from several correlated images. On the other hand, active optical systems use their own light sources to either raster scan or spatiotemporally vary the illumination of the surrounding environment. They reconstruct the 3D model by detecting the modulation of projected illumination caused by the shape of the part. A clear classification of passive and active optical techniques was proposed in literature. They were evaluated based on the measurement range and accuracy. For example, interferometry and confocal optical systems have high accuracy, while time of flight pulse-based systems have less accuracy [75, 76]. One example of passive optical systems is commercial stereo vision that can be used for scanning PBF-manufactured

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parts, even if they are less accurate when constructing the 3D model. An example of active optical systems is the triangulation-based instrument, which consists of one or multiple industrial cameras and a structured light source. The advantage of passive optical systems compared to active optical systems is that they are cheaper in terms of hardware requirements, more compact, and easier to use [76]. Passive optical techniques consider additional assumptions and simple computational requirements when constructing the 3D model. This leads to a less accurate, but a faster measurement. In addition, passive optical techniques use visual or physical indicators like surface texture, focus, shapes, and shading to reconstruct the 3D model [77]. Hence, most passive optical systems require textured surfaces to recognise mutual features. This process is simplified in active optical systems since only the overlaid illumination is used to research correspondence. Active optical systems are developed for industrial applications, where both high accuracy and reasonable speed are demanded [76]. Typically, the automotive and aerospace industries demand tolerances in the range of few hundreds of micrometers. These needs are achievable with existing traceable commercial optical-form measurement systems used in controlled environment, through laser triangulation and structured light systems. Furthermore, current available laser triangulation and structured light systems are usable for the characterization of the rough surface texture of PBF-manufactured parts. Finally, highly complex geometries can still limit the use of current optical-form measurement systems. Optical sensors can function if the inspected surface is accessible. This means the inspected surface must be in the light ray or camera direction. This limitation can be treated by combining a series of measurement through multiple-sensors and by applying data fusion methods. Also, to achieve tighter dimensional tolerances, many manufacturers polish partially or fully the surface of part.

47.3.2 Other Measurement and Characterization Systems Tactile/Contact Measurement When characterizing the geometric and dimensional defects of PBF-manufactured part, contact measurement systems remain the reference in terms of quality and accuracy of the generated data, and this is due to the maturity level of these systems [78]. Coordinate Measuring Machines (CMM) equipped with contact probing heads are one of the most accurate tactile measurement systems [79]. CMM can be defined as a higher motion system for positioning a sensor around the inspected surface. Different sensor technologies are used in conjunction with CMM. Among the contact probing systems, we can define two categories: touch trigger

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probes that read the coordinates of each contact point; and scan probing systems that remain in contact with the surface of the specimen throughout the movement of the sensor and that read the contact points coordinates at a given frequency. It should be noted that CMM can also be combined with contactless optical sensors such as laser plan or structured fringe projection. Figure 47.8b shows a classical tactile measurement system. Probe-based sensors can function if the inspected surface is accessible. Consequently, tactile systems cannot be used to inspect internal dimensions and geometries. One of the main advantages of PBF is its ability to manufacture parts with complex internal features and shapes. Therefore, the use of contact measurement systems can only be reserved for the inspection of the external features. Furthermore, the surface texture has an influence on the accuracy of measurement [77]. Indeed, PBF-manufactured parts have a rather degraded surface roughness, which limits their use as functional parts [47]. Under these conditions, the use of contact probing systems should not be considered. PBF is usually followed by other machining process to obtain functional surfaces. Following this step, the use of contact probe systems can be reconsidered. It should be noted that recent developments in PBF systems are increasingly opening the door to the production of parts with functional surface roughness, without the need for additional treatment. For this new generation of machines, contact measurement system can be fully considered.

Ultrasonic Inspection Ultrasonic inspection is a non-destructive measurement technique. Ultrasonic waves are used to detect internal inconsistencies in PBF-manufactured parts such as pores and cracks. Also, material-related microstructural and mechanical properties can be evaluated using these waves. Ultrasonic Testing (UT) is sensitive to penetration defects, pores, and inclusions. It is dependent on several factors such as the distance between the emitter and the specimen, the emitted wave frequency, the projection direction, and the geometric characteristics of the specimens. Figure 47.8c illustrates the working principle of UT [80]. To detect defects, an emitter transmits ultrasonic waves into the targeted area and a receiver captures the reflected signal. This reflected signal is expressed as a function of the voltage/ time and is influenced by the encountered internal inconsistent forms. The changes in these reflected signals give indications on the shape, size, and position of these inconsistencies [81]. UT was used for evaluating the mechanical properties such as the elastic properties of stainless-steel specimens, and the results were comparable to destructive measurement [82]. Similarly, the investigation of elastic properties of PBF-manufactured parts using UT and XCT was studied as

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a function of the specimen size, the thermal gradient, and the scanning strategy [83]. Also, UT was considered a technique for in-situ monitoring during the manufacturing process for early evaluation [84]. It was used for early defects detection through in-line monitoring. Real-time acoustic emissions were used to detect any internal cracks and delamination during the powder deposition process [85]. Similar ultrasonic inspection protocol was also used for in-line evaluation of the layering deposition in PBF. This inspection illustrated that the micro surface defects and flaws in a single layer can be detected using UT [86]. For PBF, UT was integrated to monitor the meltpool dynamics, the residual stress, and to examine the factors affecting the data acquisition process [87, 88]. Additionally, ultrasonic in-situ spatial mapping of porosity in PBF-manufactured specimens can be used as an indicator to the changes in the process performance [14]. Also, UT can be used for both in-line and post-manufacturing defect inspection [89]. For composite structures, UT was beneficial for early porosity characterization in feedstock material [90]. Finally, UT was applied in structural health evaluation for cracks localization and for damage accumulation, which produced comparable results to those obtained using eddy current and radiography [91]. UT is useful to measure the residual stress in PBF-manufactured parts [92]. However, conventional ultrasonic or advanced ultrasonic testing, such as phased array ultrasonic testing combined with total focusing method, are more suitable for in-situ monitoring than for post-process inspection. Indeed, the complexity of manufactured parts and the high porosity rate can limit the effectiveness of UT as it may increase signal noise and reduce the quality of gathered data [93].

Resonant Ultrasound Spectroscopy, Infrared Thermography, and Scanning Electron Microscopy Multiple NDE methods used on conventionally manufactured parts are not suitable to evaluate highly complex geometries of PBF-manufactured parts. One technique that is mainly used in the automobile sector until now is Resonant Ultrasound Spectroscopy (RUS) [94]. An example of an RUS system is illustrated in Fig. 47.8d. Although this method doesn’t allow defects localization, it has the advantage over XCT in terms of simplicity, repeatability, speed, cost, and its independence on the size and density of the scanned specimen. RUS is not considered as measurement method, as they enable sorting defective specimen based on a set of reference defectless specimen. This is done by studying the shifts in specimen resonant spectrum corresponding to the vibrational modes. To increase the application of RUS, a suggested approach is to study the correlation between the defects size and the frequency shifts [95, 96].

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Another variant of optical scan technique is the InfraRed (IR) Thermal Imaging, which detects the characteristics of defects through using the thermal radiations of the target part, then this is compared to the thermal radiation of the surrounding material. Infrared cameras were used to identify the position of defects based on the captured thermal radiation emitted from the manufactured parts [97, 98], as shown in Fig. 47.8e. The same approach was used to provide results in real time during the manufacturing process, with an average success rate when detecting micro defects [99, 100], as shown in Fig. 47.8f. SEM can deliver better results than camera-based optical scan, but it requires preparing the specimen before the scanning process. Figure (47.8g) shows an example of the results that can be obtained through using SEM [20]. This technique is suitable for conducting powder morphology inspection and internal structure analysis. SEM was used in many AM related applications such as pores dimensions detection [23, 27, 101].

47.3.3 Test Artefacts To evaluate the performance of the PBF, multiple direct measurements are required. However, conducting composite measurement can be costly and time consuming and may not provide sufficient information to connect errors in the specimen to their sources. An alternative option is the measurement of a specific test part and to use the gained information to diagnose and to assess the overall performance of the manufacturing process. Test Artefacts (TA) are one of the means that can be employed in the context of QC. TA allow the manufacturer to perform geometrical/dimensional check, to evaluate the manufacturing conditions, and to assess the limitations of the process compared to the desired objectives and compared to other processes. TA can be classified based on the evaluated quality aspects. These aspects include the dimensional performance of PBF, the mechanical properties and the surface texture of the manufactured parts, and the parametric configuration of the process. No standardized criteria exist to design TA, as they are usually project-specific, and the geometry/dimensions are selected based on the studied features. However, several guidelines were set to make generic TA. These guidelines are related to the cost/time of the manufacturing and the measuring process. Other guidelines are related to the size, number, type, and position of the geometrical features on the TA [102, 103]. In an effort towards the standardization of these rules, ISO and ASTM developed the norm ISO/ASTM 52902E, which defines artefacts that are designed to test multiple aspects of PBF such as accuracy, machine resolution, and part texture.

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Several examples of TA have been designed in literature and and some are illustrated in Fig. 47.9. For example, geometrically simple TA were used to evaluate the smoothness of surface of AM parts produced by different AM machine [104]. Several authors proposed more complex TA that incorporate multiple features to investigate the process capabilities/limitations. The importance of designing these TA emerges from the need to pinpoint the calibration errors in the machine/process, as they act as contributors to the inconsistencies in the final part. The main objective of these efforts is to evaluate different AM processes and to identify whether they can produce comparable results [105, 106]. Furthermore, TA have proven useful in micro-engineering applications [107]. Although the benchmark geometry constructs a basis for tuning PBF, certain technical aspects, such as the process repeatability, are needed to be considered when designing the TA. This can be done through different approaches: adding multiple identical features to the TA; symmetrically repartitioning the artefact into similar areas, manufacturing the same artefact multiple consecutive times without changing the manufacturing conditions. Finally, the standard deviation of all the features measurements is an indicator of the repeatability of the process. Some authors have considered the aspect of repeatability, but others argue that manufacturing the same feature in different positions on the TA may allow the investigation of the spatial repeatability but not the process repeatability [103, 108, 109]. Geometric Benchmark Test Artefact (GBTA) is a novel concept that is developed in the literature. GBTAs are used to predict the capability of the process to manufacture specific features, and consequently, provide information regarding the geometrical characteristics of manufactured parts. However, applying generic GBTA for different PBF processes makes it harder to precisely evaluate the process performance. For this reason, feature-specific approaches were proposed, which relay on a systematic design methodology for artefacts features selection [110, 111]. Another field of application of TA is the detection of defects and the improvement of the manufacturing conditions. This requires manufacturing artefacts that are designed specifically to differentiate and to identify the origin of defects. This is done by linking the metrological observations to the parameters of the process through using a correlation matrix [112]. When designing TA, several constraints related to the measurement options must be considered. Multiple TA were designed based on standard and normative geometrical features, and consequently didn’t cause metrological issues, which is not the case of PBF-manufactured parts that contain freeform surfaces. CMM can provide stable results when measuring TA. But some authors remarked several issues related to the measurement accuracy, resolution, and time, which present

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Fig. 47.9 Examples of test artefacts in literature: (a) [104], (b) [107], (c) [112], (d) [116]

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themselves in TA with fine details or inner surfaces. This was noticeable when comparing the results of CMM to the results obtained using XCT scan [113–115]. Several authors designed TA while considering accuracy of measurement. This accuracy is estimated by using different measurement techniques or by performing multiple measurements for the same features. These techniques include laser scanning, CMM, and XCT scan [116, 117]. More research efforts investigated the advantage of using different measurement techniques and concluded that the contactless techniques (ex: XCT scan) have an advantage compared to tactile probes (ex: CMM) [47, 118].

Inference Experimental plan

Machine Learning for Quality Control in Additive Manufacturing

As the capacity to obtain large amount of data increases, the need to analyse data and extract useful knowledge becomes more relevant. This is especially true in the field of smart manufacturing, where the size of the gathered data can increase exponentially. Machine Learning (ML) is a branch of Artificial Intelligence that makes use of this data and present observations to predict the process behaviour in the following iterations [119]. Figure 47.10 illustrates the general principle of ML. Following a phase of observations and data collection,

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datasets are trained to find hidden relationships within the data and to evaluate the confidence of the computational approach. Different algorithms can be implemented for this purpose, including but not limited to, Regression Tree (RT) [120], Multivariate Adaptive Regression Splines (MARS) [121], Support Vector Machine (SVM) [122], Nearest Neighbour Regression (NNR) [123], Artificial Neural Network (ANN) [124], and Gaussian Process (GP) [125]. The selection of the proper approach is based on the nature of the observations and the desired predictive accuracy. The usage

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of ML for AM is applied in multiple domains such as manufacturing cost estimation [126], topological optimization [127], and quality prediction [128].

47.4.1 Machine Learning for Quality Control Applications: In-Situ Monitoring One field of application of ML in the context of PBF is in-situ monitoring. Different sensors can be mounted on PBF machines and can be used to achieve in-situ process surveillance [51]. For this context, ML is used to anticipate the potential defects that may appear before the layering process is finished. The effectiveness of this approach is dependent on the previously acquired knowledge, the selection of the proper ML algorithm, and the nature of the monitored data. One application is using data obtained from visual sensors to control the process. Real-time layer-by-layer in-situ images are used to monitor the rate of pores formation and to classify PBF-manufactured parts as acceptable/defective [129]. A second application is the study of the meltpool evolution. SVM and ANN were implemented to detect any inconsistencies during the meltpool formation [130]. Also, the change in temperature gradient during the meltpool solidification was studied to classify potential defects that may occur. For this purpose, different systems that detect the variations in the acoustic emissions were used. One system implemented NN algorithm [131], and another system implemented deep belief network [132]. Another application of ML for in-situ monitoring is the observation and control of the manufacturing conditions. Using data acquired from acoustic emissions as input, the machine state was monitored during the layering process to identify failed manufactured parts using the clustering method [133]. Additionally, the interaction between the powder bed and the coating blade can be an indicator to the presence of defects. Computer Vision [134] and NN algorithm [135] were used to identify the powder flow and the powder bed state after the coating step and before the sintering step. Finally, a limited work was done in the field of on-line closed loop control system. For example, microscopic visual images of textual features were used to predict the evolution of defects in PBF [136].

47.4.2 Machine Learning for Quality Control Applications: Process Optimization and Defects Prediction Here, ML is used to predict the process performance, or the manufactured part quality based on previously gathered data. Supervised ML is best suited for this purpose. Usually, the objective of this approach is to construct a predictive map by

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learning the relevance between the input data (process parameters) and the experimental output data (quality aspects), then to make inference based on new defined input. Additionally, this approach can be used to distinguish between different classes, and to assign the appropriate class to new input data based on trained classes. Finally, both classification and regression can be used in conjunction to improve the obtained results. In the case of PBF, a gaussian process-based predictive map was constructed to identify the parametric configurations of scanning power/speed and the corresponding porosity percentage [137]. The same surrogate model was used to predict the meltpool geometric characteristics such as the depth [138] and the width [128], and to avoid any parametric configuration where discontinuities and ballings may appear. Random Forest Network ML was used to establish processstructure-property relationship, and to predict the porosity percentage based on part orientation and type of powder [139]. To reduce tolerancing-related issues, bayesian inference was implemented to detect shape-related defects [140]. Unsupervised ML is also used to regroup data that share similar properties. For example, ML was implemented to reduce wastes by detecting the progression of the layering process using ultrasonic testing and k-mean clustering. The collected data were then compared to an established database to determine if the manufacturing job is considered a failure or not [133]. In PBF, defective regions in the meltpool were monitored using principal component analysis technique to proactively reduce the structural inconsistencies [141]. Another application case is NDE data analysis. As an example, ML was used to increase the selectivity and efficiency of the RUS method at sorting lattices with different number of missing struts [142].

47.5

Key Characteristic for Additive Manufacturing

Key Characteristics (KCs) is a concept that emerged in the late 90s. The attention to these KCs is reflective of multiple industrial needs such as the reduction of wastes, variability identifications, and product optimization. KCs is not a concept that is implemented in the context of AM. However, it is widely used in the automobile industry and in the assembly domain. The term KCs is referred to both sensitive product properties and part dimensions that have high sensitivity to variability [143, 144]. KCs are assigned in product/components/parts/process levels to key specifications where variability should be strictly controlled. These KCs are given priority during the manufacturing and the optimization phases, as any deviation from the predefined specifications the product failure. Different authors have proposed different definitions for KCs [145–147].

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47.5.1 Key Characteristics and Quality Control In this context, KCs are considered as method to implement QC strategies. Firstly, KCs are intended to be used as mean to focus resources/efforts on the causes of large variabilities in the process performance, and the subsequent effects on the product features. Implementing sophisticated QC strategies, which examine the effect of multiple variability sources, is expensive. Hence, it becomes more relevant to narrow the field of study to the process stages/part dimensions, where defiance is more likely to occur. Additionally, from a statistical modeling point of view, increasing the number of parameters (or model dimensions) will exponentially increase the complexity of the model, and consequently will undermine its capacity to represent reality. Thus, studying a limited number of parameters will allow the examination of the relative importance of each individual parameter. Finally, implementing KCs-related strategies will allow the manufacturer to select a more adaptable improvement plans for the following manufacturing iterations, as the focus will be shifted toward deterministic manufacturing conditions. Consequently, the time/cost of product rework will be reduced. In this Section, we will present the concept of KCs in literature, then we will present a study case KCs method is implemented in the context of AM. The concept of KCs and its implementation in the context of PBF was demonstrated and studied in [148, 149].

47.5.2 Key Characteristics: Literature Review Implementation, Selection, and Management of Key Characteristics The implementation of KCs aims to increase the communication between the process actors, to reduce the investigated data size by focusing on the important aspects of the process, and to correlate factors such as cost/time/quality to the manufacturing capabilities. Different KCs implementation approaches were adopted in literature, and they can be divided into proactive and reactive approaches. In proactive approaches, KCs are assigned before the manufacturing process starts based on process knowledge, and in reactive approaches, KCs are assigned after the manufacturing finishes and after the quality-related problems arise. The selection of KCs is based on several factors: the level of attention needed to keep a specific parameter/specification in a defined range; the client’s satisfaction; the risk of potential process/part failure; and the need to maintain the repeatability/assemblability aspects. The first step for KCs selection requires the construction of a traceable flowdown thread of the process and the product composition. This is followed by

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implementing the proper process control to reduce the anomalies in the manufacturing process and reduce the effect of variations on the products’ characteristics [146, 147, 150]. Multiple solutions were implemented in literature to select and manage the KCs. For example, identifying the optimal assembly sequence is an option to identify the associated KCs. This is performed using multiple tools such as assembly-oriented graph and tolerance analysis [144], historical data [151], risk assembly analysis [152], or by employing specific optimization strategies such as genetic algorithm [153]. Selecting KCs in assemblies is based on variation propagation principle. Variation Mode Analysis is used to assign a risk coefficient to any parameter to reflect its criticalness and to prioritize the optimization choice [154, 155]. When the KCs are assigned by their importance, several options present themselves including proper resources allocation and processimprovement [156, 157], planning strategy optimization [158, 159], causes of variability identification [143, 160], and adaptive inspection strategy selection [157, 161]. To achieve KCs in assemblies, where the dimensional integrity is important, a set of smart features can be used to absorb the variations, to free the aseembly from constraints [162], and to optimize the adjustability of the product [163].

Main Properties of Key Characteristics Several definitions of KCs are present in literature. These definitions describe their nature, how they can be identified, the different implemented detection strategies, and their impact on the process/product if their limits are not respected. KCs represent a set of features/properties/parameters/conditions, which are overly sensitive to any internal or external factors. These have different forms based on the domain. For example, KCs can refer to critical tolerances for assemblies. For chemical products, KCs refer to critical chemical ingredients and portions mixture quantities. When evaluating the mechanical performance of precision products, KCs may refer to hardness and resistance to fatigue. The tools to identify KCs can be divided into qualitative and quantitative tools. They are used individually or collectively for different purposes. Taguchi Loss Function is used to correlate cost to variations. If combined with process capability indicators, the cost variation generated by any change in a specific feature value can be evaluated. Statistical Process Control is used to visually measure variations and identify, for a given feature value, if the process is under control. Design of Experiment is used to structure a testing strategy to understand the contribution of specified factors using minimal resources. Variation Analysis is used for predicting how variation in a part affect the assemblies. Finally, historical data and process knowledge are used to formulate the level of importance of specific process stage or product features. Two strategies exist when searching for KCs: proactive and reactive detection. Proactive detection takes place during

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the design phase and it is used to make the structural and functional design insensitive to variations, or to assign acceptable limits. On the other hand, reactive detection takes place during the development phase to improve assembly/planning/inspection strategies, or it takes place after the manufacturing phase to determine the root causes of existing problems in the product and to improve the following production iterations. The type of impact on the process or on the product when KCs are not achieved can be different. The most obvious impact is the dissatisfaction and the compromised safety of the user if the product fails. Consequently, this can generate additional cost for repair, wasted resources, or lead to ineffective process planning and inspection. Finally, not respecting the defined range of KCs can generate a type of loss in quality consistency.

47.5.3 Key Characteristics for AM: Application Case in Porosity Characterization As illustrated in Fig. 47.11, a systematic approach for KCs identification in the context of PBF was proposed [149]. This approach identifies the product’s features, traces them from the functional level to the manufacturing level,

Design objectives

• KCspart are defined as “a set of features that describe the quality aspects of an additively manufactured part. They are selected based on their importance for achieving the defined value and the associated structural and functional requirements. If these features are not maintained, the target added value can be compromised.”

Process knowledge

Selection criteria

Evaluation metrics Key characteristics (KCs)

Functional design Structural decomposition Experimentation Flowdown construction

Key characteristics (KCs)

CCs list Modeling approach Expert knowledge Data collection

t bus y Ro riorit p low S hig ens h p itiv rio e rit y

Part quality attributes

Fig. 47.11 Proposed key characteristics identification protocol [149]

establishes specific conditions to narrow the selection of critical process conditions, then collects data and hierarchically identifies the priority of each process parameter to achieve the specific product’s feature. As opposed to conventional manufacturing, where KCs are considered in the case of assembly, we consider unitary parts. The main objective was to establish the cause/effect relationship between the quality aspects and the process parameter. Multiple parameters are implicated in the additive layering process, and yet only a few of these parameters are necessary to achieve optimal process parametric configuration and high-quality part. In this subsection, we describe the approach implemented to identify KCs. We distinguished between two types of KCs: those related to the AM part (KCpart), and those related to the AM process (KCprocess). Based on the main properties of KCs discussed above, the following definitions were proposed [149]:

Process parameters

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• KCsprocess are defined as “a set of process parameters that are selected based on a predefined criterion, and that conditions the defined value chain, which have a statistically detectable effect of the defined KCspart. A small defective selection of these parameters may compromise the integrity and the functionality of the targeted part. These are defined from a limited list of previously selected candidates to prioritize their effect on the KCspart.”

Key Characteristics Identification Protocol The main objective is to determine, based on the target value, the list of KCspart/KCsprocess. The proposed protocol consists of five steps. The first step requires performing a functional analysis to define the design objectives. Based on this, a structural form and a manufacturable decomposition of the different parts is selected. This decomposition should give a clear vision of the KCsparts. This includes the type of defects that can hinder the said KCsparts. The second step requires a comprehensive knowledge of the process to establish correlations, which identifies the relationship between the product’s structural/functional/geometrical features and all the parameters sets during the manufacturing phase. The third step requires the definition of a set of criteria, based on which the number of treated parameters can be reduced. These criteria are set before deciding the proper hierarchical order of the process parameters based on their impact on the KCsparts. Afterwards, this will allow the formulation of a mathematical model or an effective experimental plan. Two criteria had been defined: controllability and dependability. To identify the statistical significance of a certain parameter, the said parameter must be controllable. Here we define controllability as the ability to change the state of certain parameters during the layering process. Also, dependent parameters as those related mathematically or can be expressed as a function of other variables. From a statistical modeling point of view, a model that uses dependent variables as input may suffer from correlation-related issues, and as a result, this can underestimate/overestimate the effect of a certain parameter on the model results. Following this, a list of Candidate Characteristics (CCs) can be formulated. These characteristics are a list of parameters that need to be examined to identify their level of priority. The definition of this list is conditioned by the chosen selection criteria (controllability and dependability). The final steps are related to the data collection and analysis. The data source can either be from experimentation, surrogate model, or from reviewed literature. The collected data is acquired in the form of input predictors/output response, where the input are the CCs, and the output is the predefined KCspart. After the data is collected from a defined source, a hierarchical organization of these parameters is envisaged based on their impact on the response behaviour. This can

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be done through a sensitivity analysis/main effect analysis. A second method is to use a correlation matrix and analysis of variance to determine the variance of each parameter.

47.6

Conclusion

QC is indispensable for the widespread of AM in the industrial sector. The end quality of PBF-manufactured parts is evaluated through three aspects: mechanical performance, dimensional accuracy, and surface texture. All the observed defects that can hinder these aspects are attributed to the manufacturing conditions and to the level of control of the parameters in each manufacturing stage. Identifying the criticalness level and the defects characteristics is important for the selection of the post processing options and the optimization strategy for the following manufacturing iterations. Some examples of these defects and their formation mechanisms were illustrated in Sect. 47.2. Furthermore, the evaluation of these defects is dependent on the measurement technique used. In the context of PBF, there is an emphasis on the non-destructive evaluation, as it is considered the favourable compared to destructive evaluation. The advantages/limitation, the usability, and the application cases of some measurement technique were explored in Sect. 47.3. Also, test artefacts were reviewed, and their importance was explored as a tool for ensuring the consistency of the manufacturing process. Additionally, ML is a method for quality control in the context of AM as it allows to predict the process behaviour based on previously acquired data. More attention was given to the application of ML in the fields of in-situ monitoring and defects prediction, as discussed in Sect. 47.4. Finally, the concept of KCs was introduced and its applicability in the context of PBF as a method for quality improvement was discussed in Sect. 47.5. The different implementation approaches of KCs were presented, and a 5-staged systematic approach for KCs application was proposed.

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Dr. Charyar Mehdi-Souzani is currently senior researcher at LURPA (Automated Production Research Laboratory) at Paris-Saclay University and an associate professor at Université Sorbonne Paris Nord. He is a member of The European Society for Precision Engineering and Nanotechnology (EUSPEN) and ASME. He is a recognized expert in metrology and his current research interests are focused on geometric modeling and data processing based on deep learning and machine learning for metrology, quality control in additive manufacturing, computer-aided inspection, optical measurement system assessment and qualification, multi-sensor multi-scale data processing. He participated in several research projects funded by major French companies, and EU’s research and innovation funding program.

Dr. Al-Meslemi Yahya received his master’s degree in mechanical and Production Engineering from the University of Grenoble Alpes, France, in 2016. He received his PhD in Mechanical Engineering from the University of Paris-Saclay, Paris, France, in 2021. Through his research, he developed a computational approach that combines statistical predictive modeling, design of experiments, and nondestructive measurement analysis for predicting defects in additively manufactured metallic parts.

Kévin Ferreira is a PhD candidate in mechanical engineering at ParisSaclay University, France. He graduated in mechanical engineering (BSc 16, MSc 19) from Ecole Normale Supérieure Paris-Saclay. His dissertation entitled “Data processing for part geometry control in additive manufacturing: from predictive modeling to measurement data integration” looks at lattice structures’ geometric defects characterization and prediction.

Dr. Anne-Françoise Obaton received her PhD in Physics from University of La Rochelle, France, in 1998, and the “Habilitation à Diriger des Recherches” (HDR) from University Pierre et Marie Curie, Paris, France, in 2008. Since 2000, she has been involved in metrology at the French National Metrology Institute Laboratoire National de Métrologie et d’Essais (LNE) in Paris, France. She is conducting research on the investigation and qualification of volumetric nondestructive testing (NDT) methods for quality assurance of AM parts. Since 2014, she is involved in AM standardization (national level: UNM 920, international level: ISO/TC 261/JG 59 – Joint ISO/TC 261-ASTM F 42 Group: NDT for AM parts). She is also involved in COFREND (French Confederation for Non-destructive Testing) groups on XCT, and AM and artificial intelligence in connection with NDT. She is a member of Academia NDT International.

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Dr. Habil. Hichem Nouira is principal researcher at the French National Metrology Institute Laboratoire National de Métrologie et d’Essais (LNE) in Paris, France. He received his PhD in 2008 (ENSMM, France), the “Habilitation à Diriger des Recherches” (HDR) in 2016 (ENS-Paris Saclay, France), and MBA in 2019 (Sorbonne Business School, France). He is an Expert at CCL-CIPM (Consultative Committee for Length – International Committee for Weights and Measures), an Expert at EURAMET European Metrology Network for Advanced Manufacturing, and a CIRP (International Academy of Production Engineering) corporate member.

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Dr. Nabil Anwer is a professor at Paris-Saclay University and the deputy director of Automated Production Research Laboratory (LURPA). He is a member of the International Academy of Production Engineering (CIRP) and serves as the secretary of the Scientific and Technical Committee Design (STC Dn). He has special research interests in Quality Control for Additive Manufacturing, Tolerancing and Assembly, dimensional metrology, and Product Digital Twin. He is an associate editor of ASME Journal of Computing and Information Science in Engineering, editorial board member of Chinese Journal of Mechanical Engineering: Additive Manufacturing Frontiers, and a member of the advisory board of Digital Twin open access publishing platform. He is also a member of the ISO TC 213 (dimensional and geometrical product specifications and verification).

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Post-processing for Additive Manufactured Metal Parts: A Brief Introduction

48

Jonathan Smith and David Butler

Contents 48.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 821

48.2 48.2.1 48.2.2

Post-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 822 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 822 Post-processing Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 823

48.3

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 829

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 829

Abstract

Post-processing of AM built parts is a necessary but nonvalue-added activity associated with ensuring the part can deliver on its promised performances and stay within specifications. In this chapter, a number of topics are covered including heat treatment, surface finishing and modification, and inspection. Keywords

Surface finishing · Hot isostatic pressing · Surface modification · X-ray computed tomography

48.1

Introduction

Additive manufacturing (AM), also referred to as 3D printing, is a technology that has been rapidly evolving since the late 1980s. The initial concept began with stereolithography (SL), patented as a “system for generating three-dimensional objects by creating a cross-sectional pattern of the object to be formed” [31]. This set the foundation for formatting data files to compute the layerby-layer sequence in producing complex parts for the purpose of prototype designs. At present, there are seven J. Smith (*) · D. Butler (*) Department of Design, Manufacturing, and Engineering Management, University of Strathclyde, Glasgow, UK e-mail: [email protected]; [email protected]

categories of the International Organization for Standardization (ISO)/American Society for Testing and Materials (ASTM) AM categories. Two categories are acknowledged as major metal processes for their availability of extensiveness and complexity, direct energy deposition (DED) [1] and powder bed fusion (PBF) [61]. In addition, Vat Photopolymerization, material jetting, binder jetting, material extrusion, and sheet lamination complete the AM categories. Further, a summary of DED and PBF process categories, including subcategories and associated commercial suppliers, is shown in Fig. 48.1. It is also worth noting that additional metal AM methods suggested by researchers such as cold spraying (CS) [71], diode area melting (DAM) [72], and linear friction welding (LFW) [18], among others demonstrate future potential for AM; however, they are still being evaluated to meet ISO/ASTM. A review of the various metal additive processes was undertaken by Frazier [24]. The powder metallurgy (PM) AM technologies have made significant steps from their prototyping predecessor to manufacturing high value metal parts of functioning capabilities. Current PM AM technologies are considered the most adaptable and customizable technology over most sectors for industrial production use [67]. For example, gas turbine blades (products of GE Aerospace) designed with complex internal cooling channels are made via the electron beam melting (EBM) process using titanium aluminide (TiAl) powder to achieve the mechanical properties required for operational use [64]. Mechanical properties demonstrate strength, toughness, creep, and oxidation/corrosion resistance, exhibiting lightweight aerodynamic geometry to withstand conditions of high temperatures while considering the rotational forces required from the turbine’s high-speed rotation. This complex style of design also features single part production which would be unattainable with the conventionally cast turbine blade due to its cooling channel complexity.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_48

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Direct manufacturing (DM) Stratasys Direct metal deposition (DMD) BeAM Laser metal deposition (LMD) Trumpf, mazak, hybrid manufacturing tech.

Direct energy deposition (DED)

Laser-engineering net shaping (LENS) Optomec Wire arc additive manufacturing (WAAM) MX3D Powder metallurgy additive manufacturing processes Laser melting (LM), renishaw Selective laser melting (SLM) SLM solutions, concept laser Selective laser sintering (SLS) 3D systems

Powder bed fusion (PBF)

Direct metal laser sintering (DMLS) EOS Electron beam melting (EBM) GE additive, arcam

Fig. 48.1 Summary of DED and PBF technologies

Additionally, due to the low production volume, the AM process becomes much more affordable and time efficient, making it the more desirable technology for production. This practical case offers many more advantages; however, it would not be possible without the implementation of post-processing, such as heat treatments, machining, surface modifications, etc., in making this part fit for purpose. A key point being surface defects that occur during the build process and stand as an interruption to the final quality of the build. Post-processing simply improves the part quality of its internal/external surface defects and eliminates unwanted mechanical properties. In most cases, the surface roughness has proved to be a challenge in achieving as-built quality and typically requires further processing. Without the aid of post-processing, the as-built surface is a part without function; hence, reviewing the post-processing capabilities is critical in achieving design efficacy during a production build. That said, a study of different post-processes across many industrial sectors and their ability to achieve surface quality will be reviewed within this section.

48.2

Post-processing

48.2.1 Introduction A common theme is clear in comparison to conventional manufacturing methods, which is the irregularities that form on the as-built surface. These highly irregular morphologies of randomly positioned features are a consequence of the physical phenomenon created from fusing and depositing the material during build. Although much research has investigated a minimization strategy for surface irregularities during a given layer-by-layer process [5, 23, 53], they remain persistently abundant. Therefore, it is important for manufacturers to recognize the options available when selecting a post-process and its parameters, as the most effective technology to be used for the job. Post-processing, as the name suggests, is a final stage after a process is complete. It is especially the stage for part improvement, which corrects as-built defects as well as enhancing part areas where the build process is incapable.

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Post-processing for Additive Manufactured Metal Parts: A Brief Introduction

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Fig. 48.2 Independent processes of an AM workflow shown in operational order

Pre-processing

Preparation

Within the AM production workflow, it is also worthwhile addressing the surrounding primary stages, as they reveal the significance of its purpose. Open literature suggests the AM production workflow as being sequenced in the following order: pre-processing, preparation, AM build, postprocessing, followed by a finished component [51, 53] – refer to Fig. 48.2. Pre-processing undergoes computational-aided design (CAD) modeling, computational-aided engineering (CAE) simulation and optimization, followed by the intellectual property (IP) that protects the data while being shared internally and externally [22]. Depending on material selection and part geometric complexity, this is potentially the most critical stage of the process because part quality is the defined accuracy determined from the prediction software. Preparation is typically process specific, which is controlled through processing parameter optimization and material [20]. Once the design is prepared for AM, the CAD data is sent to computer-aided manufacturing (CAM) to automate the process, typically using a computational numerical controlled (CNC) machining strategy that produces the physical part from specified process parameters. Following AM is post-processing which typically involves removing the excess powder as well as the supporting structures and/or substrate [32]. Machining is used to improve dimensional accuracy and thermal treatments are typically required for enhancing mechanical properties, additionally, surface finishing may be required for achieving the desired surface characteristics [59]. The final stage reassures the component meets the sufficient geometry to tolerancing standards as well as identifying any information of defects which undergoes a finalization of correction analysis checks, guaranteeing the certainty of the AM part as fit for function. Within this AM design workflow, each stage enforces the fundamentals of quality assurance, which checks on documentations, part measurement, and analysis to meet the required standards for application. Due to risks of anisotropic shrinkage and warpage, defects, and inaccuracies, the post-processing methods have been considered before commencing AM, thus, ironically,

AM build

Post-processing

Finished part

the post-process begins before an initial build. For example, Galati et al. [25] developed a numerical model predicting the lack of fusion and lateral roughness from investigating the EBM process. The accurate prediction of the surface profile roughness can correspond with specified operator finishing, essentially minimizing the post-processing requirements. Furthermore, Ning et al. [54] replaced a finite element analysis (FEA) method for a novel analytical model, which was capable of predicting part distortions developed from the PBF process. The modeling displays high computational accuracy within a short time frame without relying on iteration-based calculations. As a result, this model can help eliminate part distortions, therefore, minimizing on post-processing typical requirements. However, it is simply put that the required standards would not be met if postprocessing did not exist, so, integrating post-processing within the production workflow is fundamental in achieving total efficiency for part completion.

48.2.2 Post-processing Methods To date, the integrity of powder fused metal AM parts are incapable in achieving what a traditional subtractive manufacturing process can [44]. Unavoidably so, the AM part undergoes post-processing to overcome these undesired properties that exist from the as-build, which makes postprocessing inevitable for AM part completion. Within this section, typical post-processes will be discussed for metal AM part completion with respect to part design issues. Due to the vast number of post-processes being used on AM parts, a characterization table has been developed with the arithmetic average roughness value (Ra) being used to quantify the surface features with comparison to each of the process’s effectiveness.

Support Structure, Substrate, and Powder Removal Support structures act as a pivotal role in the success of the build quality for PM AM components [32]. In most cases, it is a requirement for PBF since it only operates off the vertical

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with each build assembly still subject to gravitational forces. As the process joins material together in a layer-by-layer fashion, it is likely that each layer has a different footprint from the previous layer, which becomes more prevalent in complex parts. Therefore, complex geometries with overhanging structures require the necessary support, also referred to as an anchor, to prevent the build from collapsing. However, the benefits being that each support structure can act as a reinforcement, relieving heat gradients from causing thermal deformations on the part geometry, also known as warpage. This technique is seldom/never used in DED since more degrees of freedom become available which allows a nonplanar slicing (curved layer) technique to be used. This is also found to be productive as it achieves better results for temperature homogenization of the overall part [74]. Although powder AM applications offer many technicalities, they may experience negative consequences derived from handling and management of the powder particles. A primary example being metal ions being released into the atmosphere that become extremely harmful to human health and the environment [3]. Removing the loose powder particles requires a cautious skillset and abiding to the correct Personal Protection Equipment (PPE) standards such as wearing masks, goggles, gloves, etc., is critical. Due to its hazardous nature, removing the powder is also time consuming. A basic removal procedure involves brushing off the powder from the as-build, a similar effect to digging up an artifact, where vacuuming is not effective. Other methods incorporate sandblasting and dry ice cleaning, while the later results in improved properties of abrasion resistance, due to offering a higher quality removal of partially melted powder [8]. Additional research investigates an automated solution to rotate, vibrate, and shake off the powder as a method to speed up production. This process can be managed within the same enclosed environment where the part has been built; therefore, powder removal can be safely and efficiently removed without human interaction. Among the loose powder that requires removal are structural supports. Due to a restricted vertical additive orientation from PBF technologies, enhancing geometric complexity and topology optimization most commonly requires structural supports during build, and this practice is also found in DED technologies. Inspired by polymer 3D printing, soluble support structures have been adopted by DED [34]. An example described by Hildreth et al. [30] utilizes carbon steel structural supports in the DED fabrication of a stainless steel arched bridge. The carbon steel, acting as a sacrificial anode, was later removed by electrochemical etching in a 41 wt% solution of nitric acid. Although support structures are not commonly implemented within DED technologies, in certain cases involving complex geometries similar to the bridge design, they offer the support for large overhangs, reducing thermal stress distortions as well as providing

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thermal dissipating pathways for minimizing on high temperature gradients [43]. Furthermore, DED technologies of new builds that have become strongly bonded during the initial deposited layer typically require removal from a build plate (substrate). In most cases, post-processing requires electron discharge machining (EDM) or laser cutting to remove this initial layer [33]. This task is also labor intensive and time consuming. However unique the properties of DED and PBF technologies are, PBF is restricted from being a multi-material technique, therefore, exhausting measures are typically required to remove powder and support structures before acquiring further post-processing treatment. Similar to the sacrificial anode investigated by Hildreth et al. [30], Lefky and Zucker [43] developed two novel approaches for dissolving support structures of metal PBF parts. The first approach utilized direct dissolution, as shown in Fig. 48.3, which electrochemically dissolves the supporting structures, though this technique was found to be nonselective as part dimensional accuracy became affected during the dissolving stage. The second approach incorporated a sensitizing agent during the post-processing annealing stage, which decreased the chemical stability between 100 and 200 μm of the component’s surface. The etching agent was then applied, where anodic corrosion would occur on the sensitized surface of the ~150 μm thick support structures. It is worthwhile noting, while the underlying component material was cathodic protected, only a maximum of 100 μm was removed from its surface. Research undertaken by Lefky and Zucker [43] as well as Junk and Schröder [34] demonstrated that both dissolution processes significantly decreased the surface roughness, although further research is required for exploring techniques to improve time and potential control over direct dissolution techniques. In addition, the chemicals used are hazardous to

Electrolyte solution

DC power supply Widened gap

Cathode

Cathode

Tank

Dissolved material

Fig. 48.3 Anodic dissolution

Anode (workpiece)

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Post-processing for Additive Manufactured Metal Parts: A Brief Introduction

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health, which create further handling and containment restrictions, effectively reducing the overall efficacy of the postprocess. Therefore, further chemical solutions that are less harmful in nature require further investigation. Nonetheless, this novel approach replaced a conventional machining process at least threefold by simplifying the post-processing of metal PBF components.

parts, the combined effect of high furnace temperatures and pressures improves part densification by accelerating the material diffusion rate and shrinking the internal porosities [50]. However, these temperatures are kept below the melting point, which enhances the isotropic material properties of a fine grain size microstructure. Four different part categories can be considered as being suitable for HIP:

Hot Isostatic Pressing and Heat Treatment There are several post-processing techniques that are to be decided based on the defects and/or modification enhancements that deliver a part for end use. Heat treatments are known for reducing residual stresses, improving mechanical properties, and changing the microstructure of metal components. Techniques such as annealing have been widely applied to AM components [6]. A stress relief cycle can typically include the raising of the AM part to the annealing temperature followed by a cooling cycle before a further heating cycle and quenching. The heat treatment process can then be followed by hot isostatic pressing (HIP) [14]. HIP is identified as the healing process for PM AM parts. In comparison to a conventional process such as casting, forging, and machining, PM HIP offers alternative benefits which can reduce or exclude further necessary steps to the AM workflow. This involves minimizing surface roughness, densifying defects of internal porosities, as well as improving mechanical and microstructural properties [1, 11, 22]. This technology is well recognized in industries featuring aggressive working environments, including oil and gas, aerospace, transportation, nuclear, and energy. The term isostatic refers to Pascal’s principle, whereby, the pressure (typically argon) is transmitted equally in all directions to provide isotropic properties with 100% densification of the work piece – refer to Fig. 48.4. During processing of stainless steel or superalloy

• Simple shapes that may be further machined • Near-net-shapes (NNS) which may require less additional machining operations • Complex net-shapes (CNS) which eliminate machining from the operation allowing for more designer flexibility • Composite material parts which can lead to increase bonding and/or improve functioning behavior

Top closure

Furnace

High pressure cylinder

Heating coils Water cooling jacket

Pressurised gas

Complex net-shaped workpiece

Insulation

Thermocouple Stage Bottom closure Vacuum line

Electric line Gas pressure inlet (argon)

Fig. 48.4 Hot isostatic pressing

Each considered component involves different HIP controls which can be simulated via computational modeling. This minimizes the risk of part over shrinkage as well as reducing machining time, especially when optimizing the more complex geometries. Due to typical internal porosities and cavities within the bulk material, densification is the primary aim. Typical modifications involve closing internal porosities and cavities, which inevitably influence the fatigue life of the part. The closed pores are described as internal pores, which have been engulfed within its material bulk during the process build. An open pore or near-surface pore, however, is exposed at the surface due to the cause of surface defects. HIP of the as-built part has been proven highly effective in closing cavities and internal pores, reducing the overall porosity to a minimum [57]. However, during high heat cycles, the open pores may infiltrate deeper into the material surface, which predominantly leaves surface defects known as notches. Therefore, additional processing operations are typically required, including machining, heat treatment, finish grinding, and/or surface treatment. Although the experimental work from Ref. [57] used a Laser-based Powder Bed Fusion (L-PBF) process, the as-build is equally susceptible to this type of behavior for all metal AM parts. In addition, the yield strength of as-built parts has been proven to decrease after HIP post-processing [38]. However, it is important to note that the thermal histories are found to be significantly different between PBF and DED processes, which are influenced by the processing conditions. The comparative study was designed to investigate the impact of HIP postprocessing on AM Ti-6Al-4V fabricated by laser DED and electron beam (EB)-DED. Both as-builts are shown to experience a loss in yield strength, though laser DED experiences a significant decrease in yield strength in comparison to EB-DED after HIP post-processing. It is relevant to note that a difference in heat inputs from both AM processes influences the chemical

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composition and microstructural changes of the TI-6Al-4V alloy. Initially, the laser-DED as-built was analyzed with greater yield strength than EB-PBF; however, the changes in composition diversified the solid solution strengthening as a result. This effectively altered the alpha (α)-lath structures during AM processing, leading to an increased coarsened α-lath thickness which impacted the Hall-Petch hardening [26] (altering the grain structure to improve the strength of the material). The discovery of larger coarser α-lath structures lowered the strengths for each as-built, L-DED as-built being significantly affected due to the vulnerability of the existing large course α-lath structure. Build geometry and scanning strategy can control these conditions due to the thermal influence on microstructure. Nonetheless, Keist et al. [38] determined that the L-DED was found to be the most influenced by HIP. The typical surface roughness achieved from post HIP considerably improved at 6–15 μm Ra.

Surface Finishing Within the open literature, an unresolved challenge for AM is surface finishing. For this reason, an overbuilt layer is required to meet the manufacturer’s surface finish, specified geometry, and mechanical requirements before being removed. An example being the limited feature size resolution available from the AM machine that prevents consistent surface accuracy. Therefore, the layer-by-layer process is required in most cases to overbuild the CAD component; as a result, the desired geometry is machined in a way that is subtractive to its intentional geometry to achieve consistent surface quality. Flynn et al. [21] point out that the finishing of metal AM parts can be categorized into three mechanisms: (i) machining and mechanical conversion, (ii) thermal processing, and (iii) chemical and electrochemical processing. With respect to the three mechanisms, utilizing a machining method to remove unwanted features of the as-build surface has been proven the most effective method in reducing the surface roughness. For example, a DED process is capable of producing ~15 μm (Ra); additionally, the average roughness can be reduced to 0.2–0.4 μm after subtractive milling, turning, or grinding [55]. These typical machining practices can provide an aesthetically pleasing shiny surface finish; however, achieving this surface finish requires the removal of several layers of the deposited materials. Furthermore, observing the as-built surface from its high peak to valley height and its irregular deformities, this surface is dissimilar to a conventional surface, i.e., a forged component. In this case, intuition developed from conventional subtractive manufacturing shows no comparison to the surface of an AM part. Additionally, most typical materials made from AM are commonly difficult-to-machine materials [2], creating more challenging concerns for tool life and feasibility from early burnouts.

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Low levels of porosity within the bulk or subsurface structure contribute to the sensitivity of the machining tool, which promotes the effect of unwanted chatter. In this case, a microscopic interrupted cut is most likely affected, resulting on tool life deficiency as well as the cutting precision on required specific tolerancing [27]. While machining can remove unwanted surface features and defects, it may also expose subsurface defects. As a result of this, the machining operation has many flaws and unknowns with AM. However, the hybrid process is an interesting topic for research. An example involving the use of a hybrid-AM machining process, utilizing an interlayer machining technique synergistic to the layer deposit, helps overcome residual stresses and improves geometric accuracy [62]. Further research has been reported in this area [55, 58]. A wide variety of cutting tool designs can also be adopted, all depending on the as-built part roughness and the required surface finishing. Furthermore, parameters such as the speed and feed rates also consider the adequate achievements for specific surface finish. For example, OSG USA Inc. has developed endmills for milling as-built rough surfaces, while focusing on the avoidance of chatter as well as optimizing on geometry accuracies and cost effectiveness. Multiple flute styles are now being featured on the market to help resolve these issues, while increasing tool life longevity. However, the contrasts of tooling design on AM have not been publicized in the open literature. Electropolishing, also known as electrochemical polishing, anodic polishing, or electrolytic polishing, is a finishing process that removes material from a metal or alloy based on anodic dissolution process (see Fig. 48.3) [28, 69]. Since electropolishing is a complicated process including electricity and chemical reaction, it is influenced by many process factors, such as current density, temperature, electrolyte types, and workpiece rotation. Electropolishing has been applied to as-build Ti-6Al-4V test specimens which had average surface roughness values in the range of 3.93–22.68 μm (Ra) – attributed to different build orientations [49]. The addition of post electropolishing (EP) was later investigated. Results showed as much as a 92% reduction in surface roughness, as the surface quality was improved to 1–3 μm Ra.

Surface Modification The modification of surface properties or surface engineering has been in existence for decades [45]. Sectors such as the automotive, aerospace, medical, and electronics have applied it to parts to either enhance performance or to ensure a longer operating life. In AM, surface modification has attracted significant attention as a means of overcoming limitations inherent in as built components such as open pores, surface cracks, and high surface roughness. The application of surface modification techniques increases the possibilities for

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Post-processing for Additive Manufactured Metal Parts: A Brief Introduction

additional component functionality of an AM component. In addition, surface modification can also lead to enhanced mechanical properties such as improved fatigue life which may not exist from the as-built part. Other properties which may be improved by modifying the surface topography include surface wettability, oleophobicity, hydrophobicity, friction, and lubricant retention [45, 56]. Modifying the component surface allows its function to behave more resiliently within a hostile environment with retrospect to the initial as-built function. A wide range of surface modification processes exist, which can be broadly categorized as mechanical, chemical, and thermal. In addition, there are a number of techniques which rely on vibrational forces to modify the surface. Table 48.1 provides a summary of the various techniques. Mechanical machining processes such as grinding and milling are well established and are primarily used to ensure the dimensions of the finished AM part are within specification [12, 13, 29, 39, 40]. As the various machining processes are well understood, they are also used to ensure the desired surface finish is also achieved based on parameters such as feed rate, depth of cut, and tool geometry. An alternative mechanical process is that of burnishing where plastic deformation is induced into the part by a tool sliding across the surface. Burnishing induces large compressive stresses into the part thus improving fatigue life and lowering the surface roughness [36, 73]. Shot peening is a well-established surface deformation process which can induce compressive residual stresses into the subsurface of materials to improve the fatigue life [35]. However, a side effect of the process is an increase in surface roughness which is more prevalent under higher peening pressures and led to a reduction in the fatigue life. In order

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to maximize the performance of the process, the peening parameters need to be carefully selected. Research reported by Trung et al. [68] indicated that the nucleation cracks or initiation cracks occurred in the subsurface at depths of 10–20 μm in the case of as-received samples but moved up to the free surface for the shot peened parts of low alloy steels. A well-established method now being utilized within AM is Laser Shock Peening (LSP). LSP is a mechanical work process intended for metallic materials [16] due to its high compressive magnitude as it tends to work on materials without the occurrence of cracks. The material interaction involves an intense amount of absorbed radiation, resulting in the ablation of a micrometric layer between the targeted material surface and the transparent deionized water [52]. The water acts as the confinement medium in its role. Alternatives to water include gels and acrylic-based medium which are dependent on the level of customization required for different applications (e.g., electrical components, biomedical parts, or localized areas which are sensitive to water). Nonetheless, the process introduces a compressive residual stress from the plasma striking the targeted surface area. The utilization of the pulsed laser beam causes localized high-pressure shockwaves within the surface, adjusting the surface microstructure as well as its surface texture [48]. Thereafter, the repetitiveness of the short laser pulses induces high stress effects, resulting in varying degrees of plastic deformation. Within AM, the application of LSP leads to the closing of pores and densification which can result in improved part performance. Furthermore, grain refinement, surface hardening, and surface texture modification are also achievable from LSP. Figure 48.5 illustrates the principle of the LSP process in a schematic form. LSP differs from shot

Table 48.1 In-situ measurement “modules” available from AM machine manufacturers and measurement specialists AM process EBPBF L-PBF

DED

Machine manufacturer Arcam

“Module” name LayerQam™

Failure mode monitored Porosity

Concept Laser

QM melt pool

Melt pool monitoring

EOS Acronity 3D

n/a n/a

Renishaw

InfiniAM

DEMCON

LCC 100

Unknown Melt pool monitoring Temperature across build Build temperature and pressure Melt pool monitoring

DM3D technology Promotec Stratonics

DMD closed-loop feedback system PM7000 ThemraViz system

Melt pool monitoring and build height Melt pool monitoring Malte pool temperature

Parameter altered n/a Laser power n/a n/a n/a Laser power Laser power n/a Laser power

Equipment Camera High-speed CMOS camera Camera High-speed CMOS camera 2X infrared-range photodiode Plasma-range photodiode 2X infrared-range photodiode Camera Dual-color pyrometer and three highspeed CCD cameras 1D photo detector Two-wavelength imaging pyrometer

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Fig. 48.5 A schematic LSP process Laser pulse

Confining layer inertial tampering

Plasma

Absorbing layer

Layer of water Absorbing layer

Pressure wave Workpiece

peening primarily with respect to the former imparting significantly deeper compressive residual stresses than shot peening. Although LSP has been an available technology since the 1960s, Sunder et al. highlighted that it has never realized the potential it deserves due to its focused specialism within the field of laser physics, mechanical and metallurgical engineering, coupled with the need for a skilled workforce in handling high-energy laser systems [65]. Many of the complex disciplines involved have believed to have impacted the unsupported growth of this novel process. LSP has recently showed potential for modifying AM parts that require the function of dynamic loading conditions and/or are exposed to extreme environments given its ability to increase surface hardness and remove near-surface cracks and voids which are detrimental to the performance of the material for specific applications [37, 65]. The typical stress development within the material is said to improve the wear, fatigue life, stress corrosion cracking, and intergranular corrosion performance of the AM part [46]. Implementing LSP by inducing a controlled measure of compressive residual stress into the layers of the as-build is considered a novel solution to enhancing performance, eliminating many of the post-processing steps, therefore, minimizing the post AM processes. Most typical surface modifications of a metal AM part have been overlooked to enhance corrosion resistance, cyclic fatigue, chemical stability, wear performance, as well as improving the aesthetical appearance [7]. Another popular trend being explored is laser remelting, typically known as laser polishing, which is made achievable as the laser beam

scans the surface of the part to reduce the high roughness count. The roughness peaks are melted into the valleys and cavities, levelling out the unwanted asperities on the surface for a smoother result. Wenhui Yu, Xuelei Tian, et al. [9] emphasized that the laser remelting process may be another approach to enhancing the density of Selective Laser Melting (SLM) parts. Their investigation discovered a porosity of about 0.77% for all specimens without laser remelting, which was reduced to 0.036% porous for specimens that adopted laser remelting. This was made achievable when parameters were selected properly. Witkin et al. [70] investigated post-surface chemically accelerated vibratory finishing to improve the high cyclic fatigue (HCF) performance of SLM and EBM specimens. The literature suggests smoothing the rough surface of an AM part will improve the fatigue life [15, 60]. However, Witkin et al. [70] described surface roughness as an undistinguished measurement parameter for fatigue performance, since hidden defects below the surface can lead to the early stages of fatigue failure. In conclusion, the fatiguelimiting features where the fatigue cracks initiated similar elastic stress concentration or stress intensity to that of the as-built. Nevertheless, HCF was improved for the EBM specimens via chemically accelerated vibratory finishing even though only slight smoothing of the surface took effect. The research of post-processing and surface functionality on fatigue performance is yet evidently unclear. Ma et al. [47] introduced a novel processing technique, Ultrasonic Nanocrystal Surface Modification (UNSM), which was initially targeted at nickel-titanium (Ni-Ti)

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Post-processing for Additive Manufactured Metal Parts: A Brief Introduction

implants. Ni-Ti parts fabricated through the AM route are prone to the potential release of toxic Ni ions which are associated with poor surface finish and high surface porosity. Through the simultaneous ultrasonic striking and burnishing, UNSM significantly improved the surface finish and decreased surface porosity. The synergistic effect of better surface finish, lower subsurface porosity, and a hardened surface layer resulted in higher wear and corrosion resistance. The technique was later applied and optimized by Kim et al. [40] to DED stainless steel 316L.

Inspection and Testing Inspection and testing are nondestructive geometric validations that require the use of different instruments for Geometric Dimensional and Tolerancing (GD&T) analysis [42]. GD&T is a design tool that uses symbolic language for production engineers to correspond with design engineers to fully capture the designer’s intent. Although principles from the dimensional tolerancing scheme have been focused on traditional methods for more than 100 years, the principles are still unclear for AM due to the number of inconsistencies and uncertainties that generate from each part design. A function of post surface finishing is to correct part distortion and enhance the surface quality. During this practice, the processing must conform to the part specifications, which are the primary standard of focus with respect to the International Organization for Standardization (ISO) and the American Society for Testing and Materials (ASTM). Until 2016, ASTM F42 and ISO TC 261 developed a new framework that would better standardize AM part development [4]. This new standards development plan is considered a living document that will be reviewed and updated on specifications concerning AM processes, testing methods, quality parameters, design guidelines, etc., to pursue this universal set of AM standards. Testing methods obtained from ISO 17296-3 [41] are specified to meet application-specific standards for industries such as aerospace, medical, energy, automotive, etc., to better qualify a part for production. A comprehensive review of the various standards for AM was carried out previously by the author [10]. Many styles of inspection are available to validate part quality including nondestructive testing techniques such as eddy current testing, magnetic particle inspection, ultrasonic testing, and visual inspection which are simply utilized to detect and characterize flaws within the surface of the metallic AM parts [17]. However, there is a lack of understanding of the soundness of modified surfaces of AM materials and their measurement for standardization before becoming end-use ready. It is a large concern for the production warranty, which must be formally addressed. To date, the integrity of powder fused metal AM parts is incapable of achieving what a traditional subtractive manufacturing process can [44].

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X-ray computed tomography (XCT) has, over recent years [63, 66], become a viable tool for both measurement and inspection in industrial applications and, specifically, AM. XCT has found uses from reverse engineering for AM to internal defect detection and measurement. For internal features, the focus has been on the measurement of density and pores as well as the study of pore morphology and distribution. This has now become a well-established primary technique for AM parts. In addition to porosity measurements, XCT is also widely used as general dimensional metrology tool replacing, in some applications, the coordinate measuring machine. This is more common with complex AM parts where accessibility issues and line-of-sight can be challenging. Integrated metrology solutions have also seen rapid development leading to improved process control and increased confidence in the as-built part [63]. Table 48.1, based on the work by Everton et al. [19] and expanded on by the authors, highlights a number of the commercially available metrology modules for AM machines.

48.3

Conclusions

It is recognized that the manufacturers’ ability to adapt to the customers’ requirements has never been as comprehensive – partially due to the unconstrained flexibility offered to the designer. In many cases, AM demonstrates many advantages over more conventional processes; however, the large-scale production of finished parts is still not established, and for many, post-processing is necessary, resulting in additional time and cost. Post-process selection can be quite challenging with the need to consider a plethora of factors such as end-use application, material composition, processing parameters, scalability, geometric complexity, as well as cost and the overall energy required to fulfil the process. AM postprocessing still faces many challenges before reaching its full potential; hence, the drive towards R&D for new technology and material development, the key element at the beginning of any great technology.

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J. Smith and D. Butler

Jonathan Smith is a PhD research student in the Department of Design, Manufacturing, and Engineering Management at the University of Strathclyde. His thesis focuses on metal additive manufacturing, identifying design characteristics, and correlating surface features to generate functional surfaces.

David Butler is a Professor of Sustainable Manufacturing in the Department of Design, Manufacturing, and Engineering Management at the University of Strathclyde. His research interests include novel manufacturing processes, the economics of manufacturing, and the circular economy. He has published over 100 journal and conference papers.

Post-processing Methods for Additive Manufactured Parts

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Dimitris Mourtzis and Panagiotis Stavropoulos

Contents

Abstract

49.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 833

49.2 49.2.1 49.2.2 49.2.3 49.2.4 49.2.5 49.2.6 49.2.7 49.2.8

Additive Manufacturing Methods . . . . . . . . . . . . . . . . . . . . . . Vat Photopolymerization Processes . . . . . . . . . . . . . . . . . . . . . . Powder Bed Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Directed Energy Deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Binder Jetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material Extrusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material Jetting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sheet Lamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Correlation Between Part Material and Process Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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49.3.1 49.3.2 49.3.3 49.3.4

Additive Manufacturing Quality Related Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Void Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anisotropic Microstructure and Mechanical Properties . . . Divergence Between Design and Execution . . . . . . . . . . . . . Layer-by-Layer Appearance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

838 838 838 839 840

49.4 49.4.1 49.4.2

Metallic Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 841 Post-processing Needs in Metal AM . . . . . . . . . . . . . . . . . . . . . 841 Classification of Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 842

49.5 49.5.1 49.5.2

Nonmetallic Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 846 Post-processing Needs in Nonmetal AM . . . . . . . . . . . . . . . . . 846 Classification of Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 846

49.6

Flexibility-Related Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 849

49.7

Time–Cost Related Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 849

49.8

Image Processing Assisted Tools for Post-processing Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 850

49.9

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 850

49.3

834 834 835 835 836 836 837 837

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 851

Despite the numerous benefits of additive manufacturing (AM), drawbacks like poor surface quality, dimensional accuracy, and internal stresses imply that AM-related techniques can rarely produce ready-to-use parts out of the machine. More often than not, AM parts need to be further processed regardless of their material in order to obtain a complete finished part or product. Post-processing refers to any type of processing of the part following its removal from the AM machine. Post-processing methods can be classified either based on the type of process (mechanical, chemical, and thermal), or the function of it (support removal, dimensional accuracy improvement, surface quality improvement, mechanical properties improvement, and additional features creation). Post-processing and related processes must be considered during the design of the AM manufactured product, thereby taking into account the material to be used, the technology, and machine to manufacture the product. This chapter aims to present the most popular post-processing techniques along with their benefits and applications. Moreover, a classification of post-processing techniques is performed according to their type, function, and material application. Keywords

Additive manufacturing · Post-processing · Post-treatment · Hybrid manufacturing · Flexibility · Accuracy · Surface quality · 3D scanning

49.1

D. Mourtzis (*) · P. Stavropoulos Department of Mechanical Engineering and Aeronautics, Laboratory for Manufacturing Systems and Automation (LMS), University of Patras, Patras, Greece e-mail: [email protected]; [email protected]

Introduction

Additive manufacturing (AM) is defined as the process of joining materials for the production of objects, made of 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies [2]. AM has gained significant popularity over the last decades, as a result of the

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_49

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extensive research and industrial developments that have been pursued during this period. First and foremost, it has widened its application spectrum from being utilized just for prototyping purposes, into being one of the most promising new technologies for manufacturing fully functional, high value products [28]. Moreover, the capabilities of AM regarding the materials that can be processed have been significantly enhanced; AM used to be restricted in processing polymers, with only a few lab-scale examples of machinery that could process other materials. In contrast, nowadays, metal AM technologies are delivering a significant breakthrough in terms of flexibility and potential for repair and remanufacturing [99], which can be utilized by numerous industries. The popularity of AM has been documented in the market, since the AM market has been growing at a compound annual growth rate of 20.9% from 2014 to 2020 [102]. Some indicative industries that are exploiting the benefits of AM are aerospace, automotive, and energy. Moreover, a significant field where AM has a wide application potential is manufacturing of biomedical components. The high interest of these industries in AM stems from a number of competitive advantages of AM. AM enables them to produce highly complex designs and employ techniques such as topology optimization and generative design. Moreover, exotic, high added-value materials, such as nickel-based alloys, titanium alloys, and ceramics, can be utilized and multi-material components can be produced. All of these benefits come without increasing their production cost to unacceptable levels, as it would happen with conventional manufacturing technologies, such as casting and machining. However, the adoption of AM in a wide industrial environment has been slightly hindered, despite the proven benefits. The new requirements that AM introduces in terms of design, process planning, safety, and integration, as well as the new skills that the workforce should acquire to adopt AM safely and successfully are key factors that have slowed down the adoption process [85, 89]. Although many industrial sectors are now less reluctant to adopt AM in their production, there are still issues that prevent the full integration of AM machines in a production line, rather than them being standalone entities in the shop floor of a manufacturer [87]. One of the biggest issues is related to the inability of AM to produce parts that will comply with the requirements of the corresponding industries. These requirements can be related to the geometrical accuracy of the parts, the surface roughness, and the mechanical properties of the component. In terms of geometrical accuracy, the nature of AM does not enable to produce a component that will exactly match the nominal CAD. Effects, such as shrinkage of the part during its cooling phase, varying dimensions of the track thickness and height in deposition-based processes, over- and underdeposition resulting from poor process parameter selection,

D. Mourtzis and P. Stavropoulos

etc., impair the accuracy of the manufactured component. Even with conservative process parameters and utilization of the most accurate AM processes, such as powder bed fusion, the required tolerances for high-value parts, such as aerospace components, cannot be achieved. Regarding surface roughness, its magnitude is in the order of tens up to a few hundreds of microns [28], which is inacceptable for applications in automotive and aerospace industries, where submicron surface quality is desired, such as in mating surfaces between different engine components (e.g., bearing housings). Finally, AM produced parts might exhibit anisotropic material properties, a high level of residual stress, and undesirable microstructure [73]. Considering the aforementioned, it is evident that the postprocessing of a component that has been produced with AM is a prerequisite so that it can have applicability in certain industries. Post-processing refers to any type of processing of the part following its removal from the AM machine. In this chapter, different post-processing methods are presented and classified based on their type, function, and material application. Their benefits and drawbacks are presented, as well as their role, in increasing the quality of a part built with AM. Finally, issues related to cost and flexibility are discussed, followed by a presentation of image processing tools that can aid in the optimization of the process chain, which includes AM, followed by a post-processing method.

49.2

Additive Manufacturing Methods

AM technologies have emerged in a wide range of variations, with their main differences being related to the way that layers are deposited on the material, the operating principle, and the materials that can be processed. Each method has in turn different benefits, drawbacks, and challenges, as well as applications or industrial sectors that it serves. As a result, the post-processing methods that usually accompany each AM technology are driven by the unique characteristics that each AM process has. In this section, an overview of the different AM technologies is provided to the reader, also linked with the core challenges of each technology that have to be considered, when selecting a post-processing method. Towards this purpose, the classification of AM processes follows, based on their process mechanism, as presented by Bikas et al. [4] in their work.

49.2.1 Vat Photopolymerization Processes The materials that are processed with Vat Photopolymerization (VPP) processes are liquid, radiation-curable resins, or photopolymers. These materials react when exposed to electromagnetic radiation, mainly in the ultraviolet range. This exposure

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Post-processing Methods for Additive Manufactured Parts

triggers a chemical reaction, called photopolymerization, which is responsible for the solidification of the material. The challenge related to VPP is the structural integrity of the produced components, which is related to the limitation of the process in the use of photopolymerizable materials. More specifically, the impact strength and durability of these materials are inferior to those of thermoplastics that are produced with injection molding, while the aging of the materials degrades their mechanical properties [28]. To this end, postcuring of the parts with UV radiation is often employed, with the aim of optimization of their structural integrity. Moreover, another issue is related to the process mechanism. Since the material is in liquid form before it is processed, it provides no support to the built volume, as opposed to powder bed processes, which in turn leads to the need for support structures, in places where overhanging geometries must be built. These support structures need to be removed after the part is finished, introducing a necessary post-processing step. Figure 49.1 provides an overview of the process mechanism of VPP.

Curing device Vat

Curing beam

Built part Build platform

Liquid photopolymer

835

49.2.2 Powder Bed Fusion Powder bed fusion (PBF) is a process group, in which multiple fusion mechanisms can be employed, namely solid-state sintering, chemically induced sintering, liquid phase sintering, or full melting [39, 40]. Moreover, the energy source in PBF can vary between a laser-based energy source and an electron beam energy source. PBF processes can be used to process both metallic, as well as nonmetallic materials, such as polymers. The main issue of this process is related to the physical phenomena that govern it. The powder is sintered or melted and then solidified and cooled at room temperature. Also, the energy source that scans the part for the formation of each layer reheats the previous layers as well, generating high thermal gradients within the build direction of the part. These two phenomena result in high residual stresses and warping of the part, which introduces metrological deviations, compared to the nominal CAD [88]. Thermal treatment is often used for post-processing of parts, whose structural properties are of utmost importance. Since the process uses powdered material, this powder might be enclosed in cavities of the built component, or trapped in the internal volume of the component, in case it is manufactured hollow, for weight reduction purposes. This introduces an additional post-processing step, which is related to the removal of the excess powder of the workpiece. Careful cleaning of the part is also significant for the safety of the people that come in contact with it, since metal powder can be harmful for a person that might accidentally inhale it. Figure 49.2 presents a schematic of the PBF process.

49.2.3 Directed Energy Deposition Fig. 49.1 Vat Photopolymerization process schematic

Directed energy deposition (DED) processes enable the manufacturing of components by melting the material as it

Fig. 49.2 PBF process schematic

Scanner Laser source Leveling roller Powder supply system Powder feeder piston

Laser beam Melt pool Powder bed Built part Build platform piston

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is deposited onto the substrate. The material that is deposited can be either in powder or in wire form, each one having its advantages and drawbacks. Suitable work materials are polymers, ceramics, and metal matrix composites; however, DED processes usually utilize metal powders. Similarly to PBF, parts that are manufactured by DED suffer from high residual stress and warping during their cool down, requiring thermal treatment after their production, in many cases. Moreover, parts that are manufactured with DED exhibit poor surface quality and metrological accuracy, also compared to parts manufactured with PBF, while presenting phenomena of over- or under-deposition, if suboptimal process parameters are utilized. As a result, post-processing needs to be employed in order to address these issues. In Fig. 49.3, an overview of the DED process is provided.

BJ, the material is stored in a powder bed and the binder is sprayed on it, in order to bond the particles together, as well as providing interlayer fusion. Both metallic and nonmetallic powders can be used and the binder can be water- or polymerbased. A necessary post-processing step, similar to the PBF process, is the thorough removal of the remaining powder from the manufactured part. The main issue that is observed in parts that are manufactured with BJ is related to their structural integrity. In order to optimize their mechanical properties, the infiltration of the part might be required after it is manufactured. Also, for metal parts, it is required to perform a thermal treatment after the part is finished, so that the binder evaporates, and the material is sintered. Figure 49.4 outlines the working principles of a typical BJ machine.

49.2.5 Material Extrusion 49.2.4 Binder Jetting The process mechanism of binder jetting (BJ) has some similar characteristics to the process mechanism of PBF. In

Powder delivery

Laser beam

Deposition head

Shielding gas

Deposited track

Melt pool

Building platform

Built part

Fig. 49.3 DED process schematic

The most common variant of material extrusion is fused deposition modelling (FDM), which is one of the most popular AM processes, as it is not limited to industrial applications. In FDM, the material, usually stored in the form of a filament, is deposited in a semi-molten state through a deposition nozzle to build the part, in a layer-by-layer fashion, as shown in Fig. 49.5. The materials that are utilized in FDM are mostly polymers. The main issues of the FDM process are related to the process nature. The layer thickness and height, together with other process parameters, such as scanning speed, play a crucial role in the quality of the printed part. Dimensional inaccuracy, warping of the part, and poor aesthetic appearance of the external surfaces are common problems with components manufactured with FDM, leading to the need for an additional post-processing step. Also, FDM, being a deposition-based process, is limited when it comes to overhanging geometries. To this end, support structures are printed to enable the production of said geometries. These

Fig. 49.4 Schematic of BJ process Leveling roller Powder supply system Powder feeder piston

Inkjet head Binder jet Powder bed Built part Build platform piston

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Post-processing Methods for Additive Manufactured Parts

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Inkjet head UV light

Filament supply Deposition nozzle Deposited track Built part Building platform

Filament cartridge Rollers Heated material

UV beam Photopolymer jet Built part Building platform

Fig. 49.5 FDM process schematic

support structures have to be removed from the part after it is finished, introducing an additional post-processing step.

49.2.6 Material Jetting Material jetting (MJ) is one of the earliest AM variants, initially evolving from inkjet printing. In MJ, photosensitive polymers, which are heated to lower their viscosity and optimize the printing process, are sprayed and cured with the use of a UV light, through the photopolymerization phenomenon, a process mechanism similar to VPP. Figure 49.6 provides an overview of the process mechanism. MJ has similar issues related to the structural integrity of the manufactured components like VPP. Moreover, support structures are always required in MJ, introducing an additional post-processing step to remove them from the part.

49.2.7 Sheet Lamination Sheet lamination builds the part layer-by-layer by introducing sheets, which have the geometry of the cross-section of the part to be manufactured, on top of each other, and bonding them. The bonding techniques can be broken down to (a) gluing or adhesive bonding, (b) ultrasonic welding, (c) thermal bonding, and (d) clamping. The first two are the most popular methods with a wider range of use and will be further discussed in this study.

Gluing or Adhesive Bonding The commercial name of this process group is called Laminated Object Manufacturing (LOM). LOM is also one of the earliest AM processes to be commercialized. It can utilize sheets of any material that can be cut precisely using laserbased or mechanical material removal processes; however, paper has been the material that was mostly utilized for LOM,

Fig. 49.6 MJ process schematic

making it very convenient to acquire as bulk material. In LOM, the layer of the material is positioned on the cutting table and bonded with the previous layer, using adhesive. Then, the layer is cut with a knife or laser to get the desired geometry and the next layer is introduced. This process is repeated until the final part is built. The main benefit of LOM is that parts with complex internal geometries can be created (Fig. 49.7).

Ultrasonic Welding Ultrasonic additive manufacturing (UAM), also called ultrasonic consolidation (UC), combines lamination of metal sheets with machining. The metal sheets are bonded together with the use of a rotating sonotrode that travels along the length of the workpiece, oscillating at high frequency. The material removal process can take place either in between the placement of each layer or when every layer has been laminated, depending on the geometry of the part. The main benefits of UAM are that complex internal geometries can be created and that the energy consumption is significantly lower than other metal AM processes, since the material does not need to be melted. However, the mechanical properties of the final component are inferior. Being integrated directly with a subtractive manufacturing process, UAM does not require post-processing to tackle any dimensional accuracy or surface quality challenges. However, defects on the interface between the layers are present very often, requiring posttreatment to alleviate them (Fig. 49.8).

49.2.8 Correlation Between Part Material and Process Mechanism Table 49.1 provides an overview of the materials that can be processed, as well as their state, according to each AM process mechanism. Moreover, indicative values of the

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Scanner

Laser source

Current layer

Processed layer

Current layer

Excess material take-up roll

Film supply roll

Building platform

Fig. 49.7 LOM process schematic

Sonotrode

linked with the respective AM processes and required postprocessing methods, which will be discussed in detail in Sects. 49.4 and 49.5.

Metal foil, fed by automatic feeder Metal base plate Building platform

Fig. 49.8 UAM process schematic

dimensional accuracy and surface quality that can be achieved by each process type are provided.

49.3

Additive Manufacturing Quality Related Challenges

As mentioned in the introduction, AM still suffers from several challenges that make AM-built components unsuitable for applications, where high structural integrity, tight tolerances, or an aesthetically pleasant external surface are of utmost importance. However, for most industrial sectors, one of those three aspects is key requirements in their production. As a result, industry and academia have put a lot of effort in identifying and accurately modelling the mechanisms of AM that introduce these challenges, while investigating methods to minimize their impact through optimization and control of the process [86]. In the context of the selection of post-processing methods in various AM processes, it is important to identify and classify the key quality-related challenges that impact AM parts. Therefore, in this section, brief overview of some key challenges related to quality will be provided. These challenges can then be

49.3.1 Void Formation During AM, voids might be formed inside the part, which are a function of part orientation, process parameters, or how the design was input to the machine. Microstructural voids are created during the build of the part. They need to be minimized to limit their adverse effect on mechanical properties and to ensure the consistency of AM parts. The void types that might be observed in a component produced by AM can be classified into three groups: (a) porosities, which are mainly spherical and less than 100 μm, as shown in Fig. 49.9; (b) melting-related defects, that are characterized by irregular shape; and (c) cracks, which are the result of rapid cooling, sharp thermal gradients, and thermal stresses [82], which are depicted in Fig. 49.10. A common area for the formation of voids is in the interface between each individual track that is deposited or sintered, as a result of air that is trapped in the material during the formation of the track. Voids are detrimental for the structural integrity of metal AM parts, which are mainly used in load bearing application. To this end, post-processing methods, such as thermal treatment, have to be employed in order to alleviate these defects and ensure a homogeneous microstructure.

49.3.2 Anisotropic Microstructure and Mechanical Properties Another challenge related to the quality of an AM part is the layer-by-layer approach and cohesion. That leads to the

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Table 49.1 Correlation between material and process mechanism

Process mechanism Photopolymerization Laser sintering Laser melting Electron beam melting Material extrusion Binder jetting Adhesive bonding Mechanical bonding

Materials Photosensitive polymers, resins Metals, polymers, ceramics Metals, polymers, ceramics Metals Polymers Metals, polymers, ceramics All materials Metals

Bulk material state Liquid

Surface roughness (μm Ra) ~0.1–0.35

Dimensional accuracy (μm) 140

References [15]

Powder

~6–45

50

[27]

Powder, wire Powder, wire Filament Powder

~2–16

100

[27]

~20–50

130

[24, 37]

~3–10 ~1–15

130 85

[4] [97]

Sheet Sheet

~20–30 Governed by the material removal process

200 Governed by the material removal process

[4]

Moreover, during the printing process, a phenomenon of high fluctuation of part temperature is present, as the part is built layer by layer. This phenomenon is more prominent in metallic materials, since they possess a much higher melting point compared to polymers. As a result, residual stresses can be observed at the part that must be relieved, in order to avoid premature failure of the component during its service life. By utilizing heat treatment methods, it is possible to significantly reduce the residual stresses of the component.

Z

200 Pm

Fig. 49.9 Pore formation in AlSi10Mg processed by SLM [82]

formation of an anisotropic microstructure of the created part (different mechanical properties in different directions). It is common for AM machines to also have different resolution along different orthogonal axes. Typically, the vertical build axis is responsible for the layer thickness, and this would be of a lower resolution compared with the two axes in the build plane. The critical angle, to position a part in the build chamber, compared to the build direction can be experimentally or theoretically calculated, to provide optimal results for a specified geometry. In a case study of Oliver et al. [60], experiments on coupons manufactured by Selective Laser Sintering (SLS) were conducted, which were then tested in tension using full field Digital Image Correlation (DIC) to measure strain. Figure 49.11 shows how the stress at failure varied with build orientation.

49.3.3 Divergence Between Design and Execution In order to enable full integration of AM in modern production facilities of high-value industries, it is important that the part that is built will satisfy extremely tight geometrical tolerances, which can be in the range of tenths of a micron for applications, such as aerospace. There are three main factors that affect the ability of AM to create parts as close to the nominal CAD as possible. Accuracy is a function of the system’s capability to control the motion of the material melting across the entire build envelope. So, the accuracy depends on the process parameters and varies between the different AM methods. Some processes are capable of submicron tolerances, whereas others have around 1 mm. A general rule is that the larger the build volume and the faster the build speed, the worse the accuracy. Resolution of the system is one more parameter. Resolution refers to the smallest tolerance the machine can theoretically reproduce. That can translate to some constant conditions of the system like the step of the motors, the

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a)

b)

c)

Region 1

Region 2 Solidification cracking

Liquation cracking

Liquation cracking

Laves Laves

20 Pm

20 Pm

20 Pm

Fig. 49.10 Hot cracking during deposition of IN718 [10]

0

15

30

80

75

z 90

architecture of the whole system, the size of the deposition nozzle, and the minimum movement that the controller of the machine can dictate. The final width of the track determines the resolution that can be achieved in the AM process [91]. Repeatability indicates the equipment’s ability to produce parts with constant dimensions, time after time. Just as resolution does not translate into accuracy, accuracy does not translate into repeatability. Some systems have good accuracy but poor repeatability. The divergence between design and execution for each AM process is heavily impacted by the process mechanism, as shown in the previous section. To this end, post-processing should be considered, more often than not, in order to tackle this issue. Material removal processes (mechanical, electrothermal, or laser-based) are usually integrated either in the same machine tool or within the AM production workflow to address this challenge.

x y

True stress at failure (MPa)

b)

Build direction

a)

45

Fig. 49.11 Tensile coupons orientation (a) and variation of true stress at failure as a function of build orientation (b) [60]

60

55

50

45 0

15 30 45 60 75 90 Build orientation (degrees)

49.3.4 Layer-by-Layer Appearance The appearance of a final part is half of a successful manufacturing process and the reasons can be related to the aesthetic quality of the part or other performance aspects. The stair-stepping or staircase effect is a common issue in the layered manufacturing processes (Fig. 49.11). The surface quality is not ideal because of the existence of vertical edges, which is a result of the basic principle of AM that dictates that the part is built using a layer-by-layer approach. This issue depends mainly on the layer thickness and the build direction and, although it can be significantly reduced through the optimization of process parameters, it is very difficult to eliminate, especially in deposition based processes (DED, FDM), where this effect is more prominent (Fig. 49.12). The following figure provides an overview of the impact of each of the aforementioned quality-related challenges in

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Post-processing Methods for Additive Manufactured Parts

the various categories of additive manufacturing technologies (Fig. 49.13).

49.4

Metallic Materials

In this section, post-processing methods for metallic parts, manufactured by AM, will be presented in more detail and classified according to the type that each method belongs to. The benefits and drawbacks of the different methods are going to be discussed as well, aiming to provide a clear overview to the reader regarding the different possibilities.

49.4.1 Post-processing Needs in Metal AM The post-processing requirements for metallic components, produced by AM, are a result that is dependent on several factors, related to the nature of the AM processes and the application that the part is intended to serve. First of all, every metal AM process utilizes a baseplate, upon which the part is built. This baseplate is manufactured from a metallic material that is compatible with the material that is being processed.

Build layers (actual surface)

Original CAD model

Build direction

Fig. 49.12 Schematic representation of the staircase effect

Challenges AM process

Void formation

841

The first layers of the part that is being manufactured will always be fused with the baseplate, since the melt pools penetrate it as well. As a result, the removal of the base plate is a post-processing need that is always existent in AM. Powder bed processes, such as SLS, utilize the powder bed to support any overhanging geometries that exist in upper layers. On the other hand, deposition-based processes, such as Laser Metal Deposition (LMD), do not have this possibility. Especially in three-axis systems, where non-vertical deposition is not possible, the manufacturability of parts with several overhanging geometries is very limited [45, 46]. In order to tackle this issue, support structures can be designed and deposited during the fabrication of the part. However, these structures have to be removed when the deposition is finished, usually through a material removal process. In many powder bed processes (especially when nonmetallic materials are considered), the powder bed acts as a supporting structure during the build. However, the powder that aids in supporting the built part is a challenge to be dealt with after the part is finished. Thorough cleaning of the powder is crucial to ensure the safety of equipment and operators. Powder particles should be carefully contained, since they may damage machinery that does not have appropriate ingress protection. Moreover, powder can be harmful to humans, in case it enters the respiratory system, and, depending on the material, the powder can create combustible dust. It is evident that careful cleaning and handling of the powder is of utmost importance [71]. Especially in the case that the part has deep cavities or internal channels, extra caution should be taken during post-processing. Other challenges in metal AM processes are related to the accuracy of the parts that are manufactured. In general, the accuracy that a machine tool can achieve is related to its

Anisotropic microstructure and mechanical properties

Divergence between design and execution

Layer-by-layer appearance

Vat Photopolymerization Powder bed fusion Directed energy deposition Binder jetting Material extrusion Sheet lamination Low/zero impact Moderate impact High impact

Fig. 49.13 Impact of quality-related challenges to AM technologies

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positioning system, as well as the process instabilities, which might induce additional inaccuracies. Modern AM machine tools are built with sophisticated positioning systems, which provide high resolution, with minimal impact on part accuracy. The accuracy reduction of the AM processes is a result of the process mechanisms, which are related to melting and solidification of the part. Most machine tools, which utilize optimized process parameters for the respective material, can achieve an accuracy in the range of 0.1 mm [100]. Achieving high accuracy in metal AM is a significant challenge in general, but the main issue is the accuracy along the build axis (usually the Z-axis of the part). DED processes suffer mostly in this scenario, since over- and under-deposition are the two main challenges that need to be tackled [74] by optimizing process parameters and employing control systems to ensure melt pool stability and uniform deposition. In many applications where tight tolerances are required for the functional components, this accuracy level is not enough, leading to the need for post-processing of the components built by AM. Moreover, the dimensional accuracy of a part can also be hindered by the warping phenomenon that is present during the cooling of the part, after the AM process [75], especially in thin-walled components. To compensate for this phenomenon, parts are built with excess material, which is removed during the post-processing stage, in order to achieve the nominal geometry. Another aspect related to the quality of the part is its surface roughness. Industrial case studies [68] have shown that the surface roughness that can be achieved is in the order of tenths of micrometers, which indicates that for applications requiring mirror-like surface finish (in the submicron range) additional post-processing steps are required. Finally, there are aspects related to the performance of parts manufactured by AM, which have to be resolved with the use of post-processing methods. As mentioned in the previous section, cracking and void formation might impair the structural integrity of the part, leading to reduced mechanical properties of an AM-built component, compared to a wrought one. Another challenge that reduces the performance of the part is the presence of significant residual stresses at the end of the AM process, which is a result of inhomogeneous microstructure evolution and nonuniform phase transformations [7]. Tensile residual stresses, which are mainly observed in the outer layers of the part, can be detrimental to its performance, reducing its fatigue life significantly [64]. Another aspect of the material that dictates its performance is its corrosion resistance. Parts that are manufactured for aerospace or energy applications will spend their service life in corrosive environments; it is evident that examining the corrosion behavior of AM-built parts is also crucial. This topic has been well investigated in literature, although further work is necessary to extract confident results [38]. It has been reported that the powder

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characteristics [8, 9], purging gas [1], and process parameters [44] can have an impact on the corrosion behavior of the AM-built part. Thermal treatment (e.g., sintering, annealing, hot isostatic pressing, etc.) or mechanical post-processing (e.g., milling, grinding, etc.) techniques can be employed to tackle the aforementioned challenges and enhance the performance of the components that are manufactured by AM. An overview of those techniques is presented in the following section and a visual representation of the different post-processing methods for metal AM, as well as the AM technologies and quality-related challenges that they apply to is provided in Table 49.2.

49.4.2 Classification of Methods Mechanical Material Removal Processes A group of methods that are utilized very often for postprocessing of the components that are manufactured by AM are material removal processes. Material removal processes can be used for a variety of purposes during post-processing, but the main applications are related to the removal of support structures, in processes like DED, and the processing of the built part, in order to achieve high quality in terms of dimensional accuracy and surface finish. The material removal processes that are mostly utilized are milling and turning. These two processes have become very popular, since a lot of academic research and industrial developments have been pursued on this topic, leading to the emergence of hybrid manufacturing. Hybrid manufacturing is a term that is commonly used for the combination of an AM process with a material removal process (milling, turning) in a single machine tool. Globally acknowledged machine tool builders, such as DMG Mori [16] and Mazak [53], have launched hybrid manufacturing machine tools in the market, while CAM software developers, such as Siemens [81] and SprutCAM [84], provide functionalities in their software that enable simultaneous programming of the additive and subtractive manufacturing processes, to serve hybrid manufacturing machine tools. Being one of the most fundamental post-processing methods for AM, hybrid manufacturing has also received a lot of interest and research in topics that are related to its optimization [47], modelling [29], and sustainability analysis [62]. Moreover, in a wide range of applications, the utilization of abrasive media has been observed. Abrasive flow machining has been utilized in numerous applications, especially in parts where internal channels and freeform surfaces are key characteristics [42] to achieve very high surface quality, close to the submicron range [65]. Figure 49.14 outlines the two types of mechanical material removal processes that are utilized for AM postprocessing (Fig. 49.15).

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843

Table 49.2 Classification of post-processing methods for metal AM

Type

AM post-processing methods for metallic materials Mechanical material removal

Name of post-processing method

AM process

Purpose

Electro-thermal AM process

Purpose

Chemical AM process

Laser-based

Purpose

AM process

Purpose

Thermal AM process

Purpose

Cleaning AM process

Purpose

Milling - Turning

EDM

Etching

Ablation

Sintering

Manual

Abrasive flow machining

Electrospark deposition

Chemical brightening

Laser shock peening

Quenching and tempering

Automatic powder removal

Grinding - Polishing

Electro-strengthening

Chemical machining

Laser polishing

Annealing

Ultrasonic

Hot isostatic pressing

CO2 blast

Induction heating

Ageing

49 Legend AM process

PBF

DED

BJ

LOM

UAM

Purpose

Dimensional accuracy

Surface quality

Fatigue performance

Residual stress

Corrosion behavior

Fig. 49.14 Mechanical material removal process schematic

Abrasion processes

Support/ powder removal

Cutting processes Motor

Nozzle

Cutting tool

Abrasive flow

Material chips

Processed surface

Machined surface

Workpiece

Workpiece

Fig. 49.15 Part manufactured by DED (a) and post-processed with milling (b). (Adapted from Meiners et al. [54])

Electrothermal Processes In this section, the electric or electrothermal post-processing methods that are used to increase the quality of AM parts will be discussed. The processes that are considered as electrothermal are those that utilize electricity to generate a heat flow towards the part, in order to alter its state, either geometrical or microstructural. Figure 49.16 outlines the working principle of electrothermal processes. Electrical Discharge Machining (EDM) is also one post-processing method that is utilized for the post-processing of AM parts. The main use of EDM for AM parts post-processing is related to the removal of the base plate, upon which the part is built, through wire EDM.

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Fig. 49.16 Electrothermal processes schematic

Electrode (cathode)

Power source

–

Workpiece (anode)

+

Electric arc Molten material

Dielectric fluid

The advantages of EDM that make it the most suitable candidate for this application is that this process can be completed with very high accuracy, materials with low machinability can be processed and the cost of the base plate removal is minimal, compared to milling and turning. For these reasons, there have been commercial systems developed that are dedicated to base plate removal with wire EDM [59]. Apart from that, EDM can also be used for finishing parts that are built by AM, since it can achieve very high surface quality in the submicron range [104]. Using EDM instead of mechanical material removal processes is advantageous when the features of the part that need to be processed are small, so the process time will not be extremely high, and very high precision and surface quality are required. Furthermore, there are other electrothermal processes that have been utilized. Electrospark deposition, which uses a consumable electrode that is deposited as a thin coating on the workpiece, has been successfully utilized to eliminate the effect of powder adhesion on the surface of components manufactured by PBF [19]. Moreover, electrostrengthening has been shown to reduce the residual stress and increase the nano-hardness of Ti6Al4V samples manufactured by PBF [98]. Finally, Induction Heating (IH) has been utilized for post-processing of the deposited material directly after its solidification, in a hybrid DED-IH approach, which has enabled the increase of the productivity of DED, while maintaining proper layer adhesion [14].

Chemical Processes Chemical processes can also be utilized to post-process AM parts, as they require fewer tooling compared to other processes, such as EDM or milling, and can provide very high part quality, especially related to the part surface. Moreover, materials with very low machinability can be chemically processed, which is another advantage of this process group. Chemical processes can provide a very clean part surface and can effectively process very complex geometries,

which is the reason that are preferred for post-processing of AM parts that are meant to serve medical applications, as shown below. Adhering powder particles, which can be detrimental in medical applications, since the loosening of these particles can put the patient’s health at risk, can be effectively removed through chemical etching with hydrogen peroxide and hydrochloric acid [93]. Moreover, chemical etching can be utilized to eliminate the need for the use of an expendable template for the fabrication of porous structures for medical applications. AM can be combined with etching to manufacture porous structures with a pore size in the micrometer range [51]. Chemical etching can also be utilized to create a complex surface morphology in the micrometer range in medical implants prepared by AM, in order to maximize the adhesion between the implant and the bone tissue [21]. Finally, chemical machining can be combined with chemical brightening to enhance the dimensional accuracy and surface quality of samples that are manufactured by AM [78]. Figure 49.17 presents the key components involved in a chemical process.

Laser-Based Processes Laser-based post-processing of AM parts is a widely used method since it can provide very high integration and industrialization potential. Utilizing two kinds of laser sources with different power and spot diameter characteristics can provide a flexible solution that can be easily integrated in machine tools. For this reason, the research on laser-based post-processing methods has been very wide, as indicated below. A process that has been utilized for post-processing of AM produced components is laser ablation. Laser ablation uses a pulsed laser to heat the material through radiation, up to the point that it evaporates or sublimates [41]. Although the material removal rates with laser ablation are low, compared to other material removal processes (e.g., machining), very accurate parts with high surface quality can be manufactured [31], which makes it an interesting applicant for integration

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Nozzles Chemical jet Photoresist mask Workpiece

Heat treatment furnace Elevated temperature chamber Workpiece

Fig. 49.17 Chemical processes schematic

Fig. 49.19 Thermal processes schematic

Laser head

Laser beam Shielding gas Molten material Workpiece

Fig. 49.18 Laser-based processes schematic

into AM machine tools, without the need of a structure that can compensate for the high loads that are present during machining. Moreover, laser-based processes are utilized for improvement of the surface quality and structural integrity of the AM produced components. For example, laser polishing remelts a layer of material at a 50–200 μm depth, which flows into the existing valleys of the surface of the part, and can effectively reduce the surface roughness and eliminate the effect of powder adhesion [36]. Finally, laser shock peening can effectively improve the structural integrity of the part by inducing compressive residual stresses, which in turn enhance the fatigue strength of the part that can be very compromised in AM-built parts [30]. Figure 49.18 provides an overview of the working principles of laser-based processes that are used for AM postprocessing.

Thermal Processes Thermal processes are one of the most popular postprocessing methods for AM parts, since the main challenges of these parts are their anisotropic microstructure and mechanical properties. Thermal treatment is a wellestablished method that can resolve these issues. BJ processes present a particular need for thermal treatment after their build, since the metal powder with the binder have

reduced mechanical properties than a melted and solidified equivalent, making the parts made with BJ unsuitable for some applications. To this end, sintering of the parts that are manufactured by BJ is performed at an elevated temperature to evaporate the binder and increase the density of the metal part, thus reducing porosity and enhancing its structural integrity [92]. Moreover, various heat treatment methods have been employed to enhance the mechanical properties of AM-built components. Such methods include ageing [103], hot isostatic pressing [33], annealing [33], and quenching and tempering [96]. It has been proven that different heat treatment methods can have a significant effect on enhancing the properties of the AM part. It can contribute towards the chemical homogenization of the part [72], reducing the anisotropic microstructure to an extent. Moreover, thermal processes, such as hot isostatic pressing, can effectively close pores that are generated during the AM process, which can be detrimental to the fatigue performance of the AM part [17]. Also, through heat treatment, the residual stresses of the part can be relieved [18], the ductility can be increased [13], while the homogenization of the microstructure can promote crack propagation resistance [76]. All of these factors contribute to a better fatigue performance of the part, compared to the as-built state, which is a crucial attribute for most engineering applications. Finally, the changes in the phases that compose the microstructure of the material, which take place during heat treatment, have been found to be beneficial for the corrosion resistance of steel [8, 9], titanium [20], and nickel-based [50] alloys. Figure 49.19 presents the schematic of a typical furnace that is used for thermal processing of AM parts.

Cleaning Processes As mentioned in the previous sections, cleaning of a part after the AM process is very important and, apart from the aesthetic result, the powder removal through part cleaning is an important aspect related to safety. To this end, manual cleaning of the components that are made by AM is a postprocessing step that always has to be taken when the part is

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built. To increase the productivity and quality of this step, several industrial solutions have been developed. Solukon [83] has developed machines that can enable automatic powder removal and clean AM parts, without human intervention. Also, cleaning of the part in an ultrasonic bath has also be employed for powder and support removal [61]. Finally, blasting of AM components with a cryogenic CO2 jet has been employed to clean the surface of the part and remove any adhered powder [48].

49.5

Nonmetallic Materials

An additional material type that can be utilized in AM processes is the nonmetallic materials. Polymers and ceramics are included in this category as types of materials that have different microstructure from metallic ones. Depending on the desired result for the part that is produced by AM, post-processing might be required also for nonmetallic parts.

49.5.1 Post-processing Needs in Nonmetal AM Most of the needs for post-processing are similar to the ones for metallic parts, which have been described in the previous section. The produced part should be as close to the nominal CAD model as possible, with a very good surface and without residual stresses. Also, all the supports that may assist during the building process of the component must be removed in a non-harmful way. Unlike metal parts, machining is rarely a solution to achieve the final geometry for a polymer part. As the traditional injection molding process produces plastic parts with higher accuracy than AM, it is a significant challenge for plastic AM processes to reach the same accuracy level. So, these parts are manufactured in their net-shape and mainly painting or metallization are some of the post-processing operations that take place for aesthetic reasons [56]. Due to the nature and process mechanism of some AM processes like SLS and FDM, surface roughness is very high. So, surface finishing should be performed to achieve higher quality. Most of the current techniques have low flexibility, large cycle times, or the incorporation of abrasives into the component [5]. Many AM technologies require generating support structures to sustain the manufactured part so that it does not collapse under its own weight. The generation of additional support structures (also called scaffolding) has to be removed by post-processing. For a given design, support structures directly add cost to the AM process and engineers aim to minimize required supports typically by optimizing the build direction. However, selecting the build direction is

usually influenced by other parameters. At least for the foreseeable future, support structures are inevitable for manufacturing many industrial parts across numerous AM processes [57]. As mentioned previously, the AM process parameters have a decisive role at the mechanical properties. During the process, thermally induced residual stresses are generated inside the material that can impair the strength of the produced part [69]. Also, this is due to the layers in the build direction being partially bonded. The quality of the bonding of the layers defines the material continuity [67]. Finally, since polymer parts, which form a large portion of the nonmetallic applications in AM, are not utilized for load bearing structures but for decorative purposes, the aesthetic results are of utmost importance. The layer-by-layer appearance of parts, especially in FDM, can have a negative effect on the aesthetics of the part. An overview of the post-processing techniques for nonmetal AM is presented in the following section and a visual representation of the different post-processing methods for nonmetal AM, as well as the AM technologies and qualityrelated challenges that they apply to is provided in Table 49.3.

49.5.2 Classification of Methods Material Removal Processes Removal of support structures and surface finish improvement is also an issue in nonmetal AM processes. Support removal is mainly achieved manually, since the strength of the material is not very high, or with chemical processes; however, material removal processes are utilized for finishing the part after its build. Sandblasting is one of the most commonly used methods in industry, since it is readily available for most manufacturers [56]. Vibratory grinding is used to improve the Ra value of SLS part from 11 to 2 μm as the removed material has a thickness lower than 0.1 mm. Mostly ceramic components have been investigated and different process times were tested for the best result [77]. Grinding and polishing can be utilized for applications that require very high surface quality, such as components that are manufactured for optical applications [35], yielding surface roughness results in the nanometer range. Hot Cutter Machining (HCM) has also been employed during the part build in the FDM process. The machining process is performed layer by layer, so the resulting surface roughness is at the order of magnitude of 0.3 μm but the surface for HCM process must be flat [63]. Also, micro-machining is used to improve the surface roughness and the dimensional accuracy of ceramic parts. Finally, sanding is employed as a post-processing method, mainly in small lot applications in job-shops, where surface quality is the primary concern.

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Table 49.3 Classification of post-processing methods for nonmetallic AM

Name of post-processing method

Type

AM post-processing methods for non-metallic materials Mechanical material Chemical Thermal Electrical Radiation-based Laser-based Cleaning removal AM process Purpose AM process Purpose AM process Purpose AM process Purpose AM process Purpose AM process Purpose AM process Purpose Etching Sintering Electroplating UV curving Laser-based polishing Manual Sandblasting

Grinding

Chemical vapor smoothing

Annealing

Hot cutter machining

Painting

Warm isostatic pressing

Sanding

Resin coating

Microwave processing Laser micro-machining

Ultrasonic

Air blasting

Micro-machining

Legend AM process

PBF

ME

BJ

MJ

VPP

Purpose

Dimensional accuracy

Surface quality

Mechanical properties

Porosity

Aesthetic enhancement

Chemical Processes Chemical post-processing is a nonconventional method with respect to the nature of them. Firstly, a chemical bath with acetone, ester, and chloride solvents is a technique of a chemical post-processing treatment. This method has been tested in ABS parts manufactured with FDM. The result is a great improvement in surface finish with a sacrifice at the outer dimensions of the sample. Ra values are between 2 and 4 μm without the help of a human hand [25] have been achieved. Chemical vapor smoothing has started gaining industrial attention as a promising solution for ABS parts, since its effectiveness in providing a high surface quality has been proven [26]. Finally, painting and coating with epoxy resin are also employed in polymer parts, in order to enhance their appearance. Thermal Processes Thermal processes are also utilized for post-processing of nonmetallic parts, mainly targeting to improve their structural integrity. Sintering techniques can be utilized to obtain highdensity ceramic or polymer parts. By performing pressure infiltration on the part prior to the sintering process, it is possible to further enhance its effect [79]. Usually finer ceramic particles can achieve better properties after sintering, compared to polymers [105]. MJ and BJ processes often exploit sintering as a post-processing strategy. Thermal annealing is also a potential method to enhance the mechanical properties of AM components. Thermal annealing has been used to modify the microstructure of polymer AM parts,

49 Support/ powder removal

with the result of improved mechanical properties. A significant increase in fracture toughness has been observed for ABS parts that are isothermally annealed at temperatures under 200  C for different durations [32]. Thermal annealing has also been proven to increase the thermal conductivity of polymer parts [67]. Finally, warm isostatic pressing or pressure infiltration can improve the density of polymer parts [79].

Electrical Processes Although electroplating is a widely used process, it is still not commonly utilized for nonmetallic parts that are produced by AM. However, there are some examples where this process has been utilized both for aesthetic and structural purposes, since nickel-coated plastics present a high strength-to-weight ratio [101]. The process mechanism in nonmetallic AM produced parts is slightly different from the conventional electroplating process. The required components for the process are an anode, which is the metal that will coat the part, a cathode, which is the actual workpiece, an electrolyte, and finally a power supply to provide the voltage. Positively charged ions can break metals down, resulting in the formation of a thin layer of coating on the surface of the part. Electroplating polymer materials like ABS is a special process. First, one layer of copper has to be deposited on the surface of the substrate before nickel can be electroplated on the copper. Strong acids are used to etch the surface, which are activated using nanoparticles of tin and palladium in order to provide a catalyst, because ABS is a very hydrophobic material.

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Radiation-Based Processes Radiation-based processes are also utilized for postprocessing nonmetallic AM parts. Their application is mainly related to the curing process of photopolymer materials. Curing is a post-processing operation that can improve the mechanical properties, sustainability, and the overall print quality [106]. The most common post-curing process is the ultraviolet chamber (Fig. 49.20), with many industrial solutions being launched in the market, which are dedicated to AM post-processing [23]. Microwave-based post-processing has also been introduced as a novel post-processing method for nonmetal AM parts. It has been observed that through this method the porosity of the parts can be effectively reduced. Positioning angle, post-curing time, and power level of the microwave radiation are the decisive factors affecting the final result [22]. Laser-Based Processes Laser-based polishing processes for AM polymer parts are being developed in the last years [43]. Apart from improving the surface quality, laser polishing can enhance the mechanical properties of a part. After a lot of passes with a high scanning speed, the material surface is heated up, until a constant surface temperature is reached, resulting in the melting of the outer surface. As a result of the melting and solidification of the outer surface, its roughness is improved.

In an indicative work, samples made by PA12 with SLS had an as-built surface roughness of 10.2 μm, which has been reduced to 0.61 μm via laser polishing. The process parameters that are used for laser polishing influence the smoothing effect [5]. Another laser-based application is laser micromachining, which can be used to create small and very accurate features in AM-built parts.

Cleaning Processes First of all, parts that are manufactured with powder-based processes (e.g., PBF) need to be cleaned from tiny polymeric particles that remain attached to their surface. Although sandblasting, which can be used for surface finishing, also helps in cleaning the part, when a part has holes with a small diameter, it cannot be cleaned by sandblasting so a pressurized airflow is used for the final cleaning. Unsintered power from small blind pockets is the hardest feature to be removed, because the sandblasting operation pushes the powder to the bottom of the pocket and compresses the granules [56]. Moreover, ultrasonic cleaning is utilized for nonmetallic AM post-processing as well (Fig. 49.21). Water-soluble polymers are developed (e.g., PVA that is used with PLA), which are used during printing for the support structures. As a result, the support can be easily removed in an ultrasonic cleaner, providing a consistent and high-quality result, with minimal need for human intervention [61].

Cleaning chamber

Curing tool Radiation

Workpiece

Workpiece

Water bath

Ultrasonic wave generator

Fig. 49.20 Radiation-based processes schematic

Fig. 49.21 Ultrasonic cleaning process schematic

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49.6

Flexibility-Related Issues

According to Chryssolouris [11], one of the key attributes that have to be considered when making decisions in manufacturing is flexibility. As such, it is important to consider the aspect of flexibility and its impact on the selection of post-processing methods and tools for AM parts. In a real industrial scenario, it would not be possible to incorporate all of the aforementioned post-processing methods and use the most optimal based on the part type. As a result, the flexibility of the post-processing tools that will be integrated in the manufacturing system that includes an AM machine has to be considered as well. Browne [6] has made a classification of the most significant flexibility types in a manufacturing system. In this section, the crucial considerations related to flexibility, which have to be taken into account when integrating post-processing in the AM workflow are discussed. Since different AM processes can deliver a diverse set of parts, any type of machinery that will be utilized for postprocessing of the AM components must have the ability to easily change to serve parts coming from different AM processes, with different sizes and complexity, requiring different setups. For example, milling is more flexible in this aspect compared to EDM and ablation in processing small and large features, with different kinds of geometries. This requirement corresponds to machine flexibility, as indicated by Browne. Moreover, the materials that can be processed by AM, as indicated in Sect. 49.2, covers a wide range from multiple metal alloys to polymers and ceramics. Thus, post-processing systems need to cover this range, in order to be flexible towards the diverse nature of AM parts. Cleaning and material removal processes are the most flexible in this aspect, while electrothermal processes are much more limited regarding the diversity of AM parts they can post-process. This requirement corresponds to process flexibility, as indicated by Browne. Another important aspect that has to be considered is the production volumes that are usually pursued with AM processes. On the one hand, metal AM has repair and remanufacturing as the key target sectors, while, on the other hand, nonmetallic AM is mainly used for small lot productions, due to the high flexibility and low productivity, compared to other methods (e.g., injection molding). As such, post-processing systems must also have this flexibility, since a small lot or even one-off production is very common in AM. This flexibility requirement is linked to the product flexibility, as indicated by Browne, which dictates that the system must be able to change to produce a new product set economically and quickly. Last but not least, the most important attribute that a postprocessing method must possess, to enable integration with AM in a single machine, is the ability for seamless interchange between AM and the post-processing method. This

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requirement corresponds to operation flexibility and, when achieved, enables the engineer to program complex process plans, including both processes, without significant effort on the process design and machine programming aspects. Only when this flexibility requirement is achieved, it is possible to fully exploit the benefits of each process that is involved in the process chain. For example, processes, such as milling or ablation, can be flexibly integrated in a machine, enabling the manufacturing of very complex internal and external features or multi-material parts, since interchangeability between AM and these processes can be easily achieved.

49.7

Time–Cost Related Issues

As it can be observed from Chryssolouris [11] that when making manufacturing-related decisions, it is also crucial to consider the time and cost that is involved with process selection. To this end, one must consider how the workflow of AM with the required post-processing steps for each specific case compares to traditional manufacturing processes. There are numerous studies that have been published on this topic. This section will focus mainly for green field manufacturing of parts, since in the context of repairing and remanufacturing, the utilization of AM has been proven to have significant advantages over traditional processing [99]. Along with the development of AM, as well as the introduction of metal AM processes, the developed cost models have evolved significantly, considering most of the aspects of the AM lifecycle, such as pre- and post-processing, redesign requirements, labor, machine costs, etc. [12]. Resource efficiency and the ability to effectively handle part and production complexity are two key aspects that AM excels in, while machine and tooling costs and process cycle time are proven disadvantages, when considering the potential cost benefit of implementing AM in a production line [66]. By examining most of the related studies, the consensus that is reached is that, at least with the current capabilities of AM, it should be preferred when lot sizes are small. On the other hand, when the lot sizes rise, traditional processes, such as injection molding [34] for nonmetallic materials and casting [94] for metallic materials still outperform AM in terms of process time and cost. It can be stated that one of the main aspects that a production engineer should consider, in order to decide if the implementation of AM would be effective for their specific production line, is the required flexibility of the line and the expected lot size. However, the direct comparison of a traditional process with AM is not enough on its own. It is also important to consider the way that AM can transform both the part that will be produced, as well as the production process itself. Intensive research on design for AM [45, 46] and its connection with design optimization tools, such as topology

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optimization [58], provide a unique opportunity to redesign a component for production with AM, by optimally exploiting its capabilities (complex freeform geometry fabrication, hollow structure fabrication, etc.). So, the redesign potentials have to also be considered in a cost analysis between AM and traditional processing, under a holistic scope that also includes the part value in the analysis. The capabilities of AM can exponentially increase the resource efficiency during manufacturing, while enabling the addition of features that increase the part value, with minimal penalty in the production cost. Even in cases where existing components that are parts of a larger assembly, which induces several design constraints, are redesigned, transforming to AM from conventional processing can still make sense from a time and cost aspect [3]. Finally, in order to optimally exploit the benefits of AM and effectively integrate the required postprocessing steps, it is important to develop hybrid process chains that will be backed up by structured decision-making and process planning methodologies [85, 89].

49.8

Image Processing Assisted Tools for Post-processing Operations

Post-processing of an AM part that is aiming to change is shape, for surface finish or dimensional accuracy purposes, requires most of the times to have information regarding the as-built shape of the part. This is especially important when complex shapes and tight tolerances are present, in order to program the toolpath of the machine that will execute the postprocessing operation (robot, machine tool, laser head). However, as it has been mentioned in the previous sections, the divergence from design to execution is a huge issue of AM, which implies that one cannot rely on the original CAD of the part and expect it to match with the as-built shape. Moreover, no analytical or finite element modelling approaches have successfully managed, up to now, to predict the material growth and the final shape of the part. Also, even the ones that can achieve a relatively high accuracy are too time consuming and computationally intensive to be implemented for large and complex parts. As a result, another method must be utilized to obtain the information related to the as-built shape of the part and use this information to generate the part program for the post-processing operation. 3D scanning is a tool that can support this task and, due to its latest developments that enable sufficient accuracy and resolution, has been very closely linked to AM, contributing to its post-processing operations. Laser- or optical-based 3D scanners are widely used to generate the point cloud of the shape of an AM part. Although 3D scanning has been the main tool for the acquisition of the part geometry, other methods, such as X-ray computed tomography [90], have been employed.

When the point cloud is obtained, the reconstruction of the part surface, the identification of corrective actions, and the programming of the toolpath have to take place. Several tools have been developed to enable the execution of these operations in a fast, accurate, and integrated fashion. After the point cloud of the part is generated, it is important to reconstruct the part surface so that noisy data and outliers are removed and that it can be utilized by CAD/CAM systems to identify the deviations from the nominal design and trigger corrective actions. In general, the most common approach is to use the point cloud to generate the geometry in the form of tessellated surfaces that can be imported to numerous kinds of software tools. There are several methods that have been employed to automate this task. A method that is commonly used in AM parts post-processing, as well as in general applications, is the Poisson surface reconstruction algorithm, which is based on constructing and solving iteratively Poisson partial differential equations, in order to generate the isosurfaces of the point cloud and ultimately reconstruct the part geometry [80]. Detection of surface boundaries and edge reconstruction with the use of the fast Fourier transform can also be employed to generate tessellated surfaces from point cloud data [55]. Also regiongrowing algorithms can be employed, which get the point cloud as input and, based on a seed surface and generate triangles on the boundaries of the existing interpolated surface, to provide a tessellated surface at the end of the algorithm [95]. Finally, spline approximation can be employed on the point cloud to generate the surface of the part [70]. Planning of the toolpath that the post-processing operation must follow requires two distinct steps. The first step is to identify the defects that exist on the AM part, compared to the original model, and the second step is to determine the way that the corrective actions should take place. The deviation map between the measured point cloud and the original CAD can be created and then local defects of the part can be identified [49]. The post-processing operation can then be planned by using conventional approaches, where the target geometry is defined by the 3D model and the geometry of the AM build component is considered as the stock for the postprocessing operations. However, some efforts on direct path planning from the point cloud of the part have been published in the literature [52].

49.9

Conclusions

In this chapter, the different AM methods have been briefly presented, focusing on the process mechanism of each method. The quality-related challenges of AM have been discussed and have been translated to post-processing needs for AM of metallic and nonmetallic materials. A classification of the post-processing methods based on the process

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mechanism of each method has been proposed, accompanied by the AM processes that each method is linked to, as well as the purpose of each post-processing method. A discussion of the flexibility and time–cost related issues indicated that integrating AM in a production line is not a straightforward task and requires careful examination of a diverse set of factors, in order to identify if AM will actually enhance production efficiency and quality for a specific case. Image processing assisted tools can aid the integration aspect and enable complex process chains to reach a high level of automation. It is evident that both the AM processes themselves and subsequently their post-processing steps are far from being considered fully mature. Even with established and wellstudied processes, such as milling, their utilization for AM post-processing induces new challenges that have to be addressed. However, it is safe to state that AM has a huge potential and with the current trend of research and development on AM that is observed, groundbreaking developments can be expected to be introduced in the following years, utilizing complex hybrid process chains with AM and postprocessing, reaching high automation levels.

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Dimitris Mourtzis is a professor in the Department of Mechanical Engineering and Aeronautics, Laboratory for Manufacturing Systems and Automation (LMS) of the University of Patras, Greece. He is an elected Fellow of the International Academy for Production Engineering (CIRP), Fellow of the International Federation of Automatic Control (IFAC) Manufacturing Modelling for Management and Control, Fellow of the International Federation of Information Processing IFIP Advances in Production Management Systems, and member of the American Society of Mechanical Engineers (ASME). His research mainly focuses in the area of manufacturing systems, automation, virtual and augmented reality in manufacturing, robotics, manufacturing processes, and engineering education though leading teaching factory initiates.

D. Mourtzis and P. Stavropoulos

Panagiotis Stavropoulos is an assistant professor in the Department of Mechanical Engineering and Aeronautics, Laboratory for Manufacturing Systems and Automation (LMS) of the University of Patras, Greece. He is a member of the Institution of Mechanical Engineers-IMEchE, registered as a Chartered Engineer the Engineering Council, member of the Virtual Research Laboratory for a Knowledge Community in Production – VRL-KciP – and member of NATO AVT-258 “Future of manufacturing for military applications.” His main research interests are focused in the field of conventional/nonconventional/micro manufacturing processes, sustainable manufacturing, CAD/RP/RM/ AM systems, and engineering education though teaching factory initiates.

Part VI Education and Training

EU Funded Projects for Qualification and Standards Requirements in Additive Manufacturing

50

Adelaide Almeida, Eurico Assunc¸a˜o, and Ana Beatriz Lopez

Contents 50.1 50.1.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 857 An Overview on Stakeholders, Standards Requirement and EU Funded Project Collaboration . . . . . . . . . . . . . . . . . . . 857

50.2

Identification of Skills Challenges in a Growing Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 859 Seven Goals Towards the AM European Skills Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 859

50.2.1 50.3 50.3.1

The European Observatory in AM . . . . . . . . . . . . . . . . . . . . 860 A Shared Vision and Collaborative Skills Solution . . . . . . 860

50.4 50.4.1

The International AM Qualification System . . . . . . . . . . 862 Harmonized Training Supported by a Robust Quality Assurance System and Aligned with Industrial Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 862

50.5 50.5.1

New Qualifications and AM Skills . . . . . . . . . . . . . . . . . . . . . 863 Address the Emergent and Short-Term Needs of the Workforce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 863

50.6

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 865

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 865

Abstract

In face of the increasing growth of Additive Manufacturing (AM) technologies and consequent requirements for new occupations, skills and knowledge for personnel working in this sector, the first International Additive Manufacturing Qualification System (IAMQS) was launched by EWF in 2018. The IAMQS covers Metal AM Qualifications for Operators, Designers, Supervisors and Engineers, implemented through international guidelines and robust quality assurance system to ensure a harmonized delivery of training in any country and/or region aligned with industrial requirements. The qualification system has been developed and implemented A. Almeida (*) · E. Assunção · A. B. Lopez European Federation for Welding, Joining and Cutting (EWF), Brussels, Belgium e-mail: [email protected]

through European-funded projects. Skills Strategy in Additive Manufacturing (SAM) project plays a key role in the consolidation of the System, bringing a comprehensive understanding of the appropriate AM skills-set and deliver them to industry through a network of European training centers. Keywords

Additive Manufacturing · International AM Qualification System · Industrial Requirements · Gap drivers · Skills Strategy in AM · New Qualifications and skills

50.1

Introduction

50.1.1 An Overview on Stakeholders, Standards Requirement and EU Funded Project Collaboration To face the lack of much needed skilled Additive Manufacturing (AM) professionals, EWF (European Federation for Welding Joining and cutting) launched the 1st International Professional Qualification System in Additive Manufacturing in 2018, in line with the ManuFUTURE Vision 2030 Strategy [1], making this a unique initiative of high relevance for the labor market, creating new qualification levels in AM. The International AM Qualification System (IAMQS) is based on knowledge and skills’ assessment and on a Quality Assurance System that ensures the recognition of the same qualification in all countries sharing the System. The AM Qualifications are developed and implemented based on a continuous search for innovative methods to improve AM personnel training and qualification, intercepting the needs, contents and paths for the new professional figures required by the industrial world. The training and qualifications were grounded on the work developed

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_50

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in the scope of three European Funded projects in the field of Additive Manufacturing, together with the respective partners from nine EU countries. The main Educational European Funded Projects supporting and involving in this activity are: • ADMIRE – Knowledge Alliance for Additive Manufacturing between Industry and Universities • CLLAIM – Creating Knowledge and Skills in Additive Manufacturing • SAM – Sector Skills Strategy in Additive Manufacturing ADMIRE project [2] aimed at bridging Universities, Research Centers and Companies working in AM through the development of an innovative European Metal AM Engineer Master’s Degree (MSc) course to reply to the urgent industrial need for highly qualified personnel in Metal AM Process Engineering and Metal AM Coordination. This MSc course and its specializations were designed in line with the lifelong learning approach to be implemented by Universities across Europe. The first European Metal AM Engineer MSc curriculum (Fig. 50.1), contains specializations in Metal AM Process Engineering and Metal AM Coordination, and was integrated as part of the IAMQS for the Advanced level in alignment with the European Qualifications Framework (EQF) level 6. Universities that wish to implement the partial of full MSc curriculum can be part of a consolidated enlarged

Market & industry

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used foc y tr us nd

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needs

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EU framework metal AM engineer qualification

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rm

Fig. 50.1 Features of the Metal AM Engineer master’s degree. (Courtesy of ADMIRE project)

European Network of AM stakeholders, where collaboration between different European Universities and between them and Companies for the implementation of the European Metal AM Engineer MSc curriculum is promoted. This collaboration can potentially increase professionals’ and students’ mobility and employability opportunities at European level. With help from a specialized team, Universities can evaluate their own capabilities (i.e., resources and field of expertise) and analyze how the MSc can be integrated on their own educational offer, in line with specific IAMQS requirements. CLLAIM project [3] aimed at creating create the first International Qualification System for Additive Manufacturing and defining the rules and operational procedures to guarantee the harmonized implementation of the System across Europe, inspired by the EWF Quality Assurance System. An innovative feature of the IAMQS was the process of Recognition of Prior Learning (RPL) allowing professionals to recognize and validate their prior knowledge and skills in AM. CLLAIM project main outcome was the development of training Guidelines for the Independent and Advanced levels of the Metal AM profiles (Fig. 50.2) in alignment with EQF levels 4 and 6, thus corresponding to Operators, Supervisors, Inspectors, and Designers for specific AM processes (such as Directed Energy Deposition for ARC and Laser Beam, Powder Bed Fusion ARC and Laser Beam). SAM, the Sector Skills Strategy in Additive Manufacturing Project [4] is The Blueprint for the Additive Manufacturing Sector aiming to tackle the current increasing labor market need for AM demands. The project is developing as an European Observatory in AM that is responsible for identifying and anticipating the right skills and deliver them to the Industry/Companies through a solid network of European Training Centers. The consortium is composed of 17 partners, encompassing industrial representatives from the sector, organizations involved in the fields of Vocational Education and Training (VET) and/or Higher Education (HE), and umbrella organizations. In collaboration with SAM, and previously in CLLAIM and ADMIRE projects, market searches to collect information on market needs and possible solutions for future workers and professionals already involved in AM sector have been conducted, validation workshops with experts from the Industry and Education were carried out, and European qualification pathways were developed. This systemic approach (Fig. 50.3), that encourages a close collaboration with major European AM companies and organizations to collect inputs from different sources in the creation of AM Qualification System, ensures Professional Profiles’ quality and transparency. These projects are interconnected to offer an easier progression within AM Qualifications, avoiding relearning, and to enhance opportunities for changing trainees’ career paths.

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Fig. 50.2 Metal AM qualifications profiles

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Fig. 50.3 Systematic approach for the identification and validation of needs. (Courtesy of EWF)

They offer advantages to Educational Systems by addressing emergent technologies easily integrated at a national level and designing individual learning pathways that are automatically recognized. The creation and implementation of the AM Qualification System, with the support of several organizations and partners, are thus of utmost relevance for the labor market as it reduces the hurdle of skills’ recognition and assures the

recognition and reliability of the awarded diploma by the Industry. The system also allows for a much-required upskilling in Metal AM Industry, preventing skills mismatches and provides to the workforce the opportunity to keep up with the advances of AM technology, while companies are able to cope with the challenges those advantages bring to their business opportunities. By assuring that the international implementation will follow the EWF Quality System rules and operating procedures, the quality of these new qualifications will be guaranteed. The strategy and methodology applied in the design of these qualifications (and future ones) within the IAMQS will be then detailed in this article.

50.2

Identification of Skills Challenges in a Growing Industry

50.2.1 Seven Goals Towards the AM European Skills Strategy The Wohlers Report (2019) [5] indicates that the AM market continues to rise, with more new companies using AM, more investment made, and a higher number of new and innovative products designed for AM being released to the market, a trend that is predicted to evolve in the upcoming years.

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Technology in AM is evolving at a much faster pace than the development of knowledge and skills that allow using it. This increasing growth in AM technology requires the definition of new professional profiles, skills and knowledge for personnel working in this sector. However, due to a fragmented training offer, which does not cover all levels of education, there is a lack of responses to those requirements and to AM labor market’s needs for skilled professionals. Already this year, the 3D Printing Trend Report 2021 [6] aiming to review the overall expected AM market growth, including the impact of COVID-19, reveals that 3D printing will continue growing 17% year-over-year in the next 3 years, pointing areas of high demand and barriers still faced by industry. The same report indicates that 19% of the barriers toward more AM applications is linked to the limited expertise of the personnel. Within this context, the SAM project undertook a stateof-the-art report on the Global and Societal Milestones [7], enabling to identifying key societal transformations that on a direct or indirect manner impact the AM sector and skills. In addition, the project consortium has implemented a forecast methodology characterized by a continuous market research to determine skills mismatches and gaps in the AM sector by deploying a set of online surveys and interviews with representatives from industry/employers in AM, research and technology centers, as well as training centers belonging both to academia and vocational, education and training. The forecast methodology applied in SAM is based on a continuous search for innovative methods to improve AM personnel training and qualification and to continuously update training and qualifications, intercepting the needs, contents, and paths for the new professional figures required by the international industrial world. Within this methodology, the gathered needs, gaps, and shortages are framed according to different scenarios: • Scenario 1: Real case, in which extent skills need to be addressed in less than 1 year. • Scenario 2: Short-term, how relevant skills / trends need to be addressed in the less than 3 years. • Scenario 3: Foresight scenarios, how relevant skills / trends need be addressed in the future, within the next 10 years. In parallel, other complementary activities are conducted using forecast methods, enabling to discuss on future AM applications, challenges and solutions to tackle AM skills needs. After collecting the data, their analysis is performed during dedicated workshops, thus defining the skills priorities and areas that needed further exploitation in the next stage of auscultation. The ultimate step of the forecast process

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consists in validating skills needs with external stakeholders during a validation workshop. The outcome of the combined state-of-the-art report and forecast process, enabled to defined seven key gap drivers (Fig. 50.4) which are the baseline of the European AM Skills Strategy Roadmap 2021 [8], namely: • Mismatch between industry needs and educational/training offer • Competition for skilled AM workers and lack of knowledge of AM from existing workers/students • Shortage of training centers, specially at Vocational Education and Training level, capable of delivering AM training (cost of the equipment/software, qualified personnel for delivering training) • Sector and process specific requirements for AM, that are also reflected on the qualifications of professionals • Fast evolving technology and industry • Lack of AM awareness among the younger generations • Necessity of more “infrastructures” for AM training Concrete solutions and feasible activities have been placed forward in SAM, and will continue after the project end, to allow the sector to adapt and reduce the potential negative impact. The Skills Strategy Roadmap is grounded in seven strategic objectives, which were defined to face up the previous gap drivers. Each individual objective translates into concrete activities, differentiated in Supporting Actions, which are general activities defined to address the objectives, and Implementing Activities, which are more concrete actions that need to be undertaken in order to achieve the expected results. The identified Sector Skills Strategy is grounded in the AM Observatory and the deployment of the IAMQS through a network of training providers, which is sustained by industry and by strong connection between a wide range of industrial sectors, which are applying AM in their activity or intend to do so (Fig. 50.5).

50.3

The European Observatory in AM

50.3.1 A Shared Vision and Collaborative Skills Solution The European Observatory in AM is responsible for implementing the forecast methodology in the AM sector, as well as manage the implementation of the IAMQS at transnational, national and regional levels supported by a network of experts in AM and stakeholders belonging to education, industry, civil society and government in Europe.

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Fig. 50.4 Gap drivers and strategic objectives of the AM skills strategy roadmap. (Courtesy of SAM project)

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50 Strengthen the collaboration between industry and training organizations Strategy

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The Observatory is putting in practice a methodology for a sustainable and continuous assessment of current and future skills needs in AM, providing real-time mapping and monitoring of AM industry needs. In terms of composition, the European Observatory in AM has two structuring councils: one for Qualifications (International AM Qualification Council – IAMQC) and one for Industry (Industrial AM Industry Council – IAMIC). Both councils result from the engagement of SAM project partners, associated partners and relevant stakeholders from different areas of the AM sector. The IAMQC is composed of a network of representative stakeholders that at national level, is responsible for the governance of education, training and qualification or certification in AM. This council is also responsible for deciding on updating or creating new Professional Profiles, Qualifications and/or Competence Units (CU), based on the validation of results from surveys, interviews, students feedback, engagement and feedback from national organizations and information on technological trends. The IAMQC also has

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the role of nominating Education Working Groups in order to revise or create Professional Profiles or Qualifications, thus based on the Industrial Council indications. For its turn, the IAMIC is composed of relevant organizations representing the industrial view and needs in AM, which includes the suppliers, original equipment manufacturers (OEMs), end-users, human resources companies, certification bodies and research organizations. This council will be responsible for the identification of new industrial requirements in terms of training, education, qualification, and certification based on market data, and for the establishment of priorities for the development of new products, according to different time frames (1 year: real case scenarios; 3 years: short-term scenarios, and 10 years: foresight scenarios). The IAMIC also has the role of nominating Industry Advisory Groups to collaborate with Education Working Groups during the validation of the industrial requirements, which will ultimately favor the updating of existing AM qualifications or development of new ones (of which the AM Observatory will have information),

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European network of training centres using the IAMQS

Creation of the European AM observatory International AM qualification system implementation & national roll out

European AM observatory is responsible for collecting and analysing data through a forecast methodology for the identification and anticipation of skills needs in the AM sector, as well as manage the implementation of an international qualification system for AM.

International AM qualification system is composed by a set of qualifications for different proficiency levels in the field of AM technologies, grounded in industry requirements and validated by experts. Within the system, a single syllabus for each level is defined, supported by a hamonized system for assessment and quality assurance, resulting in the same qualification being awarded independently from the country.

A network of training centres in AM is brought together, from both VET and HE, which are implementing the common trans-national curriculum. The training centres belonging to this network also share the same quality assurance standards in the assessment of learning outcomes, in accordance with the IAMQS training guidelines. The qualification of the AM workforce is possible through the upskilling (improving existing skills) and reskilling (training in new skills) of workers. The IAMQS uses a modular structure to design its qualifications and training programs. The outcome is that training guidelines can be used in a flexible way, aligned with the specific needs of users. The existing AM qualification system covers metal AM qualifications for operators, designers, supervisor, inspector, coordinator and engineers. More are to come namely for Polymers.

Fig. 50.5 Flagship activities foreseen in the sector skills strategy roadmap. (Courtesy of SAM project)

thus allowing them to be updated and to respond to these needs within periods of 1, 3, and 10 years.

50.4

The International AM Qualification System

50.4.1 Harmonized Training Supported by a Robust Quality Assurance System and Aligned with Industrial Requirements The IAMQS, managed by EWF was launched in 2018, being composed by a set of qualifications for different proficiency levels in the field of AM technologies, grounded in industry requirements and validated by experts. The System uses a modular structure composed by units for learning outcomes to describe the expected knowledge and skills to be acquired

by trainees after the successful completion of the training courses. Within the System, a single syllabus for each level is defined, supported by a harmonized system for assessment and Quality Assurance, resulting in the same International Qualification being awarded independently from the country. Currently, the IAMQS covers Metal AM Qualifications for Operators, Designers, Supervisor, and Engineers. Through SAM, the Qualification System is being consolidated and extended, meaning that the mentioned qualifications for Metal AM are being revised and new ones will be developed, including for different materials and processes, thus based on the industry needs identified. The use of harmonized Modular International Training Guidelines for the qualification of AM personnel has the added value of supporting the delivery of training in any country and/or region, underpinned by a Quality Assurance system and aligned with industrial needs. In terms of roll out at national and regional level, the guidelines can be used in a

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flexible way by the training providers relying on their own resources and most suitable learning approach as long as they comply with the recommended contact hours for each subjects and prove both technical and pedagogical capability as foreseen in the quality system. The methodological approach for design and review qualifications is based on the principles of functional analysis [9] which defines the occupational competencies and to set the boundaries between different occupations within AM Qualifications. It enables the operationalization of a cumulative system and individual learning pathways, where learners validate each Competence Unit independently and whereas such Competence Unit is part of several Qualifications, it is automatically recognized once it has been successfully completed. The IAMQS Qualifications are designed in a way that enhance and allow upskilling pathways, either within the same field of activity (such as among the specialized AM Operators), or among different specialization areas (such as AM Operators and AM Process Engineers). Similarly to the Structure of the Observed Learning Outcome (SOLO) Taxonomy [10] principles’ structure, the methodology for the design of upskilling qualifications encompasses the assignment of levels of increasing complexity in learners’ understanding of subjects. This means that the progression of levels is made from the lowest to the highest level in building blocks, where upon successful completion of the lowest levels, learners can start more complex levels ensuring the development of solid fundamental knowledge and skills of concepts and principles. This modular approach, using the building blocks, allows Manufacturing professionals to progress their knowledge, also their career, by obtaining new skills and knowledge inside the Qualifications System. The curricula designed for the IAMQS encompasses the definition of the following activities: • Competence Units organized in learning outcomes in terms of knowledge and skills, with a specific workload containing the minimum required or recommended contact hours (including theory, practice/laboratory hours); • Methods and tools for a harmonized assessment of the learning outcomes; • Minimum requirements for the necessary Materials (resources – activities, equipment, etc.). The implementation of first International Qualification System for Additive Manufacturing personnel is of outmost relevance for the labor market as it reduces the hurdle of skills’ recognition and assures the recognition and reliability of the awarded diploma by the Industry. International qualifications are also important in National, European and International perspectives as they promote common trust and

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cooperation at an operational level. By assuring that the international implementation will follow the EWF Quality System rules and operating procedures, the quality of these new qualifications will be guaranteed.

50.5

New Qualifications and AM Skills

50.5.1 Address the Emergent and Short-Term Needs of the Workforce Findings of the 1st round of auscultation to industry and research organizations in 2019 conducted in SAM, lead to the conclusion that Metals will continue to be required and that most required AM Professional Profiles are the Engineers for different processes followed by the Designer, which were already integrated in the IAMQS through the CLLAIM project. A such the European Observatory in AM, is keeping these Profiles and Qualification updated and is developing new European AM Skills for metals and polymers. The methodology used to design these qualifications (and future ones) is the same as described above, allowing a much-needed upskilling of professionals, preventing skills mismatches and provides to the workforce the opportunity to keep up with the advances of AM technology, while companies are able to cope with the challenges those advantages bring to their business opportunities. Four criteria were used to determine priorities to tackle the above-mentioned skills needs and gaps, which are: sectors relevance in alignment with ISO activities, urgency, impact on employability, and relevance toward raising awareness on AM. The new qualifications and skills addressed by the System, which cover the needs for the Real Case Scenario are highlighted in (Fig. 50.6) The AM Polymers Designer is the profile with the specific knowledge, skills, autonomy and responsibility to design AM solutions for the main Polymers Processes. His/her main tasks are: • Create part design solutions for AM polymer processes ensuring that: – The design considers AM benefits. – The part can be manufactured in a cost-effective and efficient way. – Post-processing can be applied. • Close polymer design proposals by verifying requirements for production, post-processing, quality control and process requirements with the project responsible, ensuring liaison with other technical areas to sign the drawings. • Contribute to projects in cooperation with AM Team and costumers.

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Fig. 50.6 New qualifications and skills integrated in the IAMQS. (Courtesy of SAM project) New qualifications and AM skills

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The Business for AM course is intended for Non-technological Managers/Managers, Non-AM specialists. The objective of the course is to capacitate trainees toward: • Taking decisions on the implementation of AM in the company • Assessing the economic viability of the implementation The Certification, Qualification, & Standardization (CQS) in Additive Manufacturing Course is intended for all interested in Certification and Standardization topics. The objective of the course is to capacitate trainees toward:

• Distinguish the main differences associated to each concept • Recognize the standards applicable to additive manufacturing • Identify how CQS can prevent the specific risks and implications related with AM implementation The Sustainability for AM Course is intended to raise awareness among all AM Profiles on the importance of sustainability applied to AM. Within this course, the participants are expected to gain the following skills: • Spot ideas and opportunities for alternative, more sustainable and simple solutions for daily AM activities

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• Name advantages and disadvantages of AM sustainability topics • Identify cases and/or examples for which AM may lead to more sustainable products • Take the initiative to make suggestions for more sustainable choices along the AM product life cycle Finally, the Metal AM Binder Jetting Process CU, was designed for two proficiency levels (Independent and Advanced), and will be integrated within the specialization for the Operator and the Engineer in the future Qualifications.

50.6

Conclusion

In the future, SAM project foresee to continue the identification of current needs with industrial organizations, educational centers and AM professionals /workers, in order to identify emergent and short-term AM skills gaps and needs. Also, the foresight analysis will be implemented to determine which skills and trend are expected to emerge until 2030. In parallel, a set of activities will take place aiming to review and design new qualifications/professional profiles and units of learning outcomes. More Qualification and skills will follow be integrated in the IAMQS, since the AM market keeps evolving and new processes and new materials start to have more industrial applications.

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2. ADMIRE Project: Knowledge alliance for additive manufacturing between Industry and universities. https://admireproject.eu/ 3. CLLAIM Project: Creating knowledge and skills in additive manufacturing. https://cllaimprojectam.eu/ 4. SAM Project: Sector skills strategy in additive manufacturing. https://www.skills4am.eu/ 5. Wohlers, T.T.: Wohlers report - 3D printing and additive manufacturing, State of the Industry, Annual Worldwide Progress Report. Wohlers Associates Incorporated (2019). https://wohlersassociates. com/press77.html 6. 3D Hubs: 3D Hubs’ Additive Manufacturing Trend Report 20213D printing market growth in the year of the COVID-19 (2021) – Consulted in May 2021. https://manufactur3dmag.com/3d-hubsreleases-its-additive-manufacturing-trend-report-2021/ 7. SAM project partners: Global and Societal Milestones Report (2020) – Consulted in May 2021. https://www.skills4am.eu/ documents/D1.2%20Global%20and%20Societal%20Milestones_ Revised.pdf 8. SAM project partners: European AM skills strategy Roadmap (2021) – Consulted in May 2021. https://www.skills4am.eu/ documents/D4.10%20Skills%20Strategy%20Roadmap%202021_ %20M24.pdf 9. Carroll, G., Boutall, T.: Guide to developing national occupational standards (2011). https://pjp-eu.coe.int/ar/web/bih-higher-educa tion/images/nos-guide-for-_developers-2011.pdf 10. Biggs, J., Collis, K.: Evaluating the quality of learning - the SOLO taxonomy (Structure of the Observed Learning Outcome) (1982). h t t p s : / / b o o k s . g o o g l e . p t / b o o k s ? h l ¼p t - P T & l r ¼& id¼xUO0BQAAQBAJ&oi¼fnd&pg¼PP1&ots¼aqmyh0HnN7& s i g ¼_ e T L x j Yq h W X 2 n f B K k 9 I y U m m b F u k & r e d i r _ esc¼y#v¼onepage&q&f¼false

Acknowledgments This manuscript was possible thanks to SAM consortium partners: IDONIAL, Materialise, AITIIP, Brunel University London, CECIMO, EC Nantes, EPMA, LORTEK, ISQ, Ansys, LAK, MTC, IMR, LMS Patras, POLIMI and FA.

Disclaimer

The European Commission’s support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

References 1. ManuFUTURE High-Level Group, European Commission: ManuFUTURE —Vision 2030 – Competitive, Sustainable and Resilient European Manufacturing: (2018). http://www. manufuture.org/wp-content/uploads/Manufuture-Vision-2030_ DIGITAL.pdf

Adelaide Almeida Coordinator of the SAM Project, the blueprint for AM aiming at delivering a strategic skills approach to support the growth of the sector.Project Manager since 2016, being responsible for several education projects focused on the development of educational programs and new professional profiles for the manufacturing industry at European Level.Her field of expertise include the development and implementation of projects aiming at developing national and international standards for Vocational Education and Training (VET) and its alignment with European policies and tools, such as the learning outcomes approach (LOs), vocational credit system (ECVET), and European Qualifications Framework (EQF) within EWF Qualification Systems.In the past, she coordinated e-learning professional courses and worked several years in the Adult Education field, as an RPL (Recognition of Prior Learning) Technician, for lower and upper secondary levels, on behalf of the Portuguese educational and training system.She holds a master’s degree (MSC) in Educational Sciences since 2008 from the University of Coimbra.

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Eurico Assunção MSc in Mechanical Engineering since 2008, by Instituto Superior Técnico, Lisbon, and a PhD at Cranfield University on laser Welding.Invited Assistant Professor September in Instituto Superior Técnico, since 2013.Post-Graduated in Business Administration and Management, General by Universidade Católica Portuguesa (2016–2017).Lecturer in the disciplines/programs of: Welding processes and complements of mechanical technology; Welding Engineer course; and in Comprehensive Welding Laser Course.

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Ana Beatriz Lopez She works at EWF as System Manager since 2019, being also involved in ERASMUS+ and H2020 projects.She holds an MSc in Mechanical Engineering since 2015, by Instituto Superior Técnico, Lisbon. PhD Thesis on “Quality Assurance for Wire and Arc Additive Manufacturing,” in which the main objective was the development of NDT techniques in order to inspect WAAM components, considering the different stages of the process: design, build process, and post-processing.

VET and Academic Training for Additive Manufacturing in Germany

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Contents 51.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 867

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Competency Requirements for Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Design and Pre-process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . In-process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Post-Process and Finishing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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51.3.1 51.3.2 51.3.3 51.3.4 51.3.5 51.3.6

Content of Various Training and Further Education Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Classification of the Educational Offers . . . . . . . . . . . . . . . . . . Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Design and Pre-process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . In-process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Post-process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The lack of skilled labor is one of the main problems faced by organizations that want to expand their activities in the field of Additive Manufacturing. One approach to solving this problem is to upskill already established skilled workers. This chapter analyses the extent to which vocational education and training of conventional occupations in Germany imparts competencies that are also needed in the field of Additive Manufacturing. For this objective, the required competencies in the additive process chain are defined. In a further step, different vocational education and training courses and exemplary further training courses as well as the occupational profiles defined by the European CLLAIM project (Creating knowLedge and skilLs in AddItive Manufacturing) are examined regarding their acquisition. The result shows that the M. Petersen · C. Leupold (*) University of Bremen, Bremen, Germany e-mail: [email protected]; [email protected]

vocational education and training courses contain up to 50% of the listed competencies of the CLLAIM profiles and thus cause a significantly reduced further training effort for participants who are already occupationally qualified. Furthermore, as expected, study programs and continuing education programs specifically geared toward Additive Manufacturing contain a large number or all the examined competencies of the CLLAIM occupational profiles. Keywords

Competency requirements · Vocational education and training · Operator laser beam powder bed fusion (LB PBF) · Designer PBF · CLLAIM · Supervisor · Inspector

51.1

Introduction

A significant growth of 21% in Additive Manufacturing (AM) in 2020 and a projected doubling of the market volume of currently $12.6 billion by 2026 show that the use of additive technologies will increase significantly [1]. For this projected increase to become true, significantly more people in a wide variety of positions will be needed to become professional users of AM technologies. The need for these is reflected in a study from 2021 [2]: 15% of over 1900 companies surveyed from 71 countries cited a lack of skilled workers as an obstacle to expanding the use of AM, and 13% cited a lack of training as an obstacle. However, for people who are interested in jobs in this field and for industrial companies, it is currently difficult to get an overview of the unstructured market of educational offers to acquire the necessary competencies for the job of choice, or to find a suitably qualified person for a vacancy [3]. In addition to the young history of AM processes compared to conventional manufacturing processes, the lack of national framework

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_51

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curricula as a reference is also a reason for this current situation. With the EU project CLLAIM “Creating knowLedge and skilLs in AddItive Manufacturing,” an international qualification framework was created for the first time that provides differentiated occupational profiles for the various areas of AM of metallic components [4]. For the respective profiles “Operator,” “Designer,” “Supervisor,” and “Inspector,” curricula were created which were composed of a pool of defined competence units. Since the first training courses according to this system were only offered in 2019, the number of people with the corresponding certificates is still small [5]. Based on the required competencies, this chapter is intended to show the extent to which already trained skilled workers from different fields in Germany have the qualifications needed in AM which are reflected in the respective profiles of the CLLAIM qualifications framework. These results can be used to estimate the effort required to upskill the existing workforce in the respective areas. For this purpose, three Dual Vocational Education and Training (Dual VET) programs whose content overlaps with activities in the different fields of AM are analyzed with a total of almost 10,000 new trainees per year [6]. Furthermore, a bachelor’s degree program for qualification in the field of AM as well as a further education program for already trained skilled workers are examined to show the overlaps here as well. The results of this step will show which qualification measures have large overlaps with the respective occupational profiles of the CLLAIM project and whose graduates therefore need to acquire fewer competencies to carry out the activities corresponding to the qualification framework. Furthermore, on this basis, it is shown how an interface between the tasks between skilled workers and academically trained employees could look within the additive process chain and which areas of application are thus open to the graduates in each case. As the CLLAIM qualification framework refers to powder and wire-based AM processes for metallic components, the focus of this analysis is placed on this field.

51.2

Competency Requirements for Additive Manufacturing

To be able to compare different educational offers, a definition of the competencies needed to carry out additive processes is necessary. In this chapter, the term “competency” describes the ability, beyond qualifications and knowledge, to process specific tasks with general characteristics [7]. Since the advantages of AM processes are particularly evident in individual components, specific challenges for process participants are produced. Their personal competencies enable them to transfer and adapt skills, knowledge, and qualifications to these new, challenging situations. The internal norms,

rules, and values as well as the experiential knowledge of the respective competency bearer also flow into a competency [8]. This deep connection of the personality with competency means that they cannot be taught in the classical sense. They can only be acquired in “novel, open and real problem situations by acting creatively” [8]. For the analysis of the necessary competencies, the results of an interview by Daniel et al. [9] and a list by Marschall [10] are used as a basis and limited to the areas shown in Fig. 51.1 and partially combined. The following analysis is based on the division of the process into design, pre-process, in-process, post-process, and finishing as provided for in VDI 3405, a standard developed by the Association of German Engineers. Depending on the business model, there may be deviations in the form of additionally required or not required competencies for the operation of AM systems.

51.2.1 Design and Pre-process According to VDI 3405, in this phase, all the necessary steps are carried out before the additive parts can be manufactured. For this, the acting person or team must have the following competencies: Overview of Additive Processes: To assess whether AM can add value to a component, it is important to have an overview of the different AM processes. If there is the possibility of accessing different processes, the acting person must be able to select the most suitable process for the particular application. Factors such as cost, duration, quality, or the need for possible post-processing can play an important role here. Without being able to compare these factors among different AM processes, it is not possible to make an informed selection of the ideal process [9]. Overview of Available Materials and Their Properties: To be able to manufacture a component that has certain characteristic values, the acting person must know which materials are available and which materials cannot (yet) be used in an additive process [10]. Furthermore, it must be known which material characteristics can be realized by additive processes, such as the maximum achievable density, the surface quality, or the strength, and whether support structures will be necessary for the production of the component when using the material. Finally, an idea of the material-specific post-processing steps that will be available must also be given at this stage in order to be able to make an assessment of the use of material in a specific case. AM-Compatible Design of the Components: When designing a component to be produced by AM, the boundary

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VET and Academic Training for Additive Manufacturing in Germany

CAD data generation

1

Data preparation

2

869

Machine preparation

3

51 P1=42 P2=400 P3=0,5

In-process Building process

4

Design & pre-process

Post-process & finishing Finished part

Finishing

6

Part removal and post processing

5

Fig. 51.1 Steps of the Laser Powder Bed Fusion process, divided into design and pre-process, in-process, and post-process & finishing; based on [11]

conditions suitable for the respective process must be considered. In addition to the usual design possibilities offered by conventional manufacturing processes, a part to be made by AM offers new construction and design approaches to use the potential of these processes in terms of material savings and shape design [12]. The required competency of designing components according to restrictions includes not only construction and simulation aspects but also the correct implementation of support structures to specifically support the component during the process and prevent unwanted deformations. Generating 3D Data: The advantages of AM also play an important role in the creation of CAD files. In addition to the fundamentals of design, AM components require deep knowledge in generating 3D CAD models. For example, a parametric structure of the models allows a faster individualization of the models, and thereby the advantages of moldand tool-free production can be used. Furthermore, e.g., basic microstructures can be used in the volume models in order to reduce the construction time and at the same time to save weight [13]. In addition to generating 3D data using a CAD program, the acting person must also be able to recognize and correct errors in 3D solid models.

Creating and Evaluating Simulations: In order to be able to fully exploit additive components with regard to their high degree of design possibilities and the associated advantages, such as a significant reduction in weight as a result of an optimal flow of forces in the component, the acting person demonstrates competencies in the area of topology optimization and computer-aided design of components [14]. Converting of Different File Formats: For use in AM, the Standard Triangle Language (STL) is often used, which approximates model surfaces by triangular facets. To achieve this format, the CAD data must be converted. On the one hand, the resolution of the triangles must be determined for this process, which affects the contour accuracy of the AM parts. On the other hand, defects often arise during the transformation (e.g., non-closed surfaces or inverted triangles) which must be identified and solved [11]. Positioning of Components and Generation of Support Structure: To ensure the components are built up in the ideal position for the respective application, the acting person must consider aspects such as anisotropy due to the layer structure regarding possible stress cases that may affect the part. Depending on the component positioning, support

870

structures must also be implemented, which usually must be removed after the AM process [11]. Slicing and Process Design: After this step, the volume models must be divided into layers of specific size in orthogonal alignment to the z-axis. This process is called “slicing.” The acting person must therefore be competent in the operation of software used for this process. In addition to the operation, the technical background for an optimal selection of the layer thickness must also be known, as this has a significant influence on various factors, such as the accuracy and the duration of the manufacturing process, which depends on it. Afterward, decisions have to be made on other machine parameters such as the exposure time of the laser [15]. Handling of Metal Powders and Other Raw Materials: The safe and quality-compliant handling of the metal powders and other raw materials used must be ensured in particular. Especially when using metal powders, health hazards can arise due to the small particle size. Other operating materials such as protective gases can also be hazardous to health, for example, due to emissions [16]. It is therefore essential that the acting person is informed about the possible risks and how to avoid them.

51.2.2 In-process According to VDI 3405, the in-process describes the manufacturing operation prepared in the pre-process that is carried out by the AM equipment [16]. Monitoring Manufacturing Process: During the build process, competencies are needed to evaluate the running process. If unplanned errors and problems occur, the acting person must be able to recognize them and make decisions regarding the continuation of the process or termination of the process. When failures occur, it is also necessary to identify the reasons in order to avoid them in further part production. One competency required for this is the operation of the respective machine [3].

51.2.3 Post-Process and Finishing This phase includes all work steps to be carried out on the component after successful completion of the in-process. Knowledge of Materials Science for Post-treatment: Since a growing number of materials can be used for the various AM processes, the acting person must have

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knowledge of relevant material types and their properties in relation to further heat treatments and metallographic analysis [12]. Overview and Planning of Finishing Processes: Users must be able to make decisions about the optimal sequence of different finishing steps in order to achieve the required component properties. To be able to make independent decisions about the necessary finishing steps, an overview of the possible processes such as abrasive blasting and milling must be available and the part properties that can be achieved in each case must be known [9]. Practical Application of Subtractive Processes: In addition to a theoretical overview of possible post-processing methods and the appropriate planning of these, the acting person should also demonstrate the competency for practical application of subtractive methods in order to be able to carry out post-processing of an additively manufactured component on their own [3]. Selection and Application of Measuring Equipment: To check the quality requirements of the manufactured components, the acting person must be able to select suitable measuring methods and apply the various measuring instruments [9]. Understanding and Handling of IT-Based Tools for Quality Assurance: In addition, competency is needed to transfer the measurement results into IT-based tools for documentation. For this point, the understanding of the tools as well as the importance of quality assurance is mandatory [17]. Reflection of Process Results: The acting person must be able to relate process results like the quality of the surface to the parameters used, the machine, and the materials. In this way, correlations can be recognized that may require changes in the design specifications or parameter settings [9].

51.3

Content of Various Training and Further Education Programs

With the further spread of AM in the industry, the range of training and further education offered for this technology is also growing apart from the offers of the machine manufacturers. In the following, various possibilities for acquiring AM skills are presented and a selection of these analyzed. Since there is no specific Dual VET for AM, training occupations are listed whose contents overlap with the required competencies for AM of metals at different points. In addition, training courses offered by associations and

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871

51.3.1 Classification of the Educational Offers

education entrance qualification, but in some cases a completed Dual VET and corresponding work experience are also recognized as entry requirements. The CLLAIM qualification framework, on the other hand, is a new approach: it represents an attempt to develop a European harmonized qualification system and corresponding qualifications according to the needs of the AM market. For this purpose, four different job profiles have been developed: operator, designer, supervisor, and inspector [4]. These professions are intended to cover all aspects of AM and to standardize the division of labor in this area.

In Germany, after completing 10–13 years of general education, more than 62.6% [18] of graduates decided in 2019 either to enter Dual VET or to go on to higher education. The 36.8% of school graduates who start Dual VET are distributed among approximately 320 [19] different training occupations, which include both a state teaching component and practical training within a company. The distribution of the contents is shown in Fig. 51.2. For persons qualified in this way, various further education programs are available, some of which require a certain amount of work experience in addition to the training qualification as a prerequisite for entry. The duration of these offers varies from a few weeks to several semesters [20]. Classical higher education programs also shown in Fig. 51.2 require in most cases a higher

Dual VET System Since there is no specific program for AM, the Dual VET programs “technical product designer” [22], “foundry mechanic” [23], and “metal cutting mechanic” [24] are examined as three Dual VET programs whose contents may overlap regarding the development of competencies for AM. The idea behind this approach is to examine the overlap of content from the pre-process phases in the occupation of technical product designer. The Dual VET of foundry mechanic is selected because it is an alternative generative process from which competencies may be transferable. Finally, the occupation of metal cutting mechanic is examined. On the one hand, this is interesting against the background of the competencies required in post-processing. On the other hand,

universities are mentioned, which are primarily aimed at already skilled workers in metal technology, and one of these courses is evaluated as an example. A bachelor’s degree program for a qualification within the field of AM is also analyzed and a selection of others is listed. Finally, the occupational profiles of the CLLAIM qualification framework are analyzed for the LPBF procedure in order to gain a reference for the evaluation.

Labour market

Further education programmes

30% of VET

70% of VET in company

in vocational school

Vocational school education • Legal basis: compulsory education law • Local government finances public vocational schools (facilities, teachers, etc.) • Vocational schools offer lessons in vocational (2/3) and general education (1/3) subjects free of charge

Dual VET system 2 – 3.5 years

In-company training • Legal basis: training contract • Company pays trainee a “training

Higher education 3.5 – 6 years

allowance”

• Company provides systematic training under real-life working conditions (incompany trainer, up-to-date equipment, etc.)

General education 10 –13 school years

Fig. 51.2 Extract of German educational offers for school graduates with a focus on dual vocational training; based on [21]

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since 2018 it has been possible for industrial metalworking occupations, including this training, to strive for an additional qualification in “Additive Manufacturing.” In the following analyses, the Dual VET program is therefore listed once without and once with the additional qualification.

Further Education and Study Programs Among other things, the lack of capacities for Dual VET in the field of AM has led to a number of different organizations offering further training in this field. For example, the DVS (German Welding Society) offers a training course for “Additive Manufacturing Metal Specialist” in various cities in cooperation with other organizations. The course concludes with an examination, which is certified in accordance with DVS Guideline 3601-1. Individual Chambers of Industry and Commerce also offer training courses, such as the course for “Certified Industrial Technician for Additive Manufacturing” from the Würzburg-Schweinfurt Chamber of Industry and Commerce, which concludes with a “Public law qualification at DQR level 6.” The Chamber of Commerce and Industry (IHK) Academy Swabia also offers a course for “IHK specialist for Additive Manufacturing processes,” through which a certificate can be obtained. Non-profit organizations such as the Educational Association of the Bavarian Economy also offer courses in AM that end with an organization’s own certificate. In addition, there are university certificates that, similar to a bachelor’s degree, show the credit points achieved, which in turn can possibly be credited in any subsequent study courses. At Schmalkaden University of Applied Sciences, for example, it is possible to study the further education program “application engineer for Additive Processes” [25] with a university entrance qualification or completed Dual VET with corresponding work experience. This is spread over a period of two semesters and consists of individual modules, each of which is concluded with an examination. After passing all modules with a total of 26 credit points, the certificate is awarded in the form of a university certificate. In addition, the Technical University Bergakademie Freiberg offers an independent bachelor’s degree program “Additive Manufacturing” [26] which can be attended after obtaining a university entrance qualification and comprises 210 CPs over seven semesters. After passing the examination, the degree “Bachelor of Science” is awarded. Due to the large number of programs offered, only the latter two were selected to be analyzed as a reference for this study. A detailed examination of the other courses listed could be carried out in a future study using the methodology presented in Sect. 51.3.2. CLLAIM: Qualifications While the CLLAIM qualification framework refers to different additive processes, for this analysis only the variant of

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laser beam powder bed fusion (LB PBF) was investigated, due to the fact that this variant is mainly used in the industrial environment for creating metal components [27]. Due to the different job requirements, the job profiles, which are divided into competence units, require different prerequisites and different workloads. While for the profile of the LB PBF operator (168 h workload), a compulsory school diploma is sufficient; for the profile of the inspector (259 h workload), a visual acuity test and basic knowledge and skills related to quality assurance and health safety environment are required. The latter is also required for the supervisor profile (182 h workload), and at least 1 year of experience in Quality and Safety supervision is recommended. The access conditions to Metal AM Designer for PBF Processes (224 h workload) admission consists of the demonstration of an Mechanical Engineering, Materials Engineering, Aeronautical Engineering or similar.

51.3.2 Methodology With the help of the module manuals and the framework curricula and training regulations or the descriptions of the competence units, the different education programs are examined regarding the intended acquisition of competencies for AM. Due to the non-uniform designations and descriptions of the competencies, an exact match is not always given, so that a gradation of the match is made. A distinction is made between cases in which the participants should have acquired the respective competency after completing the offer and those in which the participants have basically been taught the corresponding methodology but need additional knowledge acquisition to apply it to AM processes. In the following tables, the first are marked in dark green, the second in light green. Since the written documents are the sole basis for the assessment, knowledge, and skills beyond these are not recorded. Competencies acquired outside the topics of AM in the respective education and training programs are also not included.

51.3.3 Design and Pre-process In the Dual VET programs analyzed, the development of the competency to select the optimal additive process from the different additive processes is currently only aimed at in the additional qualification “Additive processes” of the metal cutting mechanic. In contrast, an overview of the different processes is included in the study program, in the further education program and in all four profiles of the CLLAIM qualification framework. An overview of the available materials and their behavior during the additive construction process is provided in some

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programs of the different educational offers. This content includes, for example, knowledge of the causes of residual stresses and undesirable deformations and how to avoid them. In the current framework curricula of Dual VET as a metal cutting mechanic or technical product designer, important aspects such as the properties, selection and handling of materials, or the design are covered, considering the material properties as well as their machining and application possibilities. Treatment of these topics focused on AM is only found in the current curricula as part of an additional qualification for training as a metal cutting mechanic. In the AM degree program, a very detailed examination of the various materials and their behavior is provided, and this topic is also integrated into the further education program. In the CLLAIM qualification framework, knowledge of processable materials is integrated into the profiles of operator, supervisor, and inspector. However, an in-depth examination of residual stresses, for example, is not provided for in the competence units. In Dual VETs such as technical product designer or foundry mechanic, the development of the competency to create components considering the manufacturing restrictions of conventional manufacturing processes such as the casting process is promoted. This basic understanding can possibly be used as a foundation and expanded by the knowledge of the restrictions of AM processes in order to learn AM-compatible design more quickly. In contrast the additional qualification “Additive Manufacturing” of the training to become a metal cutting mechanic includes the acquisition of the competency to consider the possibilities and limitations of AM in the design of components. The AM study program at the TU Bergakademie Freiberg and the further education program to become an application engineer for additive processes also include corresponding content in the module manuals. In the CLLAIM qualification system, this competency is covered in the competence units provided for the design engineer occupational profile. The generation of 3D CAD data is a basic competency in the occupational profile of the technical product designer. In the additional qualification of metal cutting mechanics, the participants are also supposed to develop this competency, while this content is not found in the rest of the Dual VET programs examined. Both in the AM study program and in the further education program, the acquisition of this competency is one of the objectives. In the CLLAIM program, this competency is required of graduates of the competence units in the guideline to become a designer. Across the various training programs, the competency to create and evaluate simulations is to be acquired in the training for technical product designers, the study program “Additive Manufacturing” and the CLLAIM profile of the designer. The converting of CAD data is learned by the participants as part of the additional training for metal cutting mechanics.

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The trainees of the occupation “technical product designer” are prepared to use standard and purchased parts from different sources in their designs, so it is necessary for them to be able to convert different file formats. It should be possible to expand this competency to include the competency of converting, which is necessary for the additive processes. In the module catalogues of the AM study program and the further education program, this competency is listed as a learning objective. It is also a required competency to achieve the designer profile in the CLLAIM qualification framework. The acquisition of the competency to position components in the build chamber and to insert component structures is only listed as a teaching objective in the study course AM and in the designer profile of the CLLAIM qualification framework. In none of the educational offers examined is both the process of slicing and the process design for AM explicitly listed as an objective in the documents. Of the Dual VET programs examined, the participants in the additional qualification “Additive Manufacturing” of the metal cutting mechanic should acquire the competency to adjust and optimize process parameters. In the study course and the further education program, only in the latter is the slicing process part of the teaching content. For the operator in the CLLAIM qualification framework, beam profiling of the laser beam is listed as a competency to be acquired, which is part of the process design. In addition to the successful production of an additive part, it is necessary for the field of metal powder-based processes to ensure that the powders are handled in a safe and high-quality manner. The knowledge and skills on this point are conveyed in the job profiles of the operator and supervisor as defined in the CLLAIM project. The module descriptions of the continuing education program and the bachelor’s program also provide the teaching of corresponding knowledge and skills. These results are shown in Table 51.1.

51.3.4 In-process To successfully monitor an AM process, it may be necessary for users to decide whether to continue or stop the process. Foundry mechanics, as well as machinists, are trained to monitor production machines, evaluate failures, and take measures to eliminate them. This competency could be transferred to additive processes by incorporating AM knowledge. Skills and knowledge for monitoring additive processes are taught in the additional qualification Additive processes of the Dual VET metal cutting mechanic as well as in the competence units for the operator PBF. The teaching in the individual training courses is illustrated in Table 51.2.

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Table 51.1 Overview of the content in the various training and further education programs referring to the competencies required in the pre-process

Apprenticeships

Technical product designer

Competency requirements

Metal cutting Foundry mechanic

Metal cutting mechanic

mechanic + Additional qualification

Overview of additive processes Overview of available materials and their properties AM-compatible design of the components Generating 3D data Creating and evaluating simulations Converting of different file formats Positioning of components and generation of support structure Slicing and process design Handling of metal powders and other raw materials Course of study & Further education Competency requirements

B. Sc. Additive manufacturing

Application engineer Additive processes

Overview of additive processes Overview of available materials and their properties AM-compatible design of the components Generating 3D data Creating and evaluating simulations Converting of different file formats Positioning of components and generation of support structure Slicing and process design Handling of metal powders and other raw materials CLLAIM Competency requirements

Operator LB PBF

Designer PBF

Supervisor

Inspector

Overview of additive processes Overview of available materials and their properties AM-compatible design of the components Generating 3D data Creating and evaluating simulations Converting of different file formats Positioning of components and generation of support structure Slicing and process design Handling of metal powders and other raw materials Aim is to acquire the competency Aim is to acquire the corresponding methodology

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875

Table 51.2 Overview of the content in the various training and further education programs referring to the competencies required in the in-process

Apprenticeships

Competency requirements

Technical product designer

Foundry mechanic

Metal cutting mechanic

Metal cutting mechanic + Additional qualification

Monitoring manufacturing process Course of study & Further education Competency requirements

B. Sc. Additive manufacturing

Application engineer Additive processes

Monitoring manufacturing process CLLAIM Competency requirements

Operator LB PBF

Designer PBF

Supervisor

Inspector

Monitoring manufacturing process Aim is to acquire the competency Aim is to acquire the corresponding methodology

51.3.5 Post-process In order to be able to carry out or arrange heat treatments or metallographic examinations, knowledge of materials science is required for many metallic components. In the different Dual VETs, prospective foundry mechanics are prepared both for the selection of heat treatments and for carrying out a range of material tests such as metallographic examinations or tensile tests. In contrast, the curricula for metal cutting operators and technical product designers do not include such content. In the AM Bachelor’s degree program under consideration, in-depth knowledge in this area is taught in the materials technology modules on ferrous and non-ferrous metals. Also in the further education program Additive Processes, the heat treatment of AM metal parts is an aspect of the module: “Metal-based Additive Manufacturing Processes.” In the CLLAIM occupational profiles of the inspector and the designer, knowledge of the thermal post-treatment of metal parts is the content of the respective competence units. Since many component properties of AM metal parts can currently only be achieved through the use of post-processing methods [28], appropriate knowledge of available subtractive manufacturing methods must be available for the selection and planning of post-processing. In the Dual VETs of technical product designer and foundry mechanic, content on

machining production processes is taught to be able to design products that can be manufactured using these processes. Particularly in the occupational profile of the metal cutting operator, a detailed examination of the various processes for finishing is fundamental. In most engineering degree programs, including the bachelor’s degree in AM, the corresponding basic competency is developed in the modules of manufacturing technology. In the AM further education course, a classification of conventional manufacturing processes is made for this purpose. According to the professional profiles defined in the CLLAIM project, the corresponding content is provided for both the operator and the designer in the competence units of the respective curriculum. The competency to apply subtractive manufacturing processes themselves is only fully acquired by trainees in the Dual VET metal cutting operator in the analyzed educational offers. Partial aspects, such as the operation of simple tools, are defined as an objective in the training for foundry mechanics as well as in the competence units for the occupational profile of LB PBF operator. To be able to check the quality of the components after completion of the production process, the competency to select and use measuring and testing equipment must be available. In the Dual VET of metal cutting mechanic and foundry mechanic, it is planned to teach the knowledge and skills for inspecting the resulting components, which can be

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transferred to AM without major adaptations. Both in the Bachelor’s degree program and in the continuing education degree program, the module plan provides for the teaching of the corresponding knowledge and skills. The acquisition of this competency is also planned for the CLLAIM profiles operator, inspector, and supervisor. For the electronic documentation of measured values, it is also important to understand how IT-based quality assurance tools work and to be able to handle them. With the exception of the CLLAIM occupational profile “operator,” the acquisition of these competencies is also found in the education and training measures listed above. For the goal of constantly reducing the proportion of components that do not meet the qualitative requirements, it is necessary to reflect on the process results after the components have been manufactured. In the training courses for foundry and metal cutting mechanics, methods for reflecting on process results are also taught, but with reference to the respective processes. Through the additional qualification “Additive Manufacturing,” the competency to evaluate Additive Manufactured components is an optional component of the training to become a cutting machine operator. The participants in the AM course at the Technical University Bergakademie Freiberg and the prospective application engineer for Additive Processes at the University of Applied Sciences Schmalkalden are trained accordingly to be qualified for this. In the CLLAIM qualification framework, the acquisition of this competency is necessary to pass examinations to become an operator or inspector. An overview of the contents taught in the various training and further education courses referring to the post-process is shown in Table 51.3.

51.3.6 Evaluation The analysis of the competencies to be acquired according to the module descriptions shows the content overlaps of the training curricula and the study programs with the different CLLAIM occupational profiles, which are listed in Table 51.4. The values of the largest and second-largest overlaps are highlighted in green and light green, respectively. The additional training for “Additive Processes” has an overlap of 80% of the competencies found in the CLLAIM occupational profile of the LB PBF operator. An identical value is found for the further education program, followed by the bachelor’s program with 73% of the competencies. It can also be seen that with 47% each, the training as a foundry mechanic and machining mechanic also contains almost half of the competencies that the operator also contains. In comparison with the CLLAIM profile of the designer for PBF, the bachelor’s program shows an overlap in all competencies. The further training course to become an application engineer

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(75%) also has a large overlap, as does the training course to become a cutting machine operator with additional qualification (63%). After training as a technical product designer, 50% of the designer’s competencies can be demonstrated. The bachelor’s degree program in additive processes and the application technician show a high degree of overlap with the occupational profiles of supervisor and inspector; in the case of the former, all the competencies examined can be found in the module manuals. Of the Dual VETs, training as a cutting machine mechanic with a completed additional qualification shows the highest degree of overlap at 67% and 73%. The Dual VET foundry mechanic still shows relatively high agreement with 64% for inspector.

51.4

Conclusion

The previous analysis shows that there are several ways to qualify for the different occupational profiles needed to carry out additive processes. The relatively new approach of the CLLAIM qualification framework takes these different ways of competency building into account by explicitly describing alternatives to fixed courses. On the one hand, this makes it possible to acquire knowledge via blended learning programs, so that some theoretical learning modules can be carried out without attending face-to-face events. On the other hand, it is possible to receive credit for competencies that result from working with additive processes or from carrying out other training or further education programs. In this way, the effort required to obtain an internationally recognized certificate in the field of AM can be significantly reduced. At present, training as a metal-cutting mechanic with the additional qualification of additive processes in particular has a high degree of overlap with the CLLAIM occupational profile of the operator, so that users who are pre-qualified in this way can pass an internationally recognized certificate with relatively little effort. Even without this additional training or after training as a foundry mechanic, basic competencies can be adopted and significantly reduce the number of competence units required. For the job profiles of designer, supervisor and inspector, on the other hand, it is evident that it is primarily the bachelor’s degree and the continuing education course that include the corresponding competencies. For people who are already professionally qualified, the continuing education program can represent an entry into the areas of choice in AM, especially outside of the operator. From these results, a relatively clear cut between the areas of responsibility of academically educated employees and professionally educated employees can be recognized for the current state of AM. While the operator’s job can be performed with little further training after completing Dual VET, for the activities in the design and

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877

Table 51.3 Overview of the content in the various training and further education programs referring to the competencies required in the postprocess

Apprenticeships

Technical product designer

Competency requirements

Metal cutting Foundry mechanic

Metal cutting mechanic

mechanic + Additional qualification

Knowledge of materials science for post-treatment Overview and planning of finishing processes Practical application of subtractive processes Selection and application of measuring equipment: Understanding and handling of IT-based tools for quality assurance Reflection of the process results Course of study & Further education Competency requirements

B. Sc. Additive manufacturing

Application engineer Additive processes

Knowledge of materials science for post-treatment Overview and planning of finishing processes Practical application of subtractive processes Selection and application of measuring equipment: Understanding and handling of IT-based tools for quality assurance Reflection of the process results CLLAIM Competency requirements

Operator LB PBF

Designer PBF

Supervisor

Inspector

Knowledge of materials science for post-treatment Overview and planning of finishing processes Practical application of subtractive processes Selection and application of measuring equipment: Understanding and handling of IT-based tools for quality assurance Reflection of the process results Aim is to acquire the competency Aim is to acquire the corresponding methodology

organization of the manufacturing operation it is more appropriate to complete a specific bachelor’s degree course or a further training course. The identification of a clear interface is not always possible, as the various additive processes have different degrees of complexity, and the required competencies vary in their depth. On top of that, this identification only represents a momentary record. As the development of AM methods progresses, the competencies required to carry out

these processes continue to evolve. At the moment, it is becoming apparent that the specialization of manufacturing systems will continue to increase in the future due to different use cases. Already today, the systems for use in industrial large-scale production of highly complex parts and on-demand manufactured spare parts differ in their structure and the peripherals used from the much less automated use of AM technology for the construction of prototypes and small

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Table 51.4 Matching the respective education and training programs with the CLLAIM – job profiles

CLLAIM - job profiles Accordance with

Operator PBF

Designer PBF

Supervisor

Inspector

Technical product designer

1 / 7.5 (13%)

4 / 8 (50%)

0 / 4.5 (0%)

0 / 5.5 (0%)

Foundry mechanic

3.5 / 7.5 (47%)

2.5 / 8 (31%)

2 / 4.5 (44%)

3.5 / 5.5 (64%)

Metal cutting mechanic

3.5 / 7.5 (47%)

1 / 8 (13%)

2 / 4.5 (44%)

2.5 / 5.5 (45%)

Metal cutting mechanic + Additional qualification

6 / 7.5 (80%)

5 / 8 (63%)

3 / 4.5 (67%)

4 / 5.5 (73%)

B. Sc. Additive manufacturing

5.5 / 7.5 (73%)

8 / 8 (100%)

4.5 / 4.5 (100%) 5.5 / 5.5 (100%)

Application engineer Additive processes

6 / 7.5 (80%)

6 / 8 (75%)

4.5 / 4.5 (100%) 5.5 / 5.5 (100%) Largest overlap Second largest overlap

series with many variants. For the latter, more and more hybrid machining centers are being offered that combine additive processes such as direct energy deposition with subtractive processes. These systems are capable of producing complex components that could not be manufactured without additive processes, or as they are made of expensive metals and are difficult to machine [29]. In addition, repairs or modifications to existing components can be implemented. On the other hand, the possibilities of networking industrial plants and artificial intelligence make a higher degree of automatization achievable. This extends from the design of components – supported by automated topology optimization – to production, which partly is already fully automated in pilot projects [30]. These changes, which are already apparent, are leading to a change in the required competencies and already clearly show that both prospective and already qualified persons will have to develop themselves further to work in the field of AM due to changing requirements in the future. Against this background, it is important to sensitize participants in education and training programs to the increased priority of lifelong learning in this field. On the other hand, a regular check of the actuality of the acquired contents in training and further education programs is essential.

References 1. 3D-grenzenlos Magazin: 3D Hubs-Trendbericht – Markt für additive Fertigung stieg 2020 um 21%. Marktverdoppelung b i s 2 0 2 6 . h t t p s : / / w w w. 3 d - g r e n z e n l o s . d e / m a g a z i n / marktforschung/3d-hubs-trendbericht-fuer-2020-27696263 (2021). Accessed 6 Oct 2021

2. Sculpteo: Was sind die Hindernisse für die Nutzungserweiterung von 3D-Druck in Ihrem Unternehmen? https://de.statista.com/ statistik/daten/studie/1168747/umfrage/ausweitungshindernissedes-3d-drucks-in-unternehmen-2020/ (2021). Accessed 6 Oct 2021 3. Marschall, H.: Additive Fertigung und betriebliche Qualifizierung. Beschäftigungs- und Qualifizierungschancen von Geringqualifizierten im 3D-Druck/in der additiven Fertigung. Working Paper Forschungsförderung, No. 172 (2020) 4. CLLAIM Project: Welcome to CLLAIM projekt. Creating a European AM qualifications system. https://www.cllaimpro jectam.eu. Accessed 6 Oct 2021 5. CLLAIM Project: Pilots of the European matrix of LOs for the European AM Qualifications. Creating a European AM qualifications system. https://www.cllaimprojectam.eu/documents/D6.2% 20CLLAIM%20CU%20Pilots%20-%20EN.pdf (2021). Accessed 6 Oct 2021 6. BiBB: Neu abgeschlossene Ausbildungsverträge, unvermittelte Bewerber, unbesetzte Ausbildungsplätze sowie Angebot und Nachfrage nach Ausbildungsberufen. https://www.bibb.de/de/ 124906.php (2021). Accessed 6 Oct 2021 7. Rauner, F.: Qualifikation, Kompetenz und berufliches Wissen – ein aufklärungsbedürftiger Zusammenhang. In: Schlögl, P., Dér, K. (eds.) Berufsbildungsforschung. Alte und neue Fragen eines Forschungsfeldes. Science Studies, pp. 86–102. transcript-Verl., Bielefeld (2010) 8. Erpenbeck, J., Sauter, W.: So werden wir lernen! Kompetenzentwicklung in einer Welt fühlender Computer, kluger Wolken und sinnsuchender Netze. Springer Gabler, Berlin (2013) 9. Daniel, C., Schmitt, B., Petersen, M.: Arbeitsprozessorientiertes und kompetenzbasiertes Lernen für die additive Fertigung. Eine LehrLern-Situation für die Aus- und Weiterbildung. lernen & lehren. 33, 103–110 (2018) 10. Marschall, H.: Personal für die additive Fertigung. Kompetenzen, Berufe, Aus- und Weiterbildung. Essentials. Springer Vieweg, Wiesbaden (2016) 11. Kumke, M.: Methodisches Konstruieren von additiv gefertigten Bauteilen. Dissertation, Technische Universität Braunschweig 12. Zeyn, H. (ed.): Industrialisierung der Additiven Fertigung. Digitalisierte Prozesskette - von der Entwicklung bis zum

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einsetzbaren Artikel, 1st edn. Beuth Innovation. Beuth; VDE Verlag GmbH, Berlin, Wien, Zürich, Berlin, Offenbach (2017) 13. Lachmayer, R., Lippert, R.B.: Entwicklungsmethodik für die Additive Fertigung. Lehrbuch. Springer Vieweg, Berlin, Heidelberg (2020) 14. Lange, F.: Prozessgerechte Topologieoptimierung für die Additive Fertigung. Dissertation 15. Lachmayer, R., Lippert, R.B. (eds.): Additive Manufacturing Quantifiziert. Visionäre Anwendungen und Stand der Technik. Springer Vieweg, Berlin (2017) 16. Lachmayer, R., Lippert, R.B., Kaierle, S. (eds.): Konstruktion für die Additive Fertigung 2018. Springer Vieweg, Berlin, Heidelberg (2020) 17. Klahn, C., Meboldt, M., Fontana, F., Leutenecker-Twelsiek, B., Jansen, J. (eds.): Entwicklung und Konstruktion für die Additive Fertigung. Grundlagen und Methoden für den Einsatz in industriellen Endkundenprodukten, 1st edn. Vogel Business Media, Würzburg (2018) 18. BiBB: Sektorenanteile 2005 und 2019 im Vergleich. https://www.bibb. de/dokumente/pdf/a2_schau_a4_2-1_2020.pdf (2021). Accessed 6 Oct 2021 19. BiBB: Struktur anerkannter Ausbildungsberufe 2010 bis 2019. https://www.bibb.de/dokumente/pdf/a2_schau_a3_1-1_2020.pdf (2021). Accessed 6 Oct 2021 20. dpa: Uni ohne Studium: Weiterbildungen mit Hochschulzertifikat. Süddeutsche Zeitung, 23 October 2017. https://www.sueddeutsche. de/karriere/arbeit-uni-ohne-studium-weiterbildungen-mit-hochschul zertifikat-dpa.urn-newsml-dpa-com-20090101-171013-99-440731. Accessed 6 Oct 2021 21. GOVET: Präsentationen zur dualen Berufsausbildung in Deutschland. https://www.govet.international/de/54880.php. Accessed 7 Oct 2021 22. BiBB: Technischer Produktdesigner/Technische Produktdesignerin - FR Produktgestaltung und -konstruktion. Informationen zu Ausund Fortbildungsberufen. https://www.bibb.de/dienst/berufesuche/ de/index_berufesuche.php/profile/apprenticeship/03092010 (2011). Accessed 14 Oct 2021 23. BiBB: Gießereimechaniker/Gießereimechanikerin. Informationen zu Aus- und Fortbildungsberufen. https://www.bibb.de/dienst/ berufesuche/de/index_berufesuche.php/profile/apprenticeship/ 190813 (2015). Accessed 14 Oct 2021 24. BiBB: Zerspanungsmechaniker/Zerspanungsmechanikerin. Informationen zu Aus- und Fortbildungsberufen. https://www.bibb. de/dienst/berufesuche/de/index_berufesuche.php/profile/apprentice ship/782319 (2018). Accessed 14 Oct 2021 25. Hochschule Schmalkalden: Anwendungstechniker*in (FH) für Additive Verfahren/Rapid-Technologien. https://www.hsm-fernstudium. de/hochschulzertifikate/technik/anwendungstechniker-fh-fuer-addi tive-verfahren/rapid-technologien. Accessed 14 Oct 2021 26. Technische Universität Bergakademie Freiberg: Bachelor Additive Fertigung (Technologie, Material, Design). https://tu-freiberg.de/ studium/bachelor-additive-fertigung-technologie-material-design. Accessed 14 Oct 2021 27. Wohlers, T., Campbell, R.I., Diegel, O., Kowen, J., Mostow, N.: Wohlers report 2021. 3D printing and additive manufacturing:

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global state of the industry. Wohlers Associates, Fort Collins, Colorado (2021) 28. Gebhardt, A., Kessler, J., Schwarz, A.: Produktgestaltung für die Additive Fertigung. Hanser, München (2019) 29. Ian Wright: Metal Additive Manufacturing for Large Parts. 3D printing large metal parts with Electron Beam Additive Manufacturing (EBAM). https://www.engineering.com/story/metal-additivemanufacturing-for-large-parts (2019). Accessed 8 Oct 2021 30. NextGenAM project for automated metal Additive Manufacturing draws to a close. https://www.metal-am.com/nextgenam-project-forautomated-metal-additive-manufacturing-draws-to-a-close/ (2019). Accessed 8 Oct 2021

Maren Petersen is a professor at the University of Bremen and a member of the ITB Executive Board. She holds a PhD from the TU Hamburg on Additive Manufacturing of metal-ceramic composites using laser beams. In addition to her work as a research assistant and then senior engineer at iLAS on the topic of laser material processing, she was part of the development of the LZN (now Fraunhofer IAPT). Her expertise includes Additive Manufacturing and work science, as well as VR learning applications for welding and collaborative robotics.

Christoph Leupold holds a master’s degree in mechanical engineering from the University of Hanover. He is a research associate at the Institute of Technology and Education and works on technical issues and their implementation in training programs for Additive Manufacturing. His current research focuses on recycling-compatible design of Additive Manufactured components in the context of the increase in multimaterial Additive Manufacturing.

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Innovative Training to Support Adoption of Additive Manufacturing

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Khalid Rafi, Alexander Liu, Paul Bates, Nima Shamsaei, and Mohsen Seifi

Contents 52.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 881

52.2 52.2.1 52.2.2

Trends and Opportunities in AM Education . . . . . . . . . . 882 Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 882 Gaps and Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 883

52.3

Current AM Education and Workforce Development Landscape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 883 Education and Workforce Development (E&WD) Roadmaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 884

52.3.1 52.4 52.4.1

Driving AM Industry Adoption Through Education and Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 885 Certified AM Professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 886

52.5 52.5.1 52.5.2 52.5.3

Skills-Based Training for AM . . . . . . . . . . . . . . . . . . . . . . . . . . The Need for Skills-Based Training in AM . . . . . . . . . . . . . . Skills-Based Training Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Skills-Based Training for Different Populations . . . . . . . . .

52.6 52.6.1 52.6.2

The Role of AM in Advanced Manufacturing . . . . . . . . 888 Advanced Manufacturing and Industry 4.0 . . . . . . . . . . . . . . 888 Advanced Manufacturing and AM . . . . . . . . . . . . . . . . . . . . . . . 889

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Role of AM Stakeholders in AM Training . . . . . . . . . . . . 889

52.8

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 889

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References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 890

Abstract

Training and education are key drivers for the broader adoption of additive manufacturing (AM). This opens a big opportunity in imparting quality training to develop a talent pool of skilled AM experts who can support K. Rafi · A. Liu ASTM International, Singapore, Singapore, Singapore e-mail: krafi@astm.org; [email protected] P. Bates · M. Seifi (*) ASTM International, USA, Washington, DC, USA e-mail: [email protected]; mseifi@astm.org

different phases of the AM value chain. As the technology is continuously improving, the training programs need to be structured to incorporate the latest developments in addition to the core fundamental concepts of the technology. This chapter focus on trends, gaps, and opportunities in AM education, the current additive manufacturing training landscape, strategies to drive AM adoption through education and training, and the role of different AM stakeholders in creating a training curriculum that adequately meets the industry needs. Keywords

AM training · Education and workforce development · Up-skilling · Cross-skilling · Re-skilling · Qualification and certification · Advanced manufacturing · AM implementation · AM role-based skill sets

52.1

Introduction

Additive manufacturing (AM) is at the tipping point of broader adoption across different industries. AM technologies are distinctively different from traditional manufacturing processes and require diverse skill sets to implement the technology. The interrelationships between different elements in the AM process chain, such as design, materials, and process, are significant, and that requires the design engineer, application engineer, quality engineer, supervisor, and AM operator/technician to have a deeper understanding of the entire process chain. Lack of education and training and the shortage of skilled workforce are often identified as the major challenges that hinders the broader adoption of AM technology [1, 2]. To realize the full potential of AM, manufacturing organizations must focus on developing a capable and skilled

N. Shamsaei Auburn University, USA, Auburn, AL, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_52

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AM workforce [3] to stay ahead in the world of digitalization as global trades evolve and become more challenging in recent years. AM is also known to improve manufacturing responsiveness due to the fast lead time, and therefore, talent development becomes important to speed up innovation at small-, medium-, and large-scale enterprises. A skilled workforce in an emerging technology area such as AM enables individual countries to be plugged into an international network of manufacturing partners and markets, creating new opportunities for growth in the manufacturing sector. AM plays an important role in the broader manufacturing capabilities and competitiveness of the manufacturing sector in all economies, particularly in the present digital transformation era.

52.2

Trends and Opportunities in AM Education

AM education is becoming one of the top priorities in the industrial adoption of AM technology. As depicted in Fig. 52.1, several training approaches are being used, which suit the needs of the industry. Developing a strategy for AM education depends on the current technology trends and the agility to respond to any change quickly. A closer look at what is happening in the industry and clearly understanding the needs could open the door to developing innovative AM education approaches.

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Fig. 52.1 Education and workforce development approach for AM industrial adoption

52.2.1 Trends Additive Manufacturing Technologies Are Growing at a Rapid Pace with Innovations and Breakthroughs New innovations and breakthroughs are taking AM to the next level of technological advancements. This can be observed across all the AM technologies, from stereolithography to directed energy deposition. Innovations are happening at a rapid pace, such that it is challenging for educational or learning programs to catch up. There are also many new technologies that have overlapping capabilities. As a result, companies will need to constantly identify process requirements as well as evaluate manpower training needs. Additive Manufacturing Is Becoming More Multidisciplinary AM is no more a standalone technology and is becoming an integral part of the advanced manufacturing concept. This opens up the interaction between AM and other technologies. Therefore, interoperability with adjacent technologies makes AM more multidisciplinary. In addition, AM technology encompasses many different conventional engineering domains such as materials, design, processes, testing, and inspection to emerging domains such as artificial intelligence, big data, cybersecurity, and robotics and automation. Design, Application, and Implementation of AM Is Becoming Faster AM is transforming into a serial production process at a faster pace. With no doubt, AM finds a wide variety of applications in different industry sectors within a limited period of time. Much of the value of AM lies in its capability to generate unique designs and fabricate components that cannot be produced by conventional means. This has staged AM for niche and novel industrial applications, such as lightweight aircraft components [4] that reduce carbon footprint, and mold inserts with conformal cooling channels for improved heat transfer that produces parts with superior surface properties [5]. Optimizing an existing design or creating a new design that improves the efficiency at component and system levels gains significant traction for a myriad of applications across different industry sectors such as aviation, spaceflight, medical, construction, oil and gas, maritime, electronics, and energy. Different Training Approaches That Vary Widely in Scope, Scale, and Quality With the current developments in AM, different training approaches are being adopted by various organizations. Universities are preparing next generation workforce with exposure to emerging technologies. Companies are providing on-the-job training to the incoming and incumbent workforce with skills required for their jobs. On-the-job training helps the

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participants become familiarized with the working environment and have a hands-on experience on the machines, tools, materials, and ancillary equipment. It could improve the productivity and efficiency of the organization. There are technical institutes that provide vocational training that prepare employees for a specific line of work with specialized skills. The trends in AM education and workforce development follow the technical advancements in the AM industry but at a much slower pace. The lag in the pace between technology advancements and the implementation of education programs has generated a gap in the availability of skilled professionals with the needed knowledge to meet the demand from AM employers [6].

52.2.2 Gaps and Opportunities There is a widening gap between AM advancements and the available skilled workforce. Bridging this gap is crucial in driving the implementation of the technology. Following are some of the gaps and opportunities that exist in creating a robust workforce development program.

AM Workforce Needs an Overall Understanding of the Entire AM Process Chain Additive manufacturing includes multiple stages, and each stage of the process is interconnected. These different stages are managed and controlled by the workforce that includes managers, engineers, supervisors, technicians, and operators. The AM workforce needs to understand the process workflow and should be able to communicate with the group. For example, an AM designer needs to work concurrently with other members down the process line to ensure that his design is in-line with material, process, post-process, and inspection requirements. Up-skilling and Ongoing Training Is Needed for Industry Professionals as Growth Continues As the technology is rapidly evolving, continuous learning is really important to stay relevant. Up-skilling, re-skilling, and cross-skilling are required for the AM workforce to be continuously updated to adapt with the latest advancement in technology. Course Work Covering End-to-End Process Chain Is Required with Multidisciplinary Exposure Different elements of engineering are applied in additive manufacturing technology, from design to materials to qualification and certification. Therefore, course work needs to address all these elements in the AM end-to-end process chain. An integration of interdisciplinary knowledge is required for the successful implementation of AM.

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Hands-on Training with Real-Life Problems Makes the Understanding Faster Exposure to the actual working of the technology is required through hands-on training. Training centers cannot afford to procure industrial-grade AM machines needed to provide the training. Apprenticeships or on-the job training programs are required to fill this gap. Training Programs Tailored for IndustrySpecific Needs Industry-based training programs that are time-sensitive and focused on a defined set of requirements to assist industry competitiveness need to be developed. One of the most common barriers for the adoption of AM across different industry sectors is a lack of appropriate skills in design, production, materials, and testing [6]. To address the above gaps in AM education, different AM stakeholders need to collaborate on developing courses aligned with the industry requirements.

52.3

Current AM Education and Workforce Development Landscape

AM education and workforce development programs are becoming crucial to develop a talent pool that can support the industrialization of technology. Understanding the need for a well-trained and capable workforce for AM, several organizations are now offering training programs covering various aspects of AM. This session focuses on how the AM education is provided at different levels within the AM ecosystem. AM education is needed for those who are currently in universities for academic degrees and those who are in the workforce. There are two approaches generally followed in providing AM education: continuing education (CE) and higher education. In addition to that, AM training is also offered through vocational education. Continuing education programs are aimed at working professionals to advance their knowledge and enhance their skills. Continuing education is offered by universities and professional bodies, often with the support of government agencies. The courses offered under CE are short term in nature ranging from a couple of days to few weeks that lead to certificates and diplomas. Large corporations prefer to train their employees through this mode due to favorable period that offers the least disruption to their work, either through internal training or by collaborating with external training organizations. Since AM is growing rapidly and to support such growth, short-term courses through continuing education are the way to accelerate the development of an AM talent pool. Various organizations now offer courses that focus on different AM

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competency levels, role-based skill sets, and industry-specific requirements. Course offered by institutes of higher education leading to academic degrees is another path for AM education. AM topics are often integrated into the major degree curricula as additional syllabi or technical elective courses, often leading to a minor or an academic certificate. For example, students pursuing a bachelor’s or master’s degree in mechanical engineering will learn a few modules on AM in core courses or can select an AM related course as an elective for their major. Elective offerings are attractive because non-engineering students such as business students can also select an AM elective to understand more about emerging technologies along with the market opportunities. As such, several universities now offer master’s program in additive manufacturing or in advanced manufacturing that covers AM topics to keep up with the growing demand for higher education in such emerging fields. AM competency training programs typically cover basic, intermediate, and advanced level courses. The basic level courses are for those with no previous exposure or knowledge in additive manufacturing and would cover general additive manufacturing processes, applications, advantages, limitations, and concepts of the additive manufacturing workflow. The intermediate level courses cover a much deeper body of knowledge covering aspects such as using additive manufacturing with other technologies in the process chain, concepts of improved product design using the unique capabilities of AM, and the knowledge required for managing the end-to-end AM process chain. The advanced level course is meant for AM engineers who intend to dive deep into different elements of the AM process chain, and are capable for the execution of concepts and skills in AM material selection, design, data preparation, processing, inspection, and quality control. Training programs focusing on specific skill sets required for AM process chain are essential. Among those skills, design for AM (DfAM) is among the most popular ones. Hence, a significant number of course offerings available from different parts of the world are focused on DfAM. This is quite natural because the unique differentiator that AM is having as compared to conventional technologies is the “design freedom.” However, after obtaining an understanding on designing parts using AM design concepts, it is required to manufacture, inspect, and qualify the parts before using them in applications, specifically the safety critical ones. Therefore, there are other roles pertinent to carry out specific tasks or functions in AM. Roles such as AM Operator, AM Technical Manager, AM Quality Engineer, and AM Safety Manager are a few requiring immediate attention. Training programs also should focus on the specific needs of an industry sector. Although the fundamental concepts of AM technology as applied to different industry sectors are the

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same, there are differences unique to the industry that needs to be addressed, such as corrosion properties for marine and oil and gas, biocompatibility for medical applications, and light-weighting for aerospace and automotive industries. These efforts are needed to concentrate on sector-specific topics, where AM has valuable applications, and develop courses that provide the necessary, sector-specific skill sets. One of the key challenges in training the workforce for AM is that the technology is evolving at a fast pace and the knowledge acquired today might need to be updated in a relatively short time frame. Therefore, the training programs need to be continuously updated with the latest developments, and the workforce also needs to be aware of these changes and quickly adapt them.

52.3.1 Education and Workforce Development (E&WD) Roadmaps In an attempt to understand the E&WD landscape and as part of developing its strategic roadmap for E&WD, ASTM International Additive Manufacturing Center of Excellence (AM CoE) conducted an extensive analysis in 2020. The landscape analysis reviewed a wide range of E&WD offerings and activities, including academic courses, training workshops, online modules, and certificate programs from organizations around the globe. In total, over 200 activities from more than 100 organizations were identified. Some of the key outcomes from that analysis were: 1. Universities and training organizations are beginning to develop E&WD programs, both as in-person and online formats. The programs are also geared towards training an emerging workforce in addition to up-skilling the current workforce. 2. These programs tend to focus on teaching technologies in a general context rather than targeting specific sectors. Similarly, there is a lack of training programs that targets specific roles and provides the necessary skills to perform those roles properly. 3. There is a lack of public-private partnerships in developing and delivering training programs to address current and projected needs. 4. Most developed training programs are equivalent to the proficiency of associate degrees, which makes the skill sets obtained noncompetitive against a workforce formally trained or with an advanced degree. The Skills Strategy Roadmap published by the SAM Project [7] identifies the current challenges in education and workforce development in additive manufacturing, and proposed actions and activities to be implemented for feasible solutions to the challenges. The key challenges identified in the report are:

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1. Mismatch between industry need and education and training offerings 2. Competition for skilled AM workers and lack of knowledge of AM from existing workers/students 3. Shortage of training centers, especially at vocational education and training level, capable of delivering AM training 4. Sector- and process-specific requirements for AM professionals 5. Fast-evolving technology and industry 6. Lack of AM awareness among the younger generation 7. Necessity of more infrastructure for AM training.

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The 2020 pandemic situation (i.e., COVID 19) created new opportunities for expanding AM training across the borders and thereby reaching out to broader audience. Training provided through virtual platforms made it accessible to anyone from any part of the world, and on-demand courses offer the flexibility to learn at any individual’s pace. Many training organizations now offer AM courses through digital platforms. In order to accelerate the implementation of AM, a knowledgeable workforce that can cater to different needs of industry is inevitable. This can be achieved through dedicated efforts in developing and implementing comprehensive AM workforce development programs.

The proposed actions in the report include:

52.4 1. Strengthen the collaboration between industry and training organizations 2. Tackle the lack of AM personnel at the European level 3. Prepare European, national, and regional organizations to tackle the challenges of AM, in terms of qualified personnel 4. Tackle the diversity of sectors and applications of AM 5. Update constantly the AM European workforce 6. Prepare the future workforce 7. Leverage on existing funding programs and mechanisms America Makes has developed an AM workforce and education roadmap [8] to identify measurable and meaningful challenges that need to be addressed. This roadmap is an outcome of series of interviews with different AM stakeholders. The roadmap identifies five focus areas for training: 1. Knowledge and Awareness: To increase the AM literacy across general public, government/policy stakeholders, students at all levels, and companies interested in adopting the technology 2. Competency and Skills: To increase the proficiency of current users and students at all levels through classroom-based learning, instructor labs, and fab labs 3. Industry Experience: To strengthen and apply additive manufacturing knowledge and skills through internships, apprenticeships, application-specific training, and industry experience accelerators 4. Individual Advancement: To ensure and grow a stable pipeline of talent by developing tools that link students and industry participants to employer needs 5. Scale and Diffusion: To help drive the rate and scale of adoption of AM by ensuring the consistency and integration of knowledge, skills, and experience and developing efficient channels of distribution All the above roadmaps clearly identify the need of focused training to develop a strong workforce to drive the adoption of AM.

Driving AM Industry Adoption Through Education and Training

While many industries have been experimenting with AM for years, the level of adoption for many industrial applications such as in aerospace, medical, marine, and oil and gas is far short of AM’s current capabilities. To overcome the economic and technical challenges in AM industry adoption, an experienced workforce having a practical understanding of the AM processes, which can reduce the development time and cost, is really important [9]. There is a growing demand for highly skilled AM professionals with a multidisciplinary and more comprehensive skill set covering aspects such as materials procurement, design, machine operation and maintenance, post-processing, testing, quality inspection, supply chain, and project management [10]. This points to the fact that a workforce having a thorough understanding of every aspect of the AM value chain is crucial for its industrialization. In an AM workflow, the process could begin with an application engineer interacting with the customer to capture all the product requirements. The application engineer should be able to understand and capture all the requirements from the client to the highest possible levels of detail and can advise the client to get any missing information to fabricate the part with the required level of quality. Then there should be a seamless flow of information down to the process chain comprising personnel who can perform different functions. The roles to perform these functions are to be well defined, such as Design Engineer, Materials Engineer, Manufacturing Engineer, Production Technician, Non-Destructive Testing (NDT) Technician, Inspection and Quality Control Engineer, as schematically described in Fig. 52.2. These different roles need to work independently and to interact with other roles. Therefore, beyond an overall understanding of the process, it is also required to have personnel with expertise in specific roles. Competency levels need to be defined to carry out such roles with a detailed description of the responsibilities and the expected activities behaviors. For example, an AM Materials Engineer should have a broad knowledge of the end-to-end

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Fig. 52.2 Typical roles in an AM workflow

AM process, with a focus on materials. He should specialize in the safe sourcing, testing, storage, handling, controlling, reusing, and recycling of materials for AM. Another key requirement that needs to be met for all these roles is to understand the qualification and certification needs, and how to make use of the standards to achieve qualification and certification. Training and education is the backbone of any quality system. An organization needs to demonstrate that they have qualified and experienced personnel who can develop and manage a quality system efficiently. Another gap to be addressed is the lack of technical knowhow in using AM by other domain experts. For example, in the medical sector, a surgeon may not have the proper knowledge in handling 3D printing software and hardware. On the other hand, a 3D printing engineer has the expertise in handling the technology but may not understand how the technology can be best utilized for the health care applications. Thus, cross-domain expertise is needed to implement AM in such scenarios. A successful approach to build a strong AM workforce is through public-private partnerships [11]. Organizations that work in silos to train the workforce are not sustainable in creating a talent pool. Organizations need to interact with each other to understand the E&WD needs so that they can develop a curriculum that would address the common requirements of the participating organizations. Through this collaborative approach, a long-term sustainable workforce talent can be created that could cater to all job levels from entry level to middle and senior level within the AM sector.

52.4.1 Certified AM Professionals As AM moves towards industrialization, qualified AM professionals who can demonstrate their ability to perform in specific roles are essential for any AM production site. Since

workforce is one of the variables in the AM process chain to achieve AM product certifications, the individuals who fabricated the product should have proven credentials for their job to ensure that the parts can be repeatedly produced within the specified level of quality. Third-party certification bodies offer personnel certification programs based on published international standards. One such standard published recently is ISO/ASTM 52942:2020 [12]. This standard specifies requirements for the qualification of operators of laser metal powder bed fusion machines for AM in aerospace applications. The scope of this standard is sector specific to aerospace; however, other personnel certification standards are currently under development that are industry agnostic.

52.5

Skills-Based Training for AM

AM is a unique technology that requires skilled workers. AM is also a horizontal manufacturing process that cuts across many industries such as aviation, spaceflight, automotive, energy, and maritime. This presents an opportunity for all existing workforce in these industries as well as underemployed and unemployed individuals to upskill and/or reskill in AM. For these reasons, a skills-based training curriculum is needed.

52.5.1 The Need for Skills-Based Training in AM AM is an emerging technology that requires a workforce with a unique set of skills. Due to the multidisciplinary nature of the AM technology, acquiring AM skills requires a structured skills-based curriculum in order to learn the art of AM. Access to a skilled workforce is key for organizations to remain competitive and continuously build deep

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technology capabilities, particularly in AM, as it creates new opportunities for growth in adjacent technologies in the grand scheme of advanced manufacturing. Yet, the profile of this workforce is uncommon and is not always available when the need arises from the industry. Existing training for such a skills intensive technology from conventional educational institutes is usually inadequate because the focus is on theoretical and fundamental knowledge, and coupled with the long course duration, this training is not always suited to the immediate needs of the industry.

52.5.2 Skills-Based Training Matrix The above understanding represents the need to adopt a structured skills-based training program and develop a training matrix that fulfills different skill sets at different levels, for different roles, depending on existing skills and experience. One example of such matrix is shown in Table 52.1. This example suggests an entry requirement of 2–7 years of related work experience in the manufacturing sector to qualify for the intermediate level. The candidate is then staged to progress to the advanced level (indicated with the green arrows). In another example, a fresh graduate with a major in chemical engineering can assess his/her interest and strengths via profiling tools and sign up for the basic skills course as an AM Design Engineer, for instance. This fresh graduate can then progress to the next level or choose to do a direct lateral movement (indicated in orange arrows) to take up a basic course in process and materials. Such is the flexibility a skills-based training model that is presented here, because both pathways allow the candidate to either

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progress towards the technical and engineering track and become the specific domain expert or progress onto the management track. One such approach that can be adopted is online learning. This method is becoming more popular and readily accepted during the COVID-19 pandemic.

52.5.3 Skills-Based Training for Different Populations AM is uniquely positioned within the skills-based training framework as it opens up opportunities for the existing workforce and addresses different populations to re-skill, crossskill, upskill, and apply continuous learning. Figure 52.3 shows an example of a skills training framework developed by ASTM International Additive Manufacturing Center of Excellence (AM CoE) where different category of populations served are recommended. The less privileged usually refers to the group of underrepresented minorities. For instance, an army veteran with interest in AM can get to know AM better by applying continuous learning by attending webinars as well as e-learning. Continuous learning is a compelling concept as it provides this group of population the opportunity to learn new technologies. Coupled with their work experience, they can be reskilled to levels that make them completive in the highskilled AM job market and provide an opportunity to join the AM industry as an equipment technician or operator. While re-skilling is designated to unemployed and underemployed, it can also apply to other populations. From the previous example, the fresh graduate has embarked onto the journey of re-skilling by picking up new skills in AM. The

Table 52.1 Example of a skills-based training matrix for different levels and different roles

Levels Roles Process and materials engineer Design engineer Quality engineer Facilities and safety engineer Equipment and maintenance technician Lateral movement Skills and experience dependent

Basic (unrelated work experience)

Intermediate (2–7 years of related work experience)

Advanced (7+ years of related work experience)

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Additive manufacturing skills training framework

Populations served Unemployed and underemployed Re-skilling

Incumbent workforce

Less privileged

Up-skilling & cross-skilling

Continuous learning

Fundamentals certificate course

Role based certificate courses

Modular, stackable

Personnel certificates

Introductory courses Webinar series E-learning

Academic degrees Short term programs Personnel certificates

E-learning Webinars

Fig. 52.3 Example of an AM skills-based training framework

candidate can undergo up-skilling in a specific domain of interest and advance in their current professional role. For this reason, the skills-based courses are designed to be modular and stackable, depending on needs, skills, and experience. Hence, the entry requirements are considered under the skills-based matrix. Finally, this candidate is also able to undergo cross-skilling across various roles in AM. For this reason, up-skilling and cross-skilling is ideally applied to the incumbent workforce.

52.6

The Role of AM in Advanced Manufacturing

Physical systems & infrastructures

Cyber systems & infrastructure

• Additive manufacturing

• AI & machine learning

• Robotics & automation

• Cybersecurity • System integration

Advanced manufacturing is achieved with the convergence of emerging technologies in both physical and cyber infrastructures and systems under Industry 4.0. Emerging technologies under physical infrastructures and systems refer to hardware systems, AM, as well as robotics and automation, whereas emerging technologies under cyber infrastructures and systems refer to technology domains such as cybersecurity, big data, industrial internet of things, and artificial intelligence and machine learning. AM plays a critical role in advanced manufacturing as it produces physical parts from digital data, fulfilling the concept of digital manufacturing.

52.6.1 Advanced Manufacturing and Industry 4.0 The different emerging technologies enable advanced manufacturing under Industry 4.0 (i4.0). i4.0 has been slated to

• And beyond

Fig. 52.4 Integration of cyber-physical systems and infrastructures

be the fourth industrial revolution, entering into a digital era of integration and interconnectivity of cyber-physical systems shown in Fig. 52.4. With the advent i4.0, advanced manufacturing can be adopted across the manufacturing industry in diverse industry sectors. The movement is real, as many governments around the world have already started to capture new growth opportunities in adjacent technologies for advanced manufacturing by focusing on and allocating resources dedicated to i4.0. The objectives are to innovate, create sustainable economic growth, build business vibrancy, and create job opportunities. The global manufacturing industry is valued at more than $12 trillion annually [13] and this presents the market that AM can potentially address.

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52.6.2 Advanced Manufacturing and AM The progress and adoption of advanced manufacturing largely depend on the convergence of other adjacent emerging technologies. While i4.0 involves several different emerging and advanced technologies such as artificial intelligence, big data, and the Internet of Things, it is widely recognized that AM remains the cornerstone and the catalyst for advanced manufacturing. Firstly, AM is considered as a green manufacturing technology that promises to minimize environmental impact [14] by reducing waste and hence it helps achieve the goal of sustainable manufacturing in advanced manufacturing. For example, AM has a higher material utilization compared to traditional machining [15]. Secondly, AM is perfectly suited for on-demand manufacturing, fulfilling the concept of digital warehouse where no physical inventory is required. This is only possible because there is, in theory, no minimum order quantity (MOQ) and no need for tooling (mold, dies, jigs, and fixtures). Next, AM is flexible. It is well positioned to produce customized products in a semiautomated less laborious fashion while digital files and equipment can be controlled remotely, facilitating the concept of lights off factory. Yet, AM is at the same time scalable, bringing advanced manufacturing to the next level. Finally, AM is well positioned to integrate readily with adjacent technologies. For instance, the establishment of a new subcommittee on data under the ASTM AM F42 committee in 2020 [16] as well as a funding from America Makes on the development of AM Cybersecurity in 2021 [17] reveal the adjacencies and dependencies of emerging technologies and how they can be deployed and utilized to seed growth in advanced manufacturing. For these reasons, AM is sometimes loosely and commonly referred to as digital manufacturing and/or advanced manufacturing. With this understanding, it is hence important to highlight and associate the link between AM training and advanced manufacturing. The training on cybersecurity for AM, for instance, will require specific cybersecurity training content and how it is utilized in AM for advanced manufacturing. In a similar fashion, other training on adjacent technologies can be utilized in AM and applied onto advanced manufacturing. Training and education become a facilitator for industry to relate to the convergence of adjacent emerging technologies with AM for advanced manufacturing.

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role is to prepare a work ready and globally competitive workforce that can expand and be cross-trained into key and high growth areas that are closely associated to AM and beyond. A good foresight involves planning ahead for training skilled workers in AM who can integrate and transit smoothly into advanced manufacturing. One example is the establishment of a government-led public-private partnership, a partnership that offers grants and incentives to develop and deliver AM training programs, addressing current and projected needs for different groups of the workforce. For example, details of the people who are unemployed can be obtained from state government boards under the coordination of this program. This data can further assess and map their interests to a specific AM role based on their prior skill sets and employment history. In essence, the public-private partnership has two benefits for the majority of the existing workforce (incumbent, unemployed, and underemployed): (1) companies are incentivized and encouraged to reskill, upskill, and cross-skill their workforce and (2) unemployed trainees are potentially provided employment opportunities in organizations that are part of the public-private partnership. Industry and academia also play an important role in order to realize the public-private partnership. For industry, besides being able to offer re-skilling, up-skilling, and cross-skilling to their own employees, the same organization can utilize grants from the government and provide enterprise-based training through programs such as internships and apprenticeships in AM for the unemployed and underrepresented minorities as well as college/university students. Such programs demonstrate some level of success when the trainee is hired into the company that is providing the training or internship program. For academia, the role in such a partnership is to develop the AM skills-based curriculum to train trainees in schools before they progress to the internship or apprenticeship within the industrial partners. The results from the R&D projects conducted on AM technologies from academia can also be utilized to develop robust teaching content. The essence of associating R&D with education in AM allows for the development of an applied and skills-based training center that can offer experiential learning and continuously stay at the forefront of technology. Generally, a workforce AM program designed and developed in collaboration with all three stakeholders will ensure that the workforce training and talent produced through this program are of the highest standard, propelling the domestic acquisition of AM skills to international superiority.

Role of AM Stakeholders in AM Training 52.8

There are mainly three categories of stakeholders: government, industry, and academia for AM training. The government plays the most important role in manpower capability development planning in a high growth sector such as AM in order to ensure a sustainable and inclusive growth. One such

Summary

This chapter covered the need for training and education in the wider adoption of AM and how this can be achieved through different methods with the involvement of various AM stakeholders.

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Demonstrate capabilities Education & training can be used to demonstrate capability & increase quality in industry Demonstrate Develop education & training Currently there are gaps in education & workforce development - These are being closed

Develop

Grow future workforce Rapid growth of AM requires rapid growth of trained personnel

Upskill existing workforce Grow

Upskill

Increase skills of existing workforce to understand AM, design for AM, business cases, etc

Fig. 52.5 Training structure for AM industrialization

Additive manufacturing education programs are growing across the globe through different entities, such as universities, professional bodies, and solution providers, and are becoming the pipelines for the future AM workforce. A series of initiatives are on the way from different organizations such as ASTM International, America Makes, and the European Welding Federation, to identify the education and workforce development needs and strategize the deployment of appropriate training programs to fill the skills gap. It is essential to bring education and industry closer together to realize the adoption of AM across various industry sectors. For that, a training structure needs to be developed with a holistic approach to supporting AM industrialization (Fig. 52.5). This can be achieved by implementing training at different levels, starting with growing a future workforce in tandem with the rapid growth of the technology and up-skilling the existing workforce to acquire the right skill sets for AM. The next level is to identify critical gaps in education and training and fill the gaps through developing appropriate education and training programs that are technology-specific, skill-specific, and sectorspecific. Finally, the outcome of any training program is to improve performance. Performance should be demonstrated through capability improvements and establishing quality in the industry. As AM involves the elements of multiple technology domains and needs to interact with adjacent technologies in the larger concept of advanced manufacturing, the training programs should also focus beyond the AM technology.

References 1. Pei, E., Monzon, M., Bernard, A. (eds.): Additive Manufacturing – Developments in Training and Education. Springer International Publishing AG (2019) 2. Despeisse, M.T.: Despeisse M, Minshall T. Skills and education for additive manufacturing: a review of emerging issues. In: IFIP Advances in Information and Communication Technology, vol. 513, pp. 289–297. Springer New York LLC (2017). https://doi.org/ 10.1007/978-3-319-66923-6_34 3. Deloitte Insights: 3D opportunity for the talent gap. https://www2. deloitte.com/uk/en/insights/focus/3d-opportunity/3d-printing-tal ent-gap-workforce-development.html 4. Byron, et al.: Metal additive manufacturing in aerospace: a review. Mater. Des. 209, 110008. https://doi.org/10.1016/j.matdes.2021. 110008 5. Kirchheim, A., Katrodiya, Y., Zumofen, L., et al.: Dynamic conformal cooling improves injection molding. Int. J. Adv. Manuf. Technol. 114, 107–116 (2021). https://doi.org/10.1007/s00170021-06794-0 6. 3Dprinting.com: The skilled workforce the additive manufacturing industry needs. https://3dprint.com/255430/the-skilled-workforcethe-additive-manufacturing-industry-needs/ (2019) 7. SAM-Skills Strategy Roadmap 2021 D4.10. Project No. 601217EPP-1-2018-1-BE-EPPKA2-SSA-B 8. Workforce and Education Roadmap: https://www.americamakes.us/ workforce-education/ 9. Additive Manufacturing: Implications for Technological Change, Workforce Development, and the Product Lifecycle Available: https://workofthefuture.mit.edu/wp-content/uploads/2020/11/2020Research-Brief-Quinlan-Hart4.pdf 10. Deloitte: 3D printing and higher education | Deloitte Insights, 2019. [Online]. Available: https://www2.deloitte.com/uk/en/insights/ focus/3d-opportunity/additive-manufacturing-highereducationdegree.html 11. https://www.realclearpolicy.com/articles/2019/08/30/in_austin_a_ publicprivate_partnership_for_workforce_success_111266.html

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12. ISO/ASTM 52942:2020. Additive manufacturing — Qualification principles — Qualifying machine operators of laser metal powder bed fusion machines and equipment used in aerospace applications 13. https://www.kearney.com/operations-performance-transformation/ article?/a/3d-printing-disrupting-the-12-trillion-manufacturingsector 14. Faludi, J., Van Sice, C.: State of knowledge on the environmental impacts of metal additive manufacturing, 2020., https://amgta.org/ wp-content/uploads/2021/01/State-of-Knowledge-on-the-Environ mental-Impacts-of-Metal-Additive-Manufacturing.pdf 15. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4487298/ 16. https://www.astm.org/COMMIT/SUBCOMMIT/F4208.htm 17. http://www.eng.auburn.edu/news/2020/12/america-makes-amcyber-award.html

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Paul Bates is an Additive Manufacturing Lead Project Engineer for the ASTM International Additive Manufacturing Center of Excellence. In his role, he brings his technical expertise to drive the projects in AM training, safety, and certification. He is an industry-recognized AM veteran. He has more than 25 years of additive manufacturing experience and fluent in numerous AM processes, including PBF, BJT, FDM, and MJ. He received the Additive Manufacturing Users Group (AMUG) DINO Award in 2012. He was a Past President of the AMUG. Bates can be reached by email at [email protected].

Khalid Rafi is the Senior Additive Manufacturing Program Development Lead at ASTM International for the AM Center of Excellence. His primary focus is to develop programs on AM education and workforce development and programs on standardization and certification. He has more than 12 years of experience in additive manufacturing, performing research, and training. He has coauthored more than 26 publications in peer-reviewed international journals and has made more than 50 presentations in conferences, symposiums, and trade shows. Rafi can be reached by email at krafi@astm.org.

Alexander Liu is Head of Advanced Manufacturing Programs, Asia region at ASTM International, responsible for ASTM AM center of excellence (CoE) and various AM programs in Asia. He has more than 14 years of experience in additive manufacturing with a primary focus on process and materials characterization. He has coauthored 15+ peerreviewed publications with 50+ invited and keynote presentations at various technical meetings. He has also received a total of 10 awards and patents in additive manufacturing. Liu can be reached by email at [email protected].

Nima Shamsaei is currently the Philpott-WPS Distinguished Professor in the Department of Mechanical Engineering at Auburn University, where he is also the founding director of the National Center for Additive Manufacturing Excellence (NCAME). His research work on fatigue, fracture, mechanics of materials, as well as qualification, certification, and standardization of additively manufactured metallic materials has resulted so far in publishing over 270 peer-reviewed journal articles and conference proceedings as well as 130+ technical presentations including 60+ invited talks or keynote/plenary speeches. Shamsaei can be reached by email at [email protected].

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Mohsen Seifi is the Vice President of global advanced manufacturing programs at ASTM International responsible for the AM center of excellence and various AM programs while leading a team of technical experts in the field. He has 10+ years of experience in additive manufacturing and coauthored 40+ peer-reviewed publications on AM presented 60+ invited and keynote lectures at various technical meetings. He has an appointment as an adjunct faculty at Case Western Reserve University. Seifi can be reached by email at mseifi@astm.org.

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Contents 53.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 893

53.2

Success with AM: Meeting Requirements with AM . . . 894

53.3

State of AM Education and Training at US Universities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 896

53.4

AM Training in Professional Societies and Standards Development Organizations in USA . . . . . . . . . . . . . . . . . . . 898

53.5

Implications of AM Education and Training Offerings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 898

53.6

Assessing AM Readiness Across the Organization in Processes, Materials, and Design . . . . . . . . . . . . . . . . . . . . 899

53.7 53.7.1 53.7.2 53.7.3 53.7.4 53.7.5 53.7.6

Quality of AM Education and Training Offerings . . . Consistency – IP and Ownership . . . . . . . . . . . . . . . . . . . . . . . . . Experience – AM and Instructors . . . . . . . . . . . . . . . . . . . . . . . . Value – Using AM and ROI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Content – Agnostic and Unbiased . . . . . . . . . . . . . . . . . . . . . . . . Pedagogy – Learner Focused . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Assessment – Show It and Prove It . . . . . . . . . . . . . . . . . . . . . .

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Closing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 902

900 901 901 901 901 902 902

United States reveals a plethora of courses on AM processes, materials, and design for AM, with relatively few courses on the economics, qualification, and broader industrialization of AM. This gives rise to a disparity of knowledge about what is feasible and could be made with AM versus what is viable and should be made with AM. The implications of these findings along with metrics for assessing the quality of AM education and training are provided, and an AM Readiness Scale is offered to help companies track their progress in four areas – materials, machines, digital, and people – as they begin their AM journey. Keywords

Additive Manufacturing · Design for Additive Manufacturing · Training · Education · Standards Development Organizations

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 902

53.1 Abstract

Producing parts with additive manufacturing (AM) requires an understanding of the entire AM workflow to ensure that parts can be successfully qualified and certified for end-use. Based on this workflow, AM training and educational needs can be identified and compared based on offerings that are now available through universities, professional societies, and standards development organizations. An analysis of the degrees, programs, and certifications offered by organizations in the J. E. Barnes (*) TBGA, Sewickley, PA, USA e-mail: [email protected] T. W. Simpson State College, PA, USA

Introduction

The terms “Training” and “Education” are often used synonymously, yet they are very distinct offerings with different intended outcomes. Education is about the learning and the process of learning new knowledge. Training is about the attainment of a skill and is focused to a specific topic or trade. Both are important and crucial in additive manufacturing (AM), and in this chapter we examine the options for AM education and training considering the topics that are essential to be covered. To be clear, the goal is to describe overarching themes important to AM, not the content itself as there are entire books available on different AM technologies and design for AM (see, for example, [1–4]). Our approach in this chapter is to work backwards from the requirements necessary to produce an AM part. Typically, this is in the form of whatever qualification or certification event may be required for the product that is being made. We

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_53

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are all familiar with the technical elements that need to be established, but often we forget about the commercial components such as cost. By highlighting “what must be true” first, we illustrate a process to get to the goal relative to what training and education is available. From there we review the entire workflow for an AM part, including essential elements like designing for AM which should start at the concept phase and conclude at certification. To do this requires a thorough understanding of the materials and processes that will be employed in final part production with AM. It may be helpful to think about what a specification might need to include to ensure consistent and safe operation to meet the requirements. For instance, NASASTD-6030 specifies AM requirements for spaceflight systems [5], while NASA-STD-6033 specifies AM requirements for equipment and facility control [6]. By thinking of the product lifecycle in reverse, we see that training and education for AM needs to work in parallel to facilitate each step of development. To examine the extent to which AM degree and certification programs teach these aspects, we review AM course offerings by several universities, professional societies, and standards development organizations (SDOs) in the United States. This reveals a plethora of courses on AM processes, materials, and design for AM, with relatively few courses on the economics, qualification, and broader industrialization of AM. The implications of these findings are discussed with regards to a company’s readiness to deploy AM to produce qualified end-use parts.

53.2

Success with AM: Meeting Requirements with AM

The earlier a team brings AM into project discussions, the more likely AM will succeed. Why? Because the start of the project is when the team has the most freedom to consider different alternatives for the part(s) being designed, the material(s) being used, and the manufacturing process(es) and assembly techniques being considered for production. As the design geometry is refined, as materials are selected,

Project concept

AM project

AM part

Designing for AM

AM process

and as manufacturing and sourcing decisions are made, the team faces more and more constraints that limit the options that can be employed effectively. All too often we hear of AM being considered late in the product development process (e.g., a supplier is late with a part; therefore, AM is used to produce it internally) or as part of a process substitution (e.g., make a part with AM instead of machining), and the benefits either fail to materialize or fall far short of what is expected in large part because that part has been optimized for a different manufacturing process. Figure 53.1 shows a simplified view of the stages of product development with AM considered as early as project conceptualization. This simplified overview was developed in collaboration by a team of industry experts at The Barnes Global Advisors who collectively have more than 125 years of experience deploying AM in more than a half-dozen different industries. The team has found that the requirements that define the project are the same whether AM is used or not. This should not come as a surprise: AM is simply another means to satisfy requirements, albeit with new shapes, materials, and fabrication processes when compared to what conventional manufacturing allows. The requirements influence which AM process(es) and material(s) are viable options for realizing a concept, much like any other manufacturing process, and designers should be sure to consider using AM in combination with other conventional manufacturing processes to realize a solution as that might be the best route to success. While the specific implementation of the following steps will differ for each combination of AM process and material, the remaining discussion is intended to be general to the AM workflow and provide sufficient scope for comparing AM training and education offerings available in US universities, professional societies, and SDOs. As concepts are generated, AM-enabled solutions may emerge, leading to an AM project if selected for further development. An AM-enabled solution is one that is viable with AM and may be difficult, if not impossible, to make with conventional manufacturing. Such examples include complex lattice structures, bioinspired organic shapes, and multi-material parts with tailored properties, to name a few.

AM build

Postprocess

Producing with AM

Fig. 53.1 Simplified view of the stages of product development with AM. (Source: The Barnes Global Advisors)

Test & qualify

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While AM is certainly a feasible option to create conventionally shaped parts, AM is likely not the most viable option for their production when cost is paramount. Making a simple L-bracket, a bent hollow tube, or a solid axle for a gear shaft can be done much more quickly and cheaply via conventional means than with AM. Consequently, AM should be considered as one of the many manufacturing alternatives available for producing parts; AM is rarely an either-or situation. The distinction between feasibility and viability is an important consideration for AM. Understanding what problem is being solved is tantamount to the value proposition. It is often the case that the value being brought by AM is a cost reduction, in which case we are fairly astute at building a business case. We must also consider the disruptive cases like elimination of spare parts, distributed manufacturing, and even perhaps societal benefits like CO2 emissions. It can be easy to think about these broad value proposition categories in project management terms: Schedule, Scope (performance), and Cost. When cost is the key consideration, just like requirements are still requirements, cost is still cost, and an AM part must be economical to make, just like any other part made any other way. A company may be willing to spend more on the first AM part it produces to validate the workflow, gather test data, or demonstrate the feasibility of an AM part to senior management. Such “pathfinder” parts are essential to help “de-risk” AM as a company starts to gain confidence in AM, or any new technology for that matter; however, AM “pathfinders” can be viewed as an investment in future capabilities and need not be viable the first time out. These “loss leaders” are not sustainable in the long run as end-use products and production parts must be profitable, and economics factors into the discussion in the early stages of an AM project just like any other project. Schedule plays an equally important role when establishing a new AM project, again just like any other project. There are two primary differences though with AM. The first difference is the perception of increased risk, whether real or unfounded, which tends to add schedule through additional experimentation, testing, and analysis. While some of this extra work is necessary now given the current state of AM, this will decrease as the industry matures and data becomes more readily available. In the meantime, companies that leverage this learning from one project to the next will accelerate their AM adoption in comparison to others and benefit more and more as their AM experience grows. This is a key tenet that is overlooked in the majority of AM education and training initiatives today. While perceptions of risk with AM can add schedule, AM can also save schedule. This is often where companies benefit most when adopting AM late in a project (e.g., another task is behind schedule, a component is late from a supplier) as AM gives project managers another “lever” to adjust the critical path during product development. The ability for AM to

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create functional prototypes and parts (relatively) quickly is another key differentiator of many AM processes. With the project scoped, the AM part(s) can now be designed to meet the requirements. The requirements are critical for AM projects just like any other project; AM just allows new and unique shapes and geometries to be realized with materials that may be overlooked or not considered when using conventional manufacturing processes. The weight or prioritization of requirements may change slightly for an AM project as new capabilities become unlocked. For example, weight reduction will always be of primary concern in space applications; however, a lightweight lattice structure may enable a denser or more expensive alloy to be used because less material is needed (or removed) when using AM compared to a subtractive process. This has led to a plethora of new 3D modeling tools and enhancements to commercial computer-aided design (CAD) software, which has created high demand for AM training and education in what is referred to by many as Design for AM (DfAM). It is easy to relate DfAM as anything that adds value to an AM part whereas we refer to anything that saves cost as MfAM (Modify for AM). MfAM is the AM equivalent of traditional DFM (Design for Manufacturing) wherein the part geometry is modified to overcome limitations or mitigate constraints associated with a manufacturing process. For instance, when using AM, layering effects may increase surface roughness on sloped surfaces, tessellation effects may create dimensional inaccuracies, or overhanging structures may require support structures – all of which require additional post-processing that add time and cost to the finished part. This is why it is important when Designing for AM to take both the AM part and the AM process into consideration as shown in Fig. 53.1. Many companies fail to do this, separating those designing for AM from those manufacturing with AM. This creates the much maligned “throw it over the wall” approach, which leads to costly iterations, rework, and project delays. Once the part is designed and prepared for build, production starts. The AM part is built with the selected AM process and material feedstock and then post-processed as needed to satisfy the design requirements. Build time, cost, and quality are dictated largely by the processing parameters used for specific AM technology (e.g., laser power, scan speed, and spot size for a laser powder bed fusion system). Likewise, post-processing requirements are driven by the process as well as the resulting material, both of which are driven by the requirements. For instance, stress relief, heat treatment, support removal, and finish machining may be necessary for a metal AM part made with laser powder bed fusion whereas a metal AM part made with binder jetting may require curing, sintering, and infiltration with media blasting or tumbling. Again, requirements drive the production requirements, which ultimately drive the cost of the AM part. Cost comes into sharp focus when in the Producing with AM phase.

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Testing and qualification remain critical in the final stages of AM production. Given the lack of widely available materials data, for instance, test specimens and witness coupons are often built alongside the part(s) to provide additional data for quality assurance and control. Such destructive testing helps reduce risk and increase confidence in the AM process and specific system being used for production, and it is unavoidable at this point in the evolution of AM. Likewise, non-destructive evaluation (NDE) techniques such as x-ray computed tomography (CT) scanning are being employed extensively for AM part production. Volumetric inspection techniques such as CT are combined with other dimensional inspection techniques (e.g., 3D scanning, metrology) to ensure that part requirements are satisfied, and destructive testing of actual AM parts is conducted as necessary. In the end, concurrently developing AM design knowledge with AM process knowledge is essential for companies to succeed with AM. Understanding the process-structureproperty relationships associated with each AM process is best accomplished with a multidisciplinary team with depth in engineering and design, materials science and metallurgy, and manufacturing and process engineering, to name a few. The more interactions the different team members can have the earlier in the project, the better the potential outcome, and the higher the chance of success. Integrating other experts early into this discussion (e.g., sourcing, testing, quality assurance, certification) will further increase the likelihood of success for any AM project, and it is important to foster this mindset during any AM training or educational activity. It is highly unlikely that any one person can be an expert in every aspect of AM given the breadth and state of the technology – and its rapid advance as it continues to evolve.

53.3

State of AM Education and Training at US Universities

AM education and training has kept pace with the technology as it has advanced, and dedicated courses on 3D printing and additive manufacturing can be found in most engineering Fig. 53.2 AM workflow converts a 3D solid model into slices that are built layer-by-layer to create a 3D object

degree programs in the U.S., at both the undergraduate and graduate level [7, 8]. Such courses tend to cover the basics of the seven different AM processes and the AM workflow to convert a 3D solid model into a 3D object. While the basic steps in the AM workflow shown in Fig. 53.2 are essentially the same for all AM processes, the specifics of each step vary for each AM process, including finishing parts for end-use. Mastery of any AM process requires knowing these differences, however subtle, as they drive the cost, time, and quality of the finished AM part. To gain hands-on experience with AM, most courses now offer laboratory or design/project experiences with polymer 3D printers; advanced courses often introduce students to metal AM processes through carefully supervised laboratory coursework, given the material handling and safety concerns associated with metal powder feedstocks. The majority of capstone (senior) design courses use 3D printing heavily for prototyping, and lectures/labs on 3D printing are integrated into introductory manufacturing courses as well as introductory materials science and engineering courses where they are used to demonstrate process-structure-property relationships. Student clubs and projects (e.g., SAE Formula car, miniBaja) have been ardent users of 3D printing technology since it became available, and informal and extracurricular activities with 3D printing are becoming more prevalent as costs have fallen. Several universities in the USA have established graduate degree programs in 3D printing and AM. The University of Maryland (UMD) and The Pennsylvania State University (PSU) were the first to launch AM graduate programs in the USA, both in 2017. UMD offers a Professional Master of Engineering (M.Eng.) in AM for resident students, and PSU launched a resident and online graduate program that offers a Master of Science (M.S.) and M.Eng., respectively, in Additive Manufacturing & Design (AMD). Soon thereafter, Carnegie Mellon University (CMU) began a M.S. in Additive Manufacturing as well, and Ohio State University (OSU) added an AM “track” to their online M.Eng. in Global Engineering Leadership program. Colorado School of Mines (Mines) recently added a M.S. non-thesis option given growing interest in AM education.

CAD model >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>3D object

XYZ

3D CAD model

.STL file

Slicing software

Layer slices & tool path

3D printer

3D object

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Table 53.1 Summary of AM graduate degree/certificate programs at universities in the USA University CMUa Minesb MITc OSUd PSUe Purduef TA&Mg UMDh UTEPi

Program offerings MS MEng ✓ ✓

✓

✓ ✓

✓

Certificate

CEUs/PDHs

✓ ✓

✓

✓ ✓ ✓ ✓ ✓

✓ ✓ ✓

Students Online ✓ ✓ ✓ ✓ ✓

✓

Instruction mode Synchronous ✓ ✓ ✓ ✓ ✓

✓ ✓ ✓

✓ ✓ ✓

Resident ✓ ✓

Asynchronous

✓

✓

a

Carnegie Mellon University: https://www.cmu.edu/engineering/am/program-info/requirements.html b Colorado School of Mines: https://online.mines.edu/advanced-manufacturing-systems-online/ c Massachusetts Institute of Technology: https://the-amtc.co.uk/training/courses/foundation-certificate-in-additive-manufacturing/ d Ohio State University: https://mgel.osu.edu/technical-track-options/additive-manufacturing e Penn State University: https://www.amd.psu.edu/index.aspx f Purdue: https://www.eventreg.purdue.edu/ec2k/Heading.aspx?heading_id¼813 g Texas A&M: https://tees.tamu.edu/workforce-development/professional-education/additive-manufacturing-cert/index.html h University of Maryland: https://mage.umd.edu/additive-manufacturing i University of Texas-El Paso: http://catalog.utep.edu/grad/college-of-engineering/mechanical-engineering/grcertificate-3dam/

A summary of the graduate programs offered at each of these US universities is given in Table 53.1. The information was obtained directly from each website as noted in the table, and the ✓ in the table indicates what is offered. As shown in the table, UMD and PSU also offer a graduate-level certificate in AM and AMD, respectively, for students that do not want to take or complete all of the coursework for a full M. Eng./M.S. degree. Stand-alone graduate certificates are also offered by the Mines, MIT, Purdue, Texas A&M (TA&M), and the University of Texas at El Paso (UTEP). As noted in the table, the AM offerings at MIT, Purdue, Texas A&M, and UTEP award CEUs (Continuing Education Units) or PDHs (Professional Development Hours), which can be used to maintain licensure or other professional certification. This list of universities was developed based on Google searches for 3D printing and additive manufacturing programs that offer stand-alone degrees or certificates. Universities with individual courses on 3D printing or additive manufacturing were excluded from the study, and there are no stand-alone degrees at the undergraduate level at any university in the USA currently. All but two of these graduate programs are offered synchronously, i.e., they begin and end for all participants at the same time, although many allow students to proceed at their own pace during the course itself. Both Purdue and MIT allow students to sign up and start (and complete) the course as their schedule permits. This provides students with greater flexibility when learning the material; however, interaction with instructors is lower in comparison. Purdue’s online AM graduate certificate is also an exception in its origins. Its courses were developed and taught by industry experts in AM, not traditional academics. As a result, Purdue was the

first to offer a course dedicated to AM economics and AM business cases. Analysis of the AM courses offered in these graduate degree/certificate programs reveals that three types of courses have emerged as “foundational” for such programs: (1) AM processes, (2) Design for AM, and (3) AM Materials. As shown in Table 53.2, dedicated courses on these three topics appear, respectively, in 9 out of 9 (100%), 7 out of 9 (77.8%), and 5 out of 9 (55.6%) of the AM graduate degree/certificate programs analyzed. This is not surprising given the tight coupling that exists between these three areas, which is rooted in the fundamental process-structure-property relationships that many engineering and materials science programs teach. Beyond these three “foundational” courses, it is interesting to note that dedicated AM Business Case, AM Computational Modeling (e.g., integrated computational materials engineering, or ICME), AM for Biomedical (e.g., bioprinting), and AM Feedstock courses appear in one-third (33%) of these degree/certificate programs. The remaining courses listed in the table appear in at least 2 (22.2%) of these 9 AM programs: AM Polymers, Science of AM, Mechanics of AM Materials, AM for Aerospace, Quality Assurance/ Quality Control (QA/QC) for AM, and a dedicated AM Hands-On Lab course. Such specializations tend to arise based on (a) the areas of expertise among the faculty/instructors within the program and (b) availability of AM processes and equipment. This is also giving rise to highly specialized courses within individual programs. For instance, PSU offers courses on 3D Concrete Printing, AM Cybersecurity, and Legal Implications of AM while UMD offers dedicated courses on artificial intelligence (AI), machine learning (ML), and data mining for AM and 3D Printed Electronics.

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Table 53.2 Common educational course offerings in AM graduate degree/certificate programs at universities in the USA AM processes Design for AM AM materials AM business case AM Comp. modeling AM for biomedical AM feedstocks AM polymers Science of AM Mechanics of AM Mtls. AM for aerospace QA/QC for AM AM hands-on lab

53.4

CMU ✓ ✓ ✓ ✓ ✓

Mines ✓ ✓ ✓

MIT ✓ ✓ ✓ ✓

OSU ✓ ✓

PSU ✓ ✓ ✓

✓ ✓

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

Purdue ✓ ✓ ✓

✓

✓

AM Training in Professional Societies and Standards Development Organizations in USA

Professional societies and standards development organizations (SDOs) have also been creating dedicated AM training courses, either stand-alone or as part of a larger AM-related workshop or conference that they offer. A list of the AM training course offerings from the six most active organizations in the USA, namely, ASME, ASTM, SAE, SME, TMS, and Underwriters Laboratory (UL), is given in Table 53.3. Based on information available on their websites, 5 of the 11 AM training courses that are offered by two or more of these organizations are the same as those offered in the AM graduate degree/certificate programs offered by universities (see Table 53.2). These courses are noted in bold italics and include: AM Processes, Design for AM, AM Materials, QA/QC for AM, and AM Feedstocks. Training courses that are unique to these organizations include AM Safety (e.g., environmental health and safety, material handling), Non-Destructive Evaluation (NDE) for AM, AM Supply Chain, AM Best Practices, AM & Traditional Manufacturing, and AM as Secondary Process. Additional offerings that are unique to each of these programs include AM Polymers (by ASTM), AI/ML/Data Mining (by TMS), and AM Business Case (by UL) and AM Post-Processing (also by UL). UL’s AM Safety course also includes a hands-on laboratory experience with metal AM. Figure 53.3 groups all of these AM education and training courses into one figure, clustering them from top to bottom in the pyramid based on the combined frequency of occurrence. The “base” of the pyramid includes courses related to AM processes, followed by AM materials, Design for AM, and QA/QC. At the top of the pyramid is AM Business Case, a dedicated course that only exists in 4 of the 15 (26.7%)

TA&M ✓ ✓ ✓ ✓

UMD ✓

UTEP ✓ ✓

✓ ✓ ✓ ✓ ✓

Freq. 9 7 5 3 3 3 3 2 2 2 2 2 2

universities and organizations reviewed. While the economics of AM are certainly touched on in other courses (e.g., AM process courses usually discuss the costs associated with each AM technology), AM costing is arguably one of the most important considerations when implementing AM, yet it receives the least attention in current academic programs and training offerings.

53.5

Implications of AM Education and Training Offerings

Based on the clustering and ordering in Fig. 53.3, one could argue that the importance and availability of AM education and training are inversely correlated – what is needed the most is currently offered the least. Figure 53.4 confirms this by overlaying the frequency of occurrence of the different AM education and training courses on the simplified AM product development process introduced in Fig. 53.1. The majority of these course offerings cover the middle stages of AM product development, namely, AM Part, AM Process, AM Build, and AM Post-Process. The last stage (Test & Qualify) is receiving considerable attention in industry these days as more and more companies shift to using AM for end-use parts; however, markedly few dedicated offerings target the earliest stages of project conceptualization (Project Concept) and project management (AM Project). As noted earlier, the sooner AM is considered in the project, the more likely AM will deliver the value that drives the hype for this relatively new technology. Adding to the confusion is that there is no clear definition of what “good” training is in AM. What topics need to be addressed along with the structure, or levels and organizational role. This lack of definition has contributed to the current situation where the technologists talk at great length about the technology and less about the part requirements and

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Table 53.3 Common AM training courses offered by professional societies and SDOs in the USA ASMEa AM processes Design for AM AM materials QA/QC for AM AM safety NDE for AM AM feedstocks AM supply chain AM best practices AM & Traditional Manf. AM as secondary process

ASTMb ✓ ✓

✓

SAEc ✓ ✓ ✓

SMEd ✓ ✓ ✓

✓

✓ ✓

✓ ✓ ✓

✓ ✓

✓ ✓ ✓ ✓

TMSe ✓ ✓ ✓

ULf ✓ ✓ ✓ ✓ ✓ ✓ ✓

Freq. 5 5 3 3 3 2 2 2 2 2 2

a

American Society of Mechanical Engineers: https://www.asme.org/learning-development/find-course/design-additive-manufacturing-metals ASTM International, formerly American Society for Testing and Materials: https://amcoe.org/events/additive-manufacturing-general-personnelcertificate-program-online c SAE International, formerly Society of Automotive Engineers: https://www.sae.org/learn/content/pd281743/ d SME, formerly Society of Manufacturing Engineers: https://www.toolingu.com/catalog –> Search "Additive Manufacturing" e The Minerals, Metals & Materials Society: https://www.tms.org/portal/MEETINGS___EVENTS/TMS_Meetings___Events/Upcoming_TMS_ Meetings/PathwaysAdvancedManufacturing/Registration/portal/Meetings___Events/2020/learning_advanced2020/registration.aspx? hkey¼b50fc36f-e8b3-428f-b928-1844aba54865 f Underwriters Laboratories: https://www.ul.com/resources/additive-manufacturing-training-and-education b

53.6

Assessing AM Readiness Across the Organization in Processes, Materials, and Design

(2)

Design for AM (12) AM materials (8 out of 15)

(3) (2) ng eli AM od for . m ng mp ini co ta m AML/da /M

AI

QA/QC (5) AM feedstocks (5)

AM

AM AM for for biom aer ed osp ica ace l (3 (2) )

or

Ef

ND

AM business case (4)

AM polymers (3) Mechanics AM Mtsl (2) AM hands-on lab (3)

Science of AM (2)

AM processes (14 out of 15)

AM safety (3)

AM as secondary process (2) AM supply chain (2) AM & traditional manf. (2) Best practices AM implementation (2)

Fig. 53.3 Clustering of AM education and training course by frequency of occurrence

how they can be met. Consequently, we see delineation between the academically oriented organization’s content and the more industrially focused organization’s content. The good news is that basic training exists and is easily attainable online or in person. Increasingly, the content is being catered in a structured way to match the organizational role. This is a key consideration because AM is disruptive, and while full of potential value, the disruptive nature also makes it harder to digest by organizations with set processes.

As AM technology has evolved, the educational programs and training opportunities have also grown to ensure that the workforce is prepared to harness the potential of AM. With hundreds of AM introductory classes offered at universities at the undergraduate and graduate level, nearly a dozen new AM graduate degree/certificate programs established, and at least half a dozen professional societies and SDOs offering AM education and training now, students and practitioners have a wealth of options from which to choose to help prepare them for the AM workforce and advanced careers. Foundational to these offerings are dedicated courses on AM Processes, AM Materials, and Design for AM. This is not surprising given the inherently tight coupling between the process-structure-property relationships that have influenced the development of most engineering and material sciences classes. With AM, however, the interplay between these relationships is more critical than ever, especially when it comes to metal AM. With laser powder bed fusion and directed energy deposition, for instance, one is literally making the material as the part is being formed layer-by-layer in the process. Change the build orientation of the part or alter the thickness of a section, and a different material will result even though the process is not changed. Conversely, change the process parameter settings, and a different material will emerge as the microstructure evolves and phases transform. Consequently, AM is inherently multidisciplinary in its current state of maturity, and it is impossible for any one

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AM processes

AM materials Design for AM

2 2

Science of AM Mech of AM Mtls

3

AM comp modeling

3

AM polymers

2

AI/ML/data mining

3

AM hands-on lab

3

AM safety

5

AM feedstocks AM processes

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AM business case

14 8

AM materials

2 2

4

Project concept

AM project

AM part

2 2

AM build

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Designing for AM

AM as 2nd process AM & trad. manf. AM supply chain AM best practices

Postprocess

AM QA/QC 2

NDE for AM

5

QA/QC for AM

Test & qualify

Producing with AM

Fig. 53.4 Frequency of AM education and training courses referenced to Simplified AM Product Development Process

person to know all there is to know about the detailed processstructure-property relationships for every AM process, material, design geometry, or any combination thereof. Designers and engineers must work closely with material scientists and metallurgists, and both must collaborate with manufacturing and process engineers who know the intricacies of the AM system(s) on hand. Each other’s knowledge can mature independently for a while, but invariably, barriers are encountered that must be resolved with knowledge from other disciplines. As such, AM knowledge matures fastest when it is allowed to “co-evolve” among disciplines, leveraging the interdependencies between them to maximize learning. To help assess an organization’s readiness for AM, The Barnes Global Advisors (TBGA) created the TBGA AM Readiness Model to help track the progression of knowledge and degree of specialization with regards to AM processes, materials, and design. Representative levels are plotted in Fig. 53.5 for metal AM, progressing from basic materials knowledge, CAD/FEA experience, and polymer 3D-printing capabilities to series production with AM using tailored materials designed via a customized AM workflow. The fourth scale on the far right of the figure (i.e., People) provides a means for tracking AM awareness across the organization, from a few individuals to enterprise-wide knowledge of AM and its application – an aspirational level achieved by only a handful of companies to date.

As can be seen for simplicity, the levels within the model have suggested topics; so, the use of “Polymer 3D Printing” at Level 0 of Machine is meant to be more indicative than prescriptive. In this specific example, it follows the path of many organizations that they may have used inexpensive or desktop style 3D printers to begin design thinking. Similarly, this Level 0 organization is likely to buy stock materials from the machine vendor, using simple CAD tools and has awareness of some, but not all of the AM processes. Just as organizations mature and increase their readiness to integrate AM, we feel strongly that these begin to form a structured framework by which people get training. In this manner, we can match the attainment of skills to an organizational goal or output and track individual progress along the way. Criteria for assessing the quality of these offerings is discussed next.

53.7

Quality of AM Education and Training Offerings

When evaluating training and education options, there is a methodical approach to take. Among the many and varied education options, the practicalities of life may dictate feasibility. A full-time program has significantly different implications than a short course or an online experience. The time

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Review of Additive Manufacturing Program Offerings in the United States

Fig. 53.5 TBGA AM Readiness Model for assessing maturing of AM knowledge within and across an organization

Machine

Materials

901

Design

Level 4

AM series 4 production

4

Tailored AM materials

Level 3

Qualified 3 metal AM process

3

Use of novel materials

Level 2

Metal AM 2 (in-house)

2 Custom powder

Specialized 2 AM tools

Level 1

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1 Sourced powder

1

Level 0

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People Enterprise-wide AM knowledge

4 Customized AM workflow

4

Integrated 3 AM workflow

Team level 3 AM expertise

53

Polymer 3D printing

commitment will be commensurate. Typically, family and work obligations are paramount, and additional education and training must accommodate that. The quality of the education or training is then different and another factor for the individual to consider. Within the educational market, there are many factors available to assess the efficacy of an institution with regard to a specialty including rankings, reputational factors, as well an external accreditations. The educational institution has taken measures to ensure the quality of their product and your education. Choosing an education product has a more established path. The same is not true with training. Training is about learning a skill and the options in AM are many and varied. ASTM E2659-18 [9] offers requirements for issuers of certificates, but no quality guidelines exist to aid certificate programs specific to AM. While complying with A2659-18, we offer an interpretation with recommendations from Simpson, Williams et al. [7], tailored to AM with an added emphasis on valuing the training to accelerate adoption. We suggest the following synopsis of what to look for in AM training content and offerings.

53.7.1 Consistency – IP and Ownership The material presented is owned and updated by the trainer regularly. Everyone gains the same knowledge and insights so that a certificate is meaningful. Often confused with training are workshops and seminars. While useful and educational, they are distinct because the speakers may not be trained in education nor do they seek to take a group of

Basic materials 0 knowledge

AM design guidelines

0 CAD & FEA

2 Some AM specialists

1

Few AM novices

0 AM awareness

people and arm them with the same information, the same vocabulary, or the same learning objectives. Consistent training helps get many people on the same page.

53.7.2 Experience – AM and Instructors Having experience in AM is rare, but having experience in AM and teaching is yet more rare. The ability for the trainer to go into a deep dive is critical to ensure that learners get what they want from the training. Are the trainers enthusiastic about what they do? Can they communicate well? Being a good engineer is a good start, but being able to communicate effectively is essential. The best educators can explain the same concept in three or more different ways so that each learner can “get” the concept.

53.7.3 Value – Using AM and ROI Training is meant to improve the skills of the employee, which bring value to the company. Learners should ask for evidence that the training yielded a desirable return on the time and money invested in the effort.

53.7.4 Content – Agnostic and Unbiased For the training to be effective it must be organized around a framework for presenting the content. Understanding the

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learning objectives is key. If learners are only interested in a deep dive into a few process, then knowing how comprehensive it is can be critical. Very often, the training is offered by entities that have a vested interest in their product being bought at the conclusion. Ensuring that instructors are independent of a product and agnostic to the process helps ensure an unbiased view. Suggested questions to ask are: Is there a stated goal and are there learning objectives? Do the trainers have their own content, case studies, quizzes as opposed to referring to well-known examples available in the literature?

53.7.5 Pedagogy – Learner Focused Does the training use text, images, videos, case studies, discussions, and team activities effectively to engage different learning styles? Everyone has a different learning style, and while presentations may convey lots of information quickly, they cater to passive learners. Discussions, case studies, and problem-based learning appeal better to active learners, who learn by engaging with the material, the instructor, and their peers. Trainers and educators should employ proper pedagogy to ensure that everyone meets the learning objectives and training outcomes.

53.7.6 Assessment – Show It and Prove It Methods to assess the effectiveness of the training are also important. Have former students successfully applied their training after course completion? Have they come back after training with follow-up questions showing they have retained and are applying the training? A concluding assessment (quiz, presentation, or case study) is essential in gauging the learners’ absorption of the information. If the employee does not retain the information, then the training was very expensive. Learning and development of new skills requires knowledge acquisition and knowledge application. By assessing this knowledge, we ensure that much of it is retained.

53.8

Closing

In the grand scheme of manufacturing, AM is a young technology, the new kid on the block. While casting, for example, has evolved over thousands of years, AM is at best still in the first half century of its existence in the oldest forms. It is speculated that AM represents less than 1% of manufacturing globally as a market. Extrapolating that to awareness, understanding and designing for AM, it does not require too much

calculation to realize that very few organizations are ready to implement AM. Further, most engineers involved in manufacturing do not know the process of designing for AM. Most managers cannot readily articulate the value proposition AM can bring to their organization. When organizations “don’t know what they don’t know,” it is nearly impossible to acquire training. Further, complicating this situation is the lack of “what good looks like” from a central authority that knows what should be included in training hinders the situation. When organizations decide to embrace AM, the next step is to work out how they communicate and permeate skills to the broader organization in a consistent and structured manner. It is impractical to have a team one week be given information by an instructor only to have the second team get different information by a second instructor the following week – and expect either team to ready to design and produce AM parts immediately. Everyone needs to be working from the same alphabet and rowing in the same direction, recognizing that it takes time and practice to become competent in all aspects of AM. On the education front, the situation is better. Universities appreciate what structure goes into learning and are working to integrate AM further into their courses. Education is the beginning, but learning is a lifelong pursuit. Colleges and universities have to create a fertile environment for the individual to succeed later in life as new innovations come along and allow them to attain the skills to succeed over their career.

References 1. Gibson, I., Rosen, D.W., Stucker, B.: Additive Manufacturing Technologies: 3D Printing, Rapid Prototyping, and Direct Digital Manufacturing. Springer, New York (2015) 2. Milewski, J.O.: Additive Manufacturing of Metals: from Fundamental Technology to Rocket Nozzles, Medical Implants, and Custom Jewelry. Springer, Cambridge, MA (2017) 3. Leary, M.: Design for Additive Manufacturing. Elsevier, Cambridge, MA (2019) 4. Diegel, O., Nordin, A., Motte, D.: A Practical Guide to Design for Additive Manufacturing. Springer, Singapore (2019) 5. NASA Technical Standards Systems: Additive Manufacturing Requirements for Spaceflight Systems, NASA-STD-6030 (2021) 6. NASA Technical Standards Systems: Additive Manufacturing Requirements for Equipment and Facility Control, NASA-STD6033 (2021) 7. Simpson, T.W., Williams, C.B., Hripko, M.: Preparing industry for additive manufacturing and its applications: summary & recommendations from a National Science Foundation workshop. Addit. Manuf. 13, 166–178 (2017) 8. Pei, E., Monzón, M., Bernard, A. (eds.): Additive Manufacturing Developments in Training and Education. Springer International Publishing, Cambridge, MA (2018) 9. ASTM International: Standard Practice for Certificate Programs, E2659-18, West Conshohocken, PA (2018)

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Review of Additive Manufacturing Program Offerings in the United States

John E. Barnes is Founder and Managing Director of the The Barnes Global Advisors. He has a 25+ year career in product development and aerospace with Lockheed Martin Skunk Works™, Honeywell Aerospace, Australia’s CSIRO, and Arconic. He has been involved in metal AM throughout this career beginning in the late 1990s where he was part of the Sandia National Labs LENS™ CRADA. Since then, he has been in and around AM working both technical and business cases for implementation and development efforts in materials, powders, processing, and printing to mature the technology for applications. John is recognized internationally for contributions to AM, product development, and leadership in engineering, and his team won the Silver Medal in the US Air Force AM Olympics. He has over 14 patents or patents in application. He was Purdue University’s Materials Engineer of the Year in 2014 and is an Adjunct Professor at Carnegie Mellon University and RMIT University. He serves Society of Manufacturing Engineers (SME) as Vice Chair of the AM Technical Community, is the Chair of America Makes Executive Committee and has many publications and invited presentations. He holds a B.S. and M.S. in Materials Engineering from Purdue University.

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Timothy W. Simpson is the Paul Morrow Professor of Engineering Design and Manufacturing at Penn State and has over 20 years of experience using and teaching students, designers, and engineers about 3D printing and AM. As Co-Director of Penn State’s Center for Innovative Materials Processing through Direct Digital Deposition (CIMP3D, www.cimp-3d.org), Tim has been at the leading edge of the recent wave of AM innovation and industry adoption, and he has extensive experience with powder bed fusion, directed energy deposition, and non-destructive inspection technologies. He specializes in Design for Additive Manufacturing, and he has helped train and educate more than 750 industry practitioners to realize AM’s unique value proposition in aerospace, automotive, consumer goods, defense, energy, medical, oil and gas, and space industries. Tim helped launch and directs the world’s first Additive Manufacturing & Design Graduate Program at Penn State, which has enrolled over 200 industry participants from over 80 different companies in its first 4 years. He also serves as the Educational ADDVisor™ for The Barnes Global Advisors and writes a monthly column, “Additive Insights” for Additive Manufacturing Media and Modern Machine Shop.

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Part VII Applications and Case Study Examples

Additive Manufacturing Applications and Case Study Examples Alain Bernard

, Christoph Klahn

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, and Manuel Biedermann

Contents 54.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 907

54.2

Additive Manufacturing as a Complete Value Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 908

54.3

Automobile Dakar Levers, Pedals, and Ball Joint . . . 909

54.4

Antenna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 910

54.5 54.5.1 54.5.2 54.5.3

Heat Exchangers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . First Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Second Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Third Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Cold Plate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 913

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Perfume Bottle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 914

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3D Printing of Cable Guides for Trains . . . . . . . . . . . . . . 915

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Demonstration Part for Process Hybridization . . . . . . 916

54.10 54.10.1 54.10.2 54.10.3

Serial Productions with Additive Manufacturing . . . Vibratory Bowl Feeders for Automation Technology . . . Slip Ring Assembly Rotor with Integrated Electrical Leads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Additive Manufactured Flow Measuring Probes . . . . . . .

54.11

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 920

911 911 912 913

916 917 918 919

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 920

Abstract

The field of additive manufacturing (AM) has been continuously growing for more than 30 years. This chapter A. Bernard (*) Ecole Centrale de Nantes, LS2N UMR CNRS 6004, Nantes, France e-mail: [email protected] C. Klahn Karlsruhe Institute of Technology, Institute of Mechanical Process Engineering and Mechanics, Eggenstein-Leopoldshafen, Karlsruhe, Germany inspire AG, Zurich, Switzerland M. Biedermann ETH Zürich, Product Development Group Zurich pd|z, Zürich, Switzerland

describes a range of applications for AM. It highlights the development along the complete value chain including application needs, part design, and production. Keywords

AM applications · Cases studies · Industrialisation

54.1

Introduction

More than 20 years ago, AM was used in different fields like casting industry [1]. Most of these applications were related to rapid prototyping and rapid product development [2, 3]. Then, rapid manufacturing and direct fabrication appeared during the last decades and, more particularly, for metallic parts during the last 10 years [4]. Nowadays, the maturity level of additive manufacturing (AM) is enough to consider it for industrial series production. However, this level of maturity is not the same in all application fields, as shown in many review papers (construction [5], biomedical [6], dentistry [7], marine industry [8], aerospace industry [9], and many other domains [10, 11]). This section of the handbook describes different case studies in different application fields that are using AM for the production of parts. The chosen applications have been selected because they are representative of the state of the art and highlight the potential development in the near future. In this first chapter of the section, a global systemic vision is introduced in order to show the complexity of a given AM-based value chain. This vision also introduces what is necessary to use AM in a complete ecosystem represented by a value chain specific to each field of application. Then, a set of selected case studies is proposed showing a few examples that will be completed by the content of the other chapters of the section, each of them focusing on a specific domain.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_54

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A. Bernard et al.

Additive Manufacturing as a Complete Value Chain

The use of AM has to be considered according to a complete value chain vision with a systemic approach, connecting different steps that are necessary to give the expected characteristics to the part(s) [12]. Many factors help in defining the complete manufacturing process depending on specific requirements in particular fields. Figure 54.1 gives a global vision of all the different tasks that have to be achieved during an AM-based complete process and complementary ones depending on different needs for material life cycle management, machine cleaning and maintenance, machining of plates to remove material from support structures, etc. All these actions are usually not integrated into the manufacturing process but have to be managed properly and in accordance with the production plan. But what is crucial, at the beginning of the process, is to transform an idea or a concept of product into a manufacturable object according to the capabilities of AM technologies. Design for AM [13, 14] allows considering many advantages of AM. Many of these advantages are shown in the case studies that are proposed in this chapter and in all chapters of this handbook.

Before starting the manufacturing process, defining the right parameters and configuration of the process is crucial [15]. The manufacturing strategies [16, 17], the choices of specific support structures [18, 19], the choice of lattice or porous structures [20, 21], and many other issues have to be defined, simulated, and validated before “pushing the button” of the AM machine (in particular placement and orientation) [22, 23]. Post-processing is necessary because AM machines cannot deliver a complete added value to the parts and because parts have to be extracted from the machine and separated from the plates when produced with metal AM machines. Heat treatments, machining, and other additional finishing operations have to be completed in order to get the final parts with the final expected characteristics. All along the value chain, technologies of control are part of this process. It is very often necessary to confirm that dimensions and geometry are coherent with the CAD or the STL/AMF/3MF file. Controlling the material characteristics is also necessary either directly with one of the manufactured parts or with some samples that are used for specific tests. Managing the life cycle of the material is essential, batch after batch, because, depending on the technology that is used, the material properties are supposed to change mostly because of the influence of the atmosphere.

Fig. 54.1 Global set of actions to be achieved for a L-PBF-based AM value chain. (Source: LS2N, Centrale Nantes)

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Additive Manufacturing Applications and Case Study Examples

Many other aspects are not detailed here because they are not essential to understand the following case studies. However, they are detailed in other chapters of this handbook. In the following sections of this chapter, some application examples have been chosen among different domains. Obviously, this is just impossible to cover all fields using AM as a key technology for innovation, product and process improvement (part consolidation, design for machining, weightsaving features, built-in assemblies, conformal cooling channels, moving parts, etc.), small and large batch production, one-at-a-time manufacturing of personalized objects, etc. The main fields are defined by several standards by ASTM and ISO groups, especially aviation, spaceflight, medical/biological, transportation/heavy machinery, maritime, electronics, construction, oil/gas, consumer, and energy sectors (https:// www.astm.org/get-involved/technical-committees/commit tee-f42/subcommittee-f42).

54.3

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Fig. 54.2 Gear lever (60% mass reduction (a) compared to the original part (b)). (Courtesy of AddUp)

Automobile Dakar Levers, Pedals, and Ball Joint

This first case study is related to an application in the automotive field. Romain Dumas, an official Porsche driver since 2004, has multiplied his victories on the racetracks. But he is, above all, a passionate driver and a man of challenge. With this spirit, RD Limited was born, a multidiscipline racing team based at the Pôle Mécanique Alès-Cévennes (south of France). In 2017, Romain Dumas won the famous Pikes Peak race (USA) with a car equipped with a hub carrier printed in 3D by Poly-Shape, a French subsidiary of AddUp. Since then, this technological partnership has only grown stronger, and it is logical that Romain Dumas has trusted AddUp to design and produce metal parts for his buggy DXX for the Dakar 2021. Two factors are essential in the search for performance in an off-road racing vehicle: lightness and robustness. The L-PBF technology allows the metal powder to be fused to create parts from successive layers. Thus, various strategic parts of the buggy were printed, including an ergonomic gear lever, whose knob is the exact representation of the driver’s hand, for a better grip and to simplify the pilot’s driving. The gear lever has been 3D printed all-in-one, using the strongest metal, titanium Ti6Al4V. Moreover, its mass has been reduced thanks to the topology optimization technique that consists in placing material only where it is needed. This technique enabled a 60% mass reduction compared to the original lever, made with conventional means. Finally, the topology optimization technique allowed savings in raw material, and, therefore, lower production costs. As shown in Fig. 54.2, in addition to the aesthetic aspect of the part, which is not very common in rally raid, AM has made it possible to integrate more functions. A cable gland is

Fig. 54.3 Pedals with grips. (Courtesy of AddUp)

now embedded in the gear lever, allowing the strain gauge installed on the gear lever to be fed without disturbing the race driver. In addition to the gear lever visible in the passenger compartment, experts from Poly-Shape have designed the three pedals of the car according to the forces exerted by the driver during the race. The result, as shown in Fig. 54.3, is an average weight saving of 42% compared to the original pedals and a stronger sturdiness because they are printed in titanium. Finally, the last part installed on the buggy that will take to ® the starting line of the Dakar 2021 on January 3 is an Inconel

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exhaust ball joint. This is the same part that already equips some cars to take part in the WRX Rallycross Championship. Concerning this kind of ball joint, Pipo Moteurs, a French engineering company and manufacturer of engines for cars that compete in the current World Rallycross Championship (WRX), has been looking for a solution to improve the exhaust line bellows that are too prone to break or even cause fires during races. Pipo Moteurs contacted PolyShape, with whom they have been collaborating for many years, to optimize the design of a ball joint manufactured exclusively in 3D metal printing. The spherical ball joints named “PSPM” (Fig. 54.4) are designed in collaboration between the Pipo Moteurs and Poly-Shape design offices, in order to meet, on the one hand, the geometrical, mechanical, and thermal constraints imposed by the engines, and on the other hand, the manufacturing constraints of metal 3D printing. The mastery of expansion phenomena and stripping techniques by AddUp have made it possible to achieve a precise adjustment between the two sections of the ball joint, which is printed all-at-once, with a very good surface finish. The result of this innovation is amazing. “Our partnership allows us to develop a ball joint exhaust system link which offers a
10 rotation on any axis to give freedom of motion for any given exhaust system installation. Besides that, in the ball joint section, a male ball joint rotating in a two-layer female joint ensures proper sealing while allowing relative motion between the pipes it joins. This part uses an interference fit between one end and the other, and therefore the only way to produce it was by using a metal AM process. With our 3D printing technology, we can make very complex shapes, lighter and performing metal parts, and we succeeded in creating the two moving layers in one block only. So, you can have one of these ball joints at the turbine exit, one at the

Fig. 54.4 (a) The PSPM ball joint, a long-life part; (b) Two nonremovable lips, printed all at once (dimensions: Ø38 mm  76 mm; weight: from 40 to 220 g (depending on model)). (Courtesy of AddUp)

A. Bernard et al.

wastegate exit, and a final one at the junction on the downpipe, giving you a ‘floating’ exhaust system, which will not fail.” adds Frederic Impellizzeri, Automotive Business Unit Manager in Poly-Shape. This new “PSPM” ball joint concept is simple: the two layers are sliding, one inside the other, and the sealing is ensured by the differential expansion phenomenon created between the two parts. This part is an unbreakable, light, and flexible, undeniable asset in the motorsport. The innovative system has been tested extensively on Pipo Moteurs’ engine since the start of 2018, and it has produced excellent results, without leaking under the high exhaust gas pressure on such a rally engine. Also, one system has been used on one of Pipo Moteurs’ customer cars competing in the WorldRX Championship since the middle of the 2018 season, without any failure. The actual ball joint system is made out of Inconel, resisting to very high temperatures. Both French companies plan to start selling it in 2019 and will offer a full range of the ball joint parts in standard diameters from 1.5 in [38.1 mm] to 3.5 in [88.9 mm] and offer bespoke geometries on customer request. The good news is that this exhaust ball joint is a patented co-development (FR1860584) between Poly-shape and Pipo Moteurs. So any motorsport company will be able to afford this very long life part, of any dimension and made in any suitable material.

54.4

Antenna

PrintSky is a joint venture between the AddUp group, an expert in metal AM, and SOGECLAIR, specializing in the integration of high value-added solutions in the fields of aeronautics, space, civilian, and military transport. The

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CEA (French Alternative Energies and Atomic Energy Commission) commissioned Printsky to redesign a typically machined support part using the possibilities offered by AM to reduce its mass. This support must also precisely ensure its functionalities to hold the equipment it has to support and resist the stresses it is subjected to. PrintSky was in charge of the design part of the project, developing its own experience and methodology to implement the characteristics of the metal part, in terms of mechanics and manufacturability. The production was then entrusted to AddUp experts that 3D printed the aerospace part using their FormUp 350 machine. After topological optimization, AM makes it possible to fabricate complex shapes, improve performance, and reduce the volume of a metal part. It also allows the manufacture of very robust parts, as demonstrated by many former developments and applications. Indeed, the material is added only where necessary, either to support forces or to ensure functionality such as fastening, support surface, or other. A good rigidity/mass balance with a high technical and economic value for an aeronautical part was achieved (Fig. 54.5). The optimized support fulfils the same functions as the original support, but with a significant mass reduction, impossible to achieve with conventional technologies.

The use of fine powder allowed obtaining a good surface finish, and finally, the part was manufactured without support, which allows a significant time-saving in postprocessing (Fig. 54.6).

54.5

54.5.1 First Case Study Temisth is a company specialized in the development of the customized thermal solution using AM. With its expertise and skill on thermal issues, Temisth supports companies in several domains to develop an innovative project from the idea up to the proof of concept. PrintSky (introduced in the previous case study) and Temisth have developed a cleanbottom heat exchanger called “HEWAM” to demonstrate their ability to design and manufacture this type of equipment. The goal was to produce a compact heat exchanger according to the L-PBF process with an innovative shape and, above all, as efficient as “traditionally” manufactured heat exchangers (Figs. 54.7 and 54.8). PrintSky was in charge of the design aspect of the project, developing its own methodology to determine the characteristics of the metal part, in terms of mechanical, thermal, and manufacturability. The production was then being proceeded by the AddUp experts who 3D printed this aeronautical part on a FormUp 350 machine. For thermal equipment, AM has a huge advantage. It allows the development of complex channel shapes and thus improves thermal performance and reduces the volume of the part. It also allows manufacturing shapes that are impossible to produce traditionally for this type of equipment (e.g., double-curved channels). The metal part thus printed is compact and has obtained a very good thermal performance for a smaller volume compared to exchangers made with more “conventional” technol® ogies. It should be noted that the wall thickness of Inconel

Fig. 54.5 Antenna (dimensions: 280  133  70 mm; mass: 364 g). (Courtesy of AddUp)

a)

Heat Exchangers

b)

z y x

Fig. 54.6 (a) Original machined part; (b) Printed part (40% mass savings compared to the given maximum target of 600 g). (Courtesy of AddUp)

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1

2

Stainless steel 304L

Fig. 54.7 Heat exchanger (dimensions: 141  117  48 mm; mass: 775 g; heat rate: 2200 W/unit; thermal efficiency: 46% (simulated results)). (Courtesy of AddUp)

Fig. 54.8 A modular solution: exchangers could be arranged next to each other in order to deliver high exchange power. The curved shape is suitable for installation in aircraft engine pylons. (Courtesy of AddUp)

718 is only 150 μm. Finally, the use of fine powder has allowed obtaining a good surface finish necessary to improve heat exchanges.

54.5.2 Second Case Study The CEA has joined forces with AddUp to create the Famergie platform to help energy sector manufacturers develop projects for the production of parts using metal AM. The first project resulting from this partnership is a demonstrator of a methanation exchanger-reactor. This device converts CO2 into methane, which can be used as a synthetic fuel. As the methanation reaction occurs at high temperature and pressure, the design of the exchanger is crucial for the efficiency and control of the entire methane production.

Fig. 54.9 1 – the part printed all in one (dimensions: 160  70  70 mm; mass: 3.2 kg); 2 – sectional view of the heat exchanger to visualize the quality and complexity of the internal channels. (Courtesy of AddUp)

Fig. 54.10 The parts in the machine after the metal powder has been removed. (Courtesy of AddUp)

CEA researchers have come up with a concept of an exchanger-reactor that takes advantage of the possibilities offered by additive technology. The AddUp experts then adapted the geometry of the part to integrate the constraints linked to the process. The operating parameters have been developed to obtain the desired surface finishes and to optimize production costs. The reactors were printed in 3D, in 304L stainless steel, on an AddUp FormUp 350 machine (Figs. 54.9 and 54.10). This technology has several advantages to improve the performance of heat exchangers. As previously mentioned, it allows the production of parts with complex channel shapes but also with very thin walls, offering larger exchange surfaces compared to parts obtained by conventional processes. In addition, by producing exchangers equipped with all their interfaces (fluid inlet and outlet connections, fasteners, etc.)

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in a single operation, the risk of leakage is lower than with assembled parts. The project carried out by CEA and AddUp paves the way for more compact, more efficient, and more reliable methanation exchanger-reactors. It improves heat exchange and offers better control of the chemical reaction. In addition, the part printed all-in-one offers high resistance to temperature and pressure, reducing the risk of leakage compared to a traditional exchanger.

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54.5.3 Third Case Study As shown with the previous examples, single-material printing has been around for more than 30 years. It is now a widely established technology with accelerating adoption. Multi-material AM is still under development but widely recognized as one interesting evolution of AM. It will allow part optimization and customization like never before. Since its foundation in 2016, Aerosint has been developing a technology that is called “Selective Powder Deposition.” This technology is an alternative powder re-recoating system that, instead of uniformly spreading just one single powder material, selectively deposits two (or more) powders to form a single layer containing two materials. This powder recoater can be integrated into any powder bed AM process (L-PBF, binder jetting, SLS, etc.) and gives those multi-material capabilities. Today, the multi-material printing approach was validated using a L-PBF process. The Aconity MIDI+ printer equipped with Aerosint’s recoater is the first commercially available multi-material L-PBF printer in the world. The first metal pair to be printed together is stainless steel and copper alloys. The applications for this pair require the high strength and/or corrosion resistance of the stainless steel combined with the good thermal or electrical conductivity of the copper alloy. Some example use cases are: extrusion nozzles, mold inserts, hot runners, or heat exchangers (see Figs. 54.11 and 54.12). The applications for multi-material can be very diverse and will grow as new material pairs get validated.

54.6

Fig. 54.11 Dual-metal heat exchanger designed by Aconity 3D and printed on Aconity MIDI+ printer equipped with Aerosint’s multimaterial powder recoater (316L þ CuCrZr). (Courtesy: Aerosint)

Cold Plate

In the race for electrification, among the issues is the cooling of electronic components. The challenge is twofold because the weight of the vehicle must also be as low as possible. Currently, the cold plates are made with two halfaluminum alloy shells enclosing a curved copper alloy tube. The result is a heavy design with a loss of heat transfer between the half-shells and the tube, with a risk of loss of waterproofing.

Fig. 54.12 Dual-metal heat exchanger designed by GEN 3D and printed on Aconity MIDI+ printer equipped with Aerosint’s multimaterial powder recoater (316L þ CuCrZr). (Courtesy: Aerosint)

AM helps to limit this onboard mass, because it is possible to adapt the design by dressing the functional areas, thus putting material only where it is needed. The minimum thicknesses attainable are in the order of mm, lower than those obtained in a foundry. It is also possible to create

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Fig. 54.13 (a) Cold plate (dimensions: 210  242  30 mm; mass: 794 g); (b) The single cooling channel passes under all the components to cool them. (Courtesy of AddUp)

textures and shapes that are difficult to achieve with conventional means allowing a high thermal exchange between fluid and electronic components. The pioneers in this field are the Formula E teams, but this concept of the cold plate can be applied to all industries where mass is a criterion, from urban vehicle to satellite (Fig. 54.13). Thanks to 3D metal printing, it is possible to create various types of cooling, including perpendicular and radial fins (like caloducs). AddUp company manufactured the part with a FormUp 350 machine. During production, the structure is self-supported. The orientation of the surfaces reduces the amount of supports, which leads to a reduction in the cost and risks associated with the manual recovery of surfaces. Chemical machining can be used to improve the internal surface quality of the cooling duct and thus the performance of the part. This cold plate is a relevant application case for L-PBF technology. The search for compactness and the optimization of fluid circulation is successful. On this part are printed the indications to simplify the assembly and traceability of the part (serial number, version, etc.) and no laser engraving. Finally, 3D metal printing allows the designer to unleash his imagination and free himself from the constraints of traditional processes, and also to focus on the functional

aspect that the product must fill, usually accompanied by a minimization of the mass.

54.7

Perfume Bottle

In the field of perfume bottles, redesign is to be considered with respect to a marketing point of view, mostly, but also to improve the package by using new technologies to really integrate more concepts and aesthetics. This was the case for MMB Volum-e group that has been asked to redesign “The Ballerina,” from Ilana Jivago. The initial concept of a perfume glass bottle was created in 1995. This new model has been designed in preparation for the LuxePack exhibition in Monaco. The main challenges have been: (1) to launch a new premium range for the Jivago brand with a unique product and an unusual packaging: (2) to balance the bottle without adding a clunky accessory, respecting the original design, (3) to test the integration of the accessory on a base; and (4) considering the pointed shape of the bottle to create a removable base. The main differentiated features have been a creative and technical force of proposal fueled by 50 years of experience

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Fig. 54.14 (a) Different iterations; (b) The final model. (Courtesy of MMB VOLUM-E group)

in the luxury markets. At the same time, the company has proposed over 4 weeks an integrated design know-how offering fast and reliable development. Based on and thanks to a diversity of internal resources and a network of local partners to support the production and delivery of “turnkey” products, they provided a representative prototype in 3 weeks, including several iterations. Global knowledge of product development has been demonstrated with the complementary creation of a secondary packaging, “Egg,” to match the ambitions of the brand (Fig. 54.14). In the end, the – Ilana Jivago – CEO concluded with a complete satisfaction: “MMB-Volum-e has found the balance point to allow the bottle to stand on its tip, while keeping a light & elegant design. Beautiful realization!”.

54.8

3D Printing of Cable Guides for Trains

The challenge for ALSTOM is to print 1300 cable guides for American and European trains, with a short delivery time in order to increase the vibration resistance of the cables and to avoid friction. The main goal is that these parts had to be fire-smoke certified (EN-45545) and also meet a rail-specific standard, the “R1-HL2” criticality level, a Level 2 flame-holding level (on a scale of 1–3). In order to achieve these goals and to fit the given requirements, the following steps of fabrication have been chosen.

First, a 3D design was carried out on CATIA by a designer from ALSTOM’s design office to create this new part and a 2D plan of the 3D design given by Kimya, an Armor group company. Second, Kimya has defined a suitable material and 3D printing profile. The filament has been produced exceptionally from granules usually reserved for the injection process to gain speed here. The filament is made of polycarbonate (PC) loaded with flame-retardant additives. Two months of iterations were required to achieve dimensional and geometric tolerance and meet the expected standard. Numerous tests were carried out on high-temperature machines until finding the perfect combination of temperatures (nozzle + tray) to circumvent the difficulties encountered during extrusion and printing, due to the type of granules used and its crystallization rate. Compensation measures were also put in place following the retraction of the cold parts. Through empirical iterations, the dimensions of the 3D part have been enlarged so that the ribs take into account the reactions of the part in the post-print stage. Manual post-processing was performed on two criticality zones to minimize roughness. The gains for ALSTOM have been effective and substantial. The parts were ready to be delivered in just 2 months, twice as fast as a conventional injection process. Despite a higher cost per piece, the tool economy (due to the absence of injection molds) makes AM more attractive for ALSTOM. This manufacturing process will therefore be permanent for this part in the future (Fig. 54.15).

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Fig. 54.15 (a) Cable guides embedded in trains; (b) Small and large cable guides. (Courtesy of Kimya and Alstom)

Demonstration Part for Process Hybridization

The following case study relates to processes hybridization. The idea is to illustrate how to use the best of different processes for the manufacture of a part [24–26]. This hybridization deals with the manufacture of a family of five individual parts (sleeves) in Inconel 718, with an internal chamber and channels (Fig. 54.16). Those internal features must offer a low roughness in order to be compatible with the fluid flows during the operation of the part. These massive parts have interior shapes that are impossible to achieve with traditional processes. The difficulty posed by these forms justifies the use of the L-PBF process. However, taking into account the mass to be implemented, the use of a DED process became necessary to finalize the massive features of the parts and thus reduce the manufacturing time on the build platform of the L-PBF process, in particular, due to the need to obtain a low roughness. The sleeves were optimized for the L-PBF and ® DED-CLAD processes, by adapting the geometries. Then the parts were manufactured: first, the core with the L-PBF process by the company MMB-Volum-e (see the part on the build platform in Fig. 54.17). The weight of the core manufactured with L-PBF is 45 kg, and the manufacturing has been achieved after 120 h (5 days full time). The adding of the features has been proceeded with ® DED-CLAD by the company IREPA LASER (see the part during processing on Fig. 54.18). The weight of the material ® deposited by DED-CLAD is 11.7 kg. Programming, machine and part setup have been less than 1 h long. ® DED-CLAD manufacturing has been achieved in 7 h. ® After L-PBF and DED-CLAD processes, the parts were stress relieved. The functional surfaces were then machined (see the part on Fig. 54.19).

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Internal chamber

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Ø 285 mm

Fig. 54.16 Sectional drawing of one of the parts. (Courtesy of DGA (Direction Générale de l’Armement))

After optimizing the geometries, the hybridization of the AM processes thus makes it possible to save manufacturing and finishing time on the parts made by L-PBF, reduce the price of the parts, and shorten the delivery time. In addition, this combination of processes also pushes the maximum dimension limits imposed by the construction chamber of L-PBF systems.

54.10 Serial Productions with Additive Manufacturing The previous case studies report for many of them one-of-akind productions or small batch productions. This is not the case for the following ones, which demonstrate the use of AM for series products.

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Fig. 54.17 The core of a part manufactured by L-PBF, on the build platform before extraction. (Courtesy of MMB VOLUM-E group)

®

Fig. 54.18 Features added with DED-CLAD . (Courtesy of IREPA LASER)

54.10.1 Vibratory Bowl Feeders for Automation Technology Automation technology uses vibratory bowl feeders to supply bulk material components automatically, singled and in the correct position to a processing or handling station. The vibrations of the bowl convey the parts upwards on a spirally rising path. Sorting elements along the parts ensure that only correctly aligned parts reach the top. Each bowl feeder in all

Fig. 54.19 Another model of part after machining and welding. (Courtesy of DGA (Direction Générale de l’Armement))

its dimensions and elements is designed exactly to the geometry and mass of the part to be conveyed. Most of these vibratory bowl feeders are therefore one-off products and works of craftsmanship, whose vibration behavior is precisely matched to the mass and dimensions of the conveyed parts. In conventional manufacturing, skilled workers build vibratory bowl feeders mainly from sheet metal by cutting, bending, and welding to create these very complex structures. Their manufacture requires experienced technicians, long production processes, and goes through various phases of testing and fine-tuning before a reliable product is reached. The Swiss manufacturer Rüfenacht AG recognized the potentials of AM and implemented an alternative process route to the conventional processes in 2015. Two factors were decisive for expanding of the production portfolio to AM. On the one hand, the use of AM makes it possible to relocate a larger part of the production to one’s own company. Previously, external suppliers carried out the milling process. The changeover to AM thus offered the opportunity to shift a larger part of the value creation to the own company, thereby increasing the own profit margins and at the same time reducing the coordination effort for the individual production steps. The second factor was the reproducibility of AM compared to a manual assembly. A common problem in the conventional production of vibratory bowl feeders is the high susceptibility to deviations caused by the manual manufacturing process. Thus, two conventionally manufactured copies of the same bowl can differ significantly in their performance, even if the same skilled worker builds both. The changeover to AM not only resulted in more

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Fig. 54.20 L-PBF-P-made vibratory bowl feeder in PA12. (Source: Rüfenacht AG)

uniform products, it also drastically reduced the cost of producing multiple copies of a bowl feeder. Now spare parts or additional copies of a feeder can easily be supplied if customers want to expand the capacity of their production lines (Fig. 54.20). The company started the implementation by evaluating the two AM technologies material extrusion and using laser-based powder bed fusion of polymer (L-PBF-P). The core requirements for the manufactured product are a correct transmission of the vibrations within the feeder bowl and a uniform surface structure to facilitate the movement of the conveyed parts. In addition, there is the need for a large build chamber in the AM machine to produce monolithic bowls. Material extrusion did not meet the requirements due to poor vibration properties and a pronounced stair case effect that created problems to very small. L-PBF-P feeder bowls meet the requirements and are comparable to conventionally manufactured bowls. Rüfenacht AG was the first company in Switzerland to manufacture vibratory bowl feeders using laser-based powder bed fusion of polyamide (PA12). The development and production of a new bowl feeder using AM takes about 2 weeks, with the fine design of the models in CAD accounting for a large part of the time. The designers draw on their experience in conventional bowl construction and can thus anticipate most problems directly in CAD. The freedom of design in AM is a particular advantage here. Designers are able to integrate quickly additional functions into the bowl feeder, such as pneumatic channels, sensors, returns, slots, and cleats. The AM process delivers components of sufficient quality that only require sand blasting to clean the surface. To the customers of vibratory bowl feeders, changeover times are an important factor. Production lines are converted to different products on a regular basis, and this requires the exchange of format parts in the bowl feeder. Mounting these format parts normally requires experienced workers due to

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the necessary calibration. A monolithic AM bowl drastically reduces the changeover costs and time and does not require any special knowledge to install. This also affects maintenance and repair, as defective and worn components are no longer repaired by a specialist. A new copy of the relevant component is made to order based on the existing design. The implementation of AM enabled Rüfenacht AG reallocate the supply chain to an in-house production. The company incorporated value-adding processes and reduced the dependence on external service providers. This increased the efficiency production process and improved the reproducibility of the product. The value creation also shifted within the company from a highly skilled production to an experienced design department. The workers were trained in CAD to maintain their specialized knowledge in the company.

54.10.2 Slip Ring Assembly Rotor with Integrated Electrical Leads Slip ring assemblies SRAs are electrical devices to transmit electrical signals from a stationary element to a rotating element. SRAs are used on earth for a variety of applications such as video surveillance, machine tools, motion simulators, and many others. In space, SRAs are recurring elements in satellites, where they can be found in solar array drive mechanisms (SADMs), antenna pointing mechanisms, momentum gyroscopes, and other instruments. In its current state-of-theart design, the rotor of an SRA consists of a stack of highprecision insulating and conductive rings, each conductive ring being manually soldered to an electric wire, which in turn is guided to the end of the rotor. The stack is connected to a central shaft and the whole assembly is mechanically stabilized by a cast resin matrix. Today, the production of SRA rotors is a long and complex process involving a large number of components and production steps. As a rule of thumb, each electrical channel adds three components to the assembly: an insulating ring, a conductive ring, and a cable. The manufacturing and installation effort is proportional to the number of channels while the robustness decreases. This context motivated the development of an AM. RUAG Space Switzerland Nyon (RSSN) and CSEM redesign a slip ring assembly rotor (SRA rotor) based on AM to reduce manufacturing and assembly costs while improving the overall reliability and repeatability of the final product. The redesign should also allow mass reduction of the rotor and avoid the use of cables, which are part of the current system architecture. The core element of the AM SRA rotor is a new design and manufacturing concept that allows to combine the two essential features of the SRA rotor: the mechanical structure and the electrical conductors including their electrical connection interfaces. A monolithic AM structure comprises a

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The following iterations of the design further enhanced some key features such as dynamic electrical noise and rotor compactness, thus opening up a wider range of applications. The new concept reduces components with 24 electrical channels from more than 70 to a single part. The new concept also significantly reduces manufacturing costs and overall mass, as the central shaft can be removed or optimized. The new architecture of the rotor no longer contains cables, which helps to improve the reliability of the system.

54.10.3 Additive Manufactured Flow Measuring Probes Fig. 54.21 Slip ring assembly rotor. (Source: CSEM)

structural hull and a multitude of electrical conductors mechanically connected to the hull by sacrificial bridges. A nonconductive material is casted around this structure. Subtractive manufacturing processes remove the sacrificial bridges after the isolation is hardened. Figure 54.21 depicts the machined SRA rotor, which is halved to show the internal conductors. The resulting component is a mechanical part with a built-in electrical conductor. The connectors to wires can take different forms such as pin, crimp, spring, or slip ring contact. The connectors are built directly during the AM process or are added during post-processing if high precision is required. The structural hull can include additional features such as mechanical interfaces, reference surfaces, bending elements, grid structure, and many others. The monolithic designs of the electromechanical components with built-in conductive wires replace a tedious assembly process with a combination of AM, casting, and subtractive manufacturing. The structural component in Fig. 54.21 is additively manufactured by L-PBF-M from aluminum AlSi10Mg. Other manufacturing technologies and materials are also possible to fulfil specific application requirements. The usual finishing steps of stress relief heat treatment, build platform separation, and cleaning were carried out on the AM part before it is filled with epoxy resin, cured, and reworked to remove the outer shell of the body and sacrificial bridges. The surface of the slip rings selectively received a gold layer to improve the tribological and electrical performance of the SRA rotor during operation. Cables were soldered to the finished part, which was then mounted on a dynamometer. The electrical properties of the rotor prototype were fully validated in terms of electrical continuity, insulation resistance, and dielectric strength. Dynamic electrical noise and durability have also been verified and showed satisfactory results for SADM applications intended for low earth orbit (LEO) and geostationary orbit (GEO) missions.

Whether aircraft, drones, racing cars, gas turbines, or submarines, and in many areas, it is important to measure the properties of a fluid flow. So-called flow measuring probes determine the pressure, velocity, and angle of an incident flow. The example of an aircraft illustrates the importance of correctly measuring the speed of the airflow: If the air speed is too low, the aircraft may stall, while high speed puts too much strain on the components. Airflow systems can stabilize drones by detecting when a gust would deflect the vehicle and actively intervening in its control. Flow measuring probes have to fulfil a variety of requirements depending on the application and the flow field to be measured. The company Vectoflow GmbH is active in the field of fluidic measurement technology and develops flow measurement systems tailored to the customer’s needs. In order to meet these requirements, the company relies on the potential of AM. Depending on the application, the probes can be adapted with regard to the probe type, the shape of the probe and the probe head, the number of measuring bores, the selected material, and the system under investigation. Figure 54.22 depicts a selection of individual probes. For this specific application, the use of additive manufacturing processes such as laser-based powder bed fusion of metal and polymer offer a variety of advantages. The freedom of design allows different configurations of flow probes and increases the measurement quality or even make a measurement possible in the first place. The probes are manufactured as stand-alone components or can be integrated directly into another part. AM allows geometrical freedom as well as a high degree of flexibility in material selection for challenging applications. Probes in gas turbine or turbomachine operate at elevated temperatures of up to 2000  C and rely on high-temperature materials such as ceramic, CoCr, tantalum, or Inconel, while lightweight applications use probes made from titanium or aluminum alloys. AM also makes very small measuring probes feasible. One of the smallest probes in the world from Vectoflow GmbH, depicted in Fig. 54.23, has an outer diameter of 0.9 mm and integrates five channels with a diameter of

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Fig. 54.22 Flow measuring probes. (Source: Vectoflow)

54.11 Conclusions

ø 0.9 mm 16

mm

This chapter relates to different case studies presenting concrete applications of AM. Some values are given about the performances that show some great potential impact of the use of AM. Some more examples will be presented in the following chapters in order to illustrate more in-depth applications of AM in several fields. Acknowledgments The authors would like to express their sincere thanks to all the different companies who provided these application examples.

Fig. 54.23 Smallest flow measuring probe in the Vectoflow program. (Source: Vectoflow)

approx. 0.1 mm. Powder removal is a challenge for such small dimensions, but feasible. The orientation in the installation space of the printer and the process parameters are decisive for the quality and perfect function of the measuring probes. The post-processing of the additive manufactured probes depends on the selected process and the application. For most probes, the tip of the probe is reworked. The integrated channels usually require no post-processing, because for most probes, no fluid flows through the channels and only pressure is transmitted, therefore it is sufficient that the channels are open and separated from each other. Only the channel surface of high-frequency probes must be reworked using special processes. Each finished flow measurement probe is calibrated in the in-house supersonic wind tunnel. The wind tunnel creates the flow conditions during operation. The measurements are correlated to the simulated flow conditions to teach the probe which signals occur in a particular flow field. The software of the probe uses this acquired measurement characteristics to determine the flow velocity and angle of attack during operation.

References 1. Bernard, A.: Rapid product development case studies and data integration analysis. Comput. Ind. 43(2), 161–172 (2000). https:// doi.org/10.1016/S0166-3615(00)00065-8 2. Bernard, A., Fischer, A.: New trends on rapid product development. CIRP Ann. Manuf. Technol. 51/2/2002, 635–652 (2002) (Keynote du Scientific and Technical Committee « Design ») 3. Bernard, A., Taillandier, G., Karunakaran, K.P.: Evolution of rapid product development with rapid manufacturing: concepts and applications. Int. J. Rapid Manuf. 1(1), 3–18 (2009)., ISSN (Online): 1757-8825, ISSN (Print): 1757-8817 (Inderscience) 4. Karunakaran, K.P., Bernard, A., Simhambhatla, S., Dembinski, L., Taillandier, G.: Rapid manufacturing of metallic objects. Rapid Prototyp. J. 18(4), 264–280 (2012). https://doi.org/10.1108/ 13552541211231644 5. Camacho, D.D., Clayton, P., O’Brien, W., Ferron, R., Juenger, M., Salamone, S., Seepersad, C.: Applications of additive manufacturing in the construction industry–a forward-looking review. In: Proceedings of the 34rd ISARC, Taipei, Taiwan, pp. 246–253., ISBN 978-80-263-1371-7, ISSN 2413-5844 (2017). https://doi.org/10. 22260/ISARC2017/0033 6. Singh, S., Ramakrishna, S., Bouten, C.V.C., Narayan, R. (eds.): Biomedical applications of additive manufacturing: present and future. Curr. Opin. Biomed. Eng. 2, 105–115 (2017). https://doi. org/10.1016/j.cobme.2017.05.006 7. Bhargav, A., Sanjairaj, V., Rosa, V., Feng, L.W., Fuh, Y.J.: Applications of additive manufacturing in dentistry: a review. J Biomed Mater Res B Appl Biomater. 106(5), 2058–2064 (2018). https://doi. org/10.1002/jbm.b.33961. Epub 2017 Jul 24. PMID: 28736923

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8. Strickland, J.: (2016). Applications of additive manufacturing in the marine industry. https://doi.org/10.13140/RG.2.2.29930.31685 9. Froes, F.H., Boyer, R. (eds.): Additive Manufacturing for the Aerospace Industry, 482 pages, Paperback ISBN: 9780128140628, eBook ISBN: 9780128140635. Elsevier Publisher (2019) 10. Khan, I., Mateus, A., Lorger, C.S.K., MitchPart, G.R.: Specific applications of additive manufacturing. Procedia Manuf. 12, 89–95., ISSN 2351-9789 (2017). https://doi.org/10.1016/j.promfg. 2017.08.012 11. Horn, T.J., Harrysson, O.L.A.: Overview of current additive manufacturing technologies and selected applications. Sci. Prog. 95(3), 255–282 (2012). https://doi.org/10.3184/ 003685012X13420984463047 12. Belkadi, F., Sanfilippo, E.M., Bernard, A., Vidal, L.M.: A productprocess model for decision-aid perspective in additive manufacturing field. Comput.-Aided Des. Applic. 17(6), 1278–1293 (2020). https://doi.org/10.14733/cadaps.2020.1278-1293 13. Thompson, M.K., Moroni, G., Vaneker, T., Fadel, G., Campbell, I., Gibson, I., Bernard, A., Schulz, J., Graf, P., Ahuja, B., Martina, F.: Design for Additive Manufacturing: trends, opportunities, considerations, and constraints. CIRP Ann. Manuf. Technol. 65(2), 737–760 (2016) 14. Vaneker, T., Bernard, A., Moroni, G., Gibson, I., Zhang, Y.: Design for additive manufacturing: framework and methodology. CIRP Ann. 69(2), 578–599 (2020). https://doi.org/10.1016/j.cirp.2020. 05.006 15. Zhang, Y., Bernard, A.: A KBE CAPP framework for qualified additive manufacturing. CIRP Ann. 67(1), 467–470 (2018) 16. Zhang, Y., Bernard, A.: An integrated decision making model for Multi-Attributes Decision Making (MADM) problems in Additive Manufacturing process planning. Rapid Prototyp. J. 20(5), 377–389 (2013) 17. Zhang, Y., Xu, Y., Bernard, A.: A new decision support method for the selection of RP process: knowledge value measuring. Int. J. Comput. Integr. Manuf. 27(8), 747–758 (2014) 18. Zhang, Y., Wang, Z., Zhang, Y., Gomes, S., Bernard, A.: Bio-inspired generative design for support structure generation and optimization in Additive Manufacturing (AM). CIRP Ann. 69(1), 117–120 (2020). https://doi.org/10.1016/j.cirp.2020.04.091 19. Wang, Z., Zhang, Y., Tan, S., Ding, L., Bernard, A.: Support point determination for support structure design in Additive Manufacturing. Addit. Manuf. 47, 102341 (2021). https://doi.org/10.1016/j. addma.2021.102341 20. Lebaal, N., Zhang, Y., Demoly, F., Roth, S., Gomes, S., Bernard, A.: Optimised lattice structure configuration for additive manufacturing. CIRP Ann. 68(1), 117–120 (2019). https://doi.org/10.1016/j.cirp. 2019.04.054 21. Zhang, Y., Tan, S., Ding, L., Bernard, A.: A toolpath-based layer construction method for designing & printing porous structure. CIRP Ann. 70, 123–126 (2021) 22. Zhang, Y., Gupta, R.K., Bernard, A.: Two-dimensional placement optimization for multi-parts production in additive manufacturing. Robot. Comput. Integr. Manuf. 38, 102–117 (2016) 23. Zhang, Y., Bernard, A., Harik, R., Karunakaran, K.P.: Build orientation optimization for multi-part production in additive manufacturing. J. Intell. Manuf. 28(6), 1393–1407. (First online: 28 February 2015) (2017). https://doi.org/10.1007/s10845-015-1057-1 24. Karunakaran, K.P., Suryakumar, S., Chandrasekhar, U., Bernard, A.: Hybrid rapid manufacturing of metallic objects. Int. J. Rapid Manuf. 1(4), 433–455 (2010). https://doi.org/10.1504/IJRAPIDM.2010. 036116

25. Suryakumar, S., Karunakaran, K.P., Bernard, A., Chandrasekhar, U., Raghavender, N., Sharma, D.: Weld bead modeling and process optimization in Hybrid Layered Manufacturing. Comput. Aided Des. 43(4), 331–344 (2011). https://doi.org/10.1016/j.cad.2011. 01.006 26. Kumar, Y., Billo, T., Murmu, A., Choube, H., Karunakaran, K.P., Bernard, A.: Hybrid layered manufacturing using Gas Metal Arc Weld (GMAW) deposition. Int. J. Adv. Manuf. Syst.. (ISSN No. 15362647). 14(1), 11–18 (2012)

A. Bernard, graduated in 1982, PhD in 1989, was Associate Professor, from 1990 to 1996 in Centrale Paris. From September 1996 to October 2001, he was Professor in CRAN, Nancy I, and led the “Integrated Design and Manufacturing” team. Since October 2001, he has been Professor at Centrale Nantes and Dean for Research from 2007 to 2012. He is researcher in LS2N laboratory (UMR CNRS 6004), former head of the “Systems Engineering –Products-Processes-Performances” team. His research topics are KM, PLM, information system modeling, enterprise modeling, systems performance assessment, virtual engineering, and additive manufacturing. He supervised more than 40 PhD students. He published more than 150 papers in refereed international journals and books. He is vice president of France Additive (French Association on Additive Manufacturing) since 1993, and Fellow emeritus of CIRP. In 2018, he has been elected Fellow Member of the Academy of Technologies of France.

Christoph Klahn is professor for Additive Manufacturing in Process Engineering at Karlsruhe Institute of Technology. He was the head of Design for New Technologies at inspire AG, closely related to ETH Zürich, until 2021. His research explores the opportunities of additive manufacturing and their implications on the development process of devices. He works on design for additive manufacturing since 2008 and received his doctorate in engineering from Hamburg University of Technology in 2015.

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Manuel Biedermann is a research associate at the Product Development Group Zurich (pd|z) at ETH Zurich since 2017. As part of his doctoral studies, he is conducting research in the field of design for additive manufacturing. His primary focus lies on the automated CAD creation of additive manufactured flow components such as fluid distributors, mixing nozzles, and hydraulic manifolds.

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Additive Manufacturing in Cultural Heritage Preservation and Product Design

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Bingjian Liu, Fangjin Zhang, Xu Sun, and Adam Rushworth

Contents 55.1 55.1.1 55.1.2 55.1.3 55.1.4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tangible Accessibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Manipulability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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55.2 55.2.1 55.2.2 55.2.3 55.2.4

Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Metal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ceramic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Section Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stone: Marble Enclosure in the Palace Museum . . . . . . . . . Metal: Bronze Lion Sculpture in the Summer Museum . . . Ceramic: Porcelain Vase and Enclosure . . . . . . . . . . . . . . . . . . Integrated Metal and Ceramic Printing: Cloisonne Restoration – AM Material Replacement . . . . . . . . . . . . . . . . Product Design: Dragon Plaque and Antique Coin . . . . . .

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Limitations and Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . 937

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Abstract

As a three-dimensional object, both visual and tactile information of tangible cultural heritage (CH) have valuable historical and contextual significance. For the purpose of preservation, compared to conventional manual restoration and digital archiving, additive manufacture (AM) has advantages in several aspects, in particular, it can produce accurate replica for people to “feel” it by B. Liu (*) · X. Sun · A. Rushworth University of Nottingham, Ningbo, China e-mail: [email protected] F. Zhang (*) School of Design and Creative Arts, Loughborough University, Loughborough, UK e-mail: [email protected]

touching. In addition, AM is not only able to produce a replica for artifact but also provides a new way for designers to create products which are recognizably linked to cultural heritage. Through these creativities, AM can help bridge the “old” to the “new” and bring the cultural heritage experience from museum to “people’s” daily lives. Nevertheless, the limitations on materials and color scheme restrict the application of AM to the CH area. In this chapter, case studies from publications were analyzed, and relevant projects conducted by the authors were presented and discussed. It shows that plastic materials are usually used to get a precise replica, but postprocessing is needed to improve the appearance and to achieve the verisimilitude with the original artifact. In addition, a process chain was proposed to act as the guideline for the integration of AM with other techniques. Keywords

Additive manufacturing · Cultural heritage · Product design · Process chain

55.1

Introduction

Cultural heritage constitutes the elements of an extremely valuable and immense historical patrimony [27], which preserves our history and helps us understand their historical context [24]. Cultural heritage can be presented as either tangible or intangible [17]. In the area of tangible heritage, there are two common ways for preservation purposes: one is to restore the historical artifact in the physical world, for instance, manually repairing the broken part of a pottery; and another is to digitally archive the artifact to store its visual information, for example, recording 3D image of the artifact. Nevertheless, additive manufacturing provides an approach to bridge the physical world and the digital virtual world, i.e., transferring the 3D data to a physical replica of CH artifact with a 3D printer.

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In recent years, thanks to its advantages in accuracy and efficiency, AM is increasingly used in cases of archaeological restorations and the preservation of culture heritage [1]. Compared to manual work and digital archiving, AM has advantages in several aspects, such as efficiency, accuracy, tangible accessibility, and manipulability:

55.1.1 Efficiency Manual restoration is the common and conventional method in the area of cultural heritage preservation. However, manual work highly relies on the rich skills and experiences of the restoration masters. Not only does manual restoration take a lengthy time but also years of training and practice [29]. In comparison, training to handle additive manufacturing needs less time and the successive layer-by-layer working principle makes 3D printers able to produce replicas with intricate shapes in shorter times.

55.1.2 Accuracy Accuracy or precision is one of the most distinguished features of AM. With computer-controlled 3D scanning and printing, additive manufacturing can produce replicas with precise dimensions.

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researchers and archaeologist are able to use and manipulate the high-quality 3D printed replica without worrying about damaging the original heritage [2, 18]. With the four advantages mentioned above, AM is widely employed in a variety of cases of archaeological restoration and cultural heritage preservation. However, the wide variety of use cases brings challenges to the application of AM. On the one hand, tangible heritage can be made of different type of materials such as stone, metal, ceramic, and so on. Correspondingly, each material and surface finish can present different visual and tangible characteristics, such as color, reflectivity, and texture. For culture heritage preservation, in any replica produced with AM, these characteristics should be as mimetic as possible to the original [5–7, 24]. Nevertheless, on the other hand, although varied materials are now available for AM, such as gypsum metal, plastic, and sand [14], it still has limitations on color scheme and the choice of materials [9, 22], and the material quality of AM replica is one of the key concerns of museum visitors [28]. Therefore, one of the key challenges in the application of AM to CH becomes how to simulate the diverse visual and tactile features of cultural heritage with limited AM materials. In the following section, a number of use cases in publications are investigated to analyze the methods and processes of the employment of AM in the practices of culture heritage preservation.

55.2

Related Work

55.1.3 Tangible Accessibility Museum visitors prefer to “feel” the cultural heritage by touching rather than just see them through glass case [4], and visually impaired people need to know about the heritage through touching experience rather than only by listening to “other’s” interpretation [28]. However, for the protection purpose, the original artifact is usually untouchable, and their digital archives can only provide visual or audio information. By reproducing accurate copies that can be handled by people, AM extended people’s multiple-sensory interactive experience with cultural heritage [28]. The tangible surrogates of the original cultural heritage become accessible to museum visitors, students, or visual impaired people, who can touch the copy to learn about the heritage rather than just through visual images [12].

As aforementioned, the purpose of cultural heritage preservation can be diverse, and the materials of artifacts can be vastly different; therefore, it is impossible to investigate all types of materials used in CH. In our study, the collection galleries in the British museum, UK [8], and the Palace Museum [23], China, are used as a reference to check what common materials are present in CH objects. With comparison and categorization, three types of materials commonly used in CH artifacts were identified, which are: (1) stone (used in sculpture, jewelry, etc.), (2) metal (used in sculptures, wares, jewelry, weapons, etc.), and (3) ceramic (used in wares, sculptures, etc.). Correspondingly, literature reviews were conducted to investigate how AM is employed in the CH artifacts made of these materials.

55.2.1 Stone 55.1.4 Manipulability As in most cases, the original cultural heritage artifacts are unique and impossible for the researcher to manipulate it to do an investigation. With additive manufacturing, the

Culture heritage made of stone can be traced to prehistoric civilization. Two case studies were investigated from publications: one is an engraved limestone slab from upper Paleolithic [5] and another is a group of sculptures made of marble from the period of “1580s” [6]. In the first case, both

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thermoplastic and fine sandstone power were tested as AM materials. The following comparison and analysis work with software package Geomagic Studio showed that thermoplastic has better performance in geometric precision, and the evidence has been provided that this was not caused by 3D printer but material. In the second case, a sintering technique using a polyamide (nylon) and fused deposition modeling (FDM) are compared, which shows the sintering photogrammetric model has much better performance in producing details compared to FDM. In these cases, data calibration and subsequent manual finishing, such as sandblasting and painting, were applied to improve the appearance of the replica. For instance, in the first case, to enhance the tactile experience, the augmented method used here was to increase the depth of the engraving in the digital model with software in order to produce a deeper engrave in the 3D printed replica.

55.2.2 Metal People have worked with metal since 3300 BC [16]. Nowadays, AM is able to process a wide range of metallic materials, such as titanium, stainless steel, aluminum, and so on [25]. However, most metal 3D printing is used in the manufacturing sector [11] and the application in CH is limited. In addition, although metal AM is able to produce a part with close or even better performance than that made by traditional manufacturing [3, 20], some issues limit its application, such as efficiency, cost, and high requirement for the experience of the manufacturing technicians [13, 25]. An example is a head of the Arringatore statue, originally made of bronze [26]. The project team used white resin printed by a photopolymerization technique to obtain a replica with precise geometry. After that, hand painting and accurate finishing were used to improve the final appearance of the replica to simulate the bronze material and aging patina.

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materials [15]. Compared to the other two, the distinguished feature of porcelain is its glossy layer of glaze, which can bring a challenge to 3D scanning and material simulation with AM. One example from the literature review is a blue and white porcelain vessel from China’s Qing Dynasty [21]. The additive manufacturing technology used here is selective laser sintering (SLS), a type of powder bed fusion AM technology, with thermoplastic powder, which resulted in a precise replica with fine surface. To simulate the glossy glaze, the replica was manually cleaned, sanded, and then dipped in a solvent.

55.2.4 Section Summary In most use cases, significant efforts were made to test different types of AM materials, and in many cases, at the end of the project, it remains inconclusive which type of AM material is the best choice as each one has various challenges and imperfections. Interestingly, although the original artifacts are made of varied materials, plastic-like AM material is often preferred in practice due to its good performance in geometric precision and surface quality (see Table 55.1). For instance, after trying both gypsum and SLS nylon powder, the decision was made in favor of the latter to reproduce a bust from nineteenth century whose original material is also gypsum [14]. In addition, the application of AM to cultural heritage is a cross-disciplinary activity; communication and collaboration among all stakeholders are essential. In the aforementioned cases, researchers needed to work with 3D technicians, 3D printing service providers, and archaeologists to get the work done. However, there is still a lack of guidelines about the application of AM in the cultural heritage area [28]. In the following section, projects conducted by the authors are presented to further demonstrate the explorations of the application of AM in CH area.

55.3

Case Studies

55.2.3 Ceramic Ceramic can present in a different type of form. Ceramic, terracotta, and porcelain can be all considered ceramic

The studies in the reviewed publications shared valuable experience and knowledge towards the application of AM in the cultural heritage preservation field. However, the

Table 55.1 AM technology and material for CH artifact Material category Stone Metal Ceramic

Cultural heritage Item Engraved man’s face Group of sculptures Arringatore statue Blue and white vessel

Original material of cultural heritage Limestone Marble Bronze Porcelain (color is underneath of the glaze)

AM technology and material SLS, thermoplastic SLS, polyamide Stereolithography (SLA), polymer resin SLS with thermoplastic powder

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research in this area is still in its infancy, and the limitations are observed. In this section, a number of case studies conducted by authors are presented to explore more possibilities in creatively employ AM in cultural heritage preservation with the emphasis on materials. Consistent with the projects in publications, the materials of stone, metal, and ceramic are covered in our projects. In addition, a project with combination of metal and a special type ceramic, cloisonne, is also presented to further demonstrate the application of AM in cultural heritage. In addition, the cases studies can also be categorized into two types of projects: one is the production of replica and another is the product design based on data collected from cultural heritage artifacts. For the aspects of materials, the methods can be categorized into two directions: one direction is to simulate the original artifact material with AM material; another approach is to create a mold with AM rather than the replica to bypass the limitations of AM materials. In the selection of AM technologies, several factors were considered, for instances, the accuracy and quality of the 3D printed objects, the cost, the availability on AM machines for the projects, and so forth. In addition, due to the limitation on time on each project, it was not feasible to test each AM technology, instead, based on the authors experience and if the resources available, the AM that can produce objects with high surface quality were employed, for instance, powder bed fusion AM, or selective laser sintering (SLS) in particular. In addition, in most cases, AM is seen as one stage in a process chain. The integration of conventional craftsmanship and other technologies is proven key to guarantee the success of the projects. The details are introduced and discussed in each project as follows.

Fig. 55.1 Original marble enclosure

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55.3.1 Stone: Marble Enclosure in the Palace Museum The project related to stone material is to build a replica of a marble enclosure, which is a flower tree relief sculpture on the ceiling of the Green Conch Pavilion that is located in the Palace Museum, Beijing (Fig. 55.1). The enclosure has low relief on both sides in an arc shape. The original piece was scanned, and a digital model was generated in GOM (Precise Industrial 3D Metrology package developed by ZEISS company) first and imported into 3D Coat for texture rendering. The texture was captured by photography and imported into the software. Then, mapping of the digital model with the texture photos and adjusting the model to the desired size was performed to present the final appearance of the replica in 360 in virtual space, as shown in Fig. 55.2. To simulate the marble material, two aspects need to be considered: the color and the texture. Therefore, the project reviewed the characteristics of different AM technologies and materials and made the decision to use color AM. The colored digital model was firstly scanned and exported in the OBJ and PLY formats to produce colored physical models on a ZPrinter650 machine directly. The color was adjusted and evaluated digitally, and a very small-scale physical model was preprinted as a test part. As the Z-Corp system was using a powdered material, it gave a textured effect that ideally suited the simulation of the surface of marble texture. Without any other finishing, the color of the model was seen as being reasonably similar to the original (Fig. 55.3). Compared to the aforementioned cases in publications which used mono AM materials, color AM material is used

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Fig. 55.2 Picture of the 3D model of marble enclosure

Fig. 55.3 Replica with color AM material

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to simulate the marble color, and with the texture directly created by the powdered AM material, post finishing is not needed so that extra time and cost were saved.

55.3.2 Metal: Bronze Lion Sculpture in the Summer Museum

Fig. 55.4 Original lion sculpture made of bronze

Fig. 55.5 Master AM replicas produced with AM

This project was to build replica for the bronze lion sculpture located in Summer Museum, around 600 years old (as shown in Fig. 55.4); the replica will be exhibited in a new garden museum. The client required the replica to be as realistic and similar as possible to the original one, which brings great challenge to AM as the bronze and its patina will be difficult to simulate with AM material. Therefore, the project team decided to build a version of the replica with SLA machine (RS6000) first. Since the sculpture was over 2 m tall, the 3D data was manipulated to several small pieces to print and then assemble to get the master replica of the lion (Fig. 55.5). Rather than directly use the replica, the next step was to use the AM replica to build a mold and then build a bronze replica with conventional casting techniques. The cast bronze replica was then treated with conventional techniques to add the patina effect (Fig. 55.6).

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Fig. 55.6 Final bronze replicas established

In this case, the project team built the mold based on the replica produced with AM rather than directly use the replica, which bypassed the limitations of AM materials but combined the advantages of AM in building intricate geometry and conventional manual techniques in casting and post treatment.

55.3.3 Ceramic: Porcelain Vase and Enclosure The first project related to ceramic is to convert a 2D painting to 3D object. The painting, titled as “Shi Yi Shi Er Image,” was made by Emperor Qianlong in the Qing Dynasty of China (Fig. 55.7). The museum that owns the paintings expected to build the 3D model based on the painting for the exhibition to enhance interaction with the audience. With the support from archaeological experts, the vase in the painting is believed to be Ru Yao, a type of porcelain from the Song Dynasty (around 900 years ago) with light blue color. The project team discussed the possibility of directly using AM material to simulate the color and glaze of the porcelain. However, this route was abandoned based on a review of the limitations of the color schemes of the available AM machines. Instead, AM was used to build a model with photopolymer material, as shown in Fig. 55.8. After that, the

Fig. 55.7 Original painting from Qing Dynasty

color, gloss, and aging treatment were added with manual painting to simulate antique porcelain (Fig. 55.9). Another case is to restore an enclosure on the window in the Palace Museum, which is a piece of famille-rose porcelain from Qing Dynasty, is shown in Fig. 55.10. The famillerose has a much richer color. In addition, the mineral pigment used for the color is on top of the glaze and creates reliefs, which can be seen from the 3D scanned image in Fig. 55.11. The characteristics of this type of porcelain make it difficult to directly use AM color printing due to the rich color combination of the artifact and the limitation of AM color schemes. In addition, the process used on the “Ru Yao” is also difficult to use here since it would take much longer to match the very rich colors. To solve these problems, the project team took high-resolution pictures of the original porcelain and then used a 2D printer, UJF-3042HG from Mimaki, to print the picture on the surface, as shown in Fig. 55.12, which is the final result after a number of adjustments to saturations and lightness in software and matching between the image and relief in the machine. Both project results were reviewed by experts and nonexperts, the feedback showed that the quality is generally good but some aspects are still subject to improvement, for example, the experts still have higher expectations for color

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Fig. 55.8 AM replica with photopolymer material

Fig. 55.10 Original porcelain enclosure from Qing Dynasty

Fig. 55.9 Final replica exhibited

quality. Table 55.2 shows the feedback for the second porcelain project. Fig. 55.11 3D scanned data shows the relief texture of the porcelain

55.3.4 Integrated Metal and Ceramic Printing: Cloisonne Restoration – AM Material Replacement The cloisonné pieces are typically installed on wood furniture or for interior decoration, and some pieces from the Palace

Museum have gone missing or been damaged over a period of hundreds of years. The traditional method of manufacturing cloisonné is complicated and time consuming, which involves forging, wire inlay, enamel filling, enamel firing, polishing, and gold plating. Forging is used to produce a copper “base model” and then designed patterns are drawn

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Fig. 55.12 Final result with 2D printing on AM replica

Table 55.2 The feedback from the participants on the quality of the prints (the numbers refer to the number of participants in that category) [19]

Quality parameter Measurements Visual effects Resolution Color Texture Surface roughness

Excellent Good Acceptable Participants (E: expert; N: nonexpert) E N E N E N 3 2 1 3 1 2 2 1 2 2 2 1 1 2 2

Poor E

N

1 2

on it (Fig. 55.13a). Wire filling is when thin bronze wire is shaped to fit the drawn patterns on the base model and attached with plant glue to form groove spaces (Fig. 55.13b). Enamel filling is used to place mineral pigments into the groove space (Fig. 55.13c). Enamel firing involves putting the colored model into oven repeatedly and requires strict control of firing temperature (Fig. 55.13d). Sanding/polishing uses a polishing machine with abrasive powder to make the bronze wires and colored parts have a smooth, flush surface (Fig. 55.13e). The last (optional) step is using gold plating to improve the artistic effects over a relatively large surface area (Fig. 55.13f).

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This experiment was to try to reproduce both the colored parts of cloisonné and the bronze wires using AM materials as replacements. If successful, this would simplify the manufacturing procedure, avoid man-made errors, and dramatically reduce time and cost. The innovative method started with photography and non-contact 3D scanning of a symmetrically similar part (Fig. 55.14). Once again, an ATOS 5M blue light scanner was adopted to scan the existing cloisonné part within dimensions of 258 mm  131 mm (Fig. 55.15), as well as a 2-mm deep recess in the wooden base that had held the missing part (Fig. 55.16). Photos had to be taken under a shadow-less lamp to obtain accurate color codes. Two data manipulation techniques were needed to acquire the digital model. The first was remodeling the entire 3D model based on the scanning data using RE techniques, and the second was extracting just the wire patterns based on the photos using imaging techniques and CAD modeling to build a 3D model (Fig. 55.17). Both methods were thoroughly tested by this case study. It was very time consuming to distinguish the bronze wire from the colored parts when using RE, especially when relying almost entirely on the vertex colors generated during scanning of this flat part. Small defects and pieces of dirt blurred the boundaries. This also caused difficulty when extracting patterns using photo-imaging techniques. In addition, accurate CAD replication of handmade pattern curves was another challenge. The digital model of the bronze wires was built first, with wire walls as thin as 0.26 mm, and all wires sat on a 1 mm thick flat bronze platform to form the groove spaces (Fig. 55.18a). The spaces for the colored enamel parts were then created through a Boolean operation and combined with a texture map generated from highresolution photos (Fig. 55.18b). The bronze wire part was then exported as an STL file for AM building with a wax material. A Projet CPX machine was adopted to produce a good surface quality pure wax model, as the very thin walls could not withstand any finishing and pure wax was easier to bronze cast than a wax and resin mixture (Fig. 55.19). The wax model was immediately sent for bronze casting to avoid thermal or mechanical deformation. Also, in this case study, the flat thin plate shape object would easily bend during and after casting and so two pieces of fireproof flagstone were used to keep the artifact flat (Fig. 55.20). After casting, minor finishing and aging treatments were applied to the bronze model to achieve a similar effect to handmade parts (Fig. 55.21). The bronze part was now ready for interaction testing with the full color AM materials. Meanwhile, the digital model of the colored parts was exported as an OBJ file to be used in an AM machine

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Fig. 55.13 (a) Forging. (b) Wire filling. (c) Enamel filling. (d) Enamel firing. (e) Polishing. (f) Gold plating

Fig. 55.14 Symmetrical piece

capable of producing full colored physical parts. This part of experiment was firstly undertaken in Deakin University, Australia, who used their Objet Connex 3 to build a full color resin model. However, both the glossy and matt effects of the resin material were too smooth to simulate the enamel texture. Thereafter, a Projet 660 Pro machine

was adopted to produce the full color enamel parts, giving a better surface texture effect and also a lower cost. The colored parts needed to be cleaned off from the printing platform while keeping all the separate pieces in their original positions. This required great care since the powder printing material was very fragile and the patterns were quite complicated (Fig. 55.22). Theoretically, the bronze and enamel parts could have been produced simultaneously as they used separately independent procedures. However, the bronze part was produced first to test the shrinkage rate, which is normally 2.5–3% (comprising 0.5% shrinkage when building the wax model and 2–2.5% during bronze casting). The precise shrinkage rate is affected by the properties of the bronze and the thickness of the solid part. Therefore, it was necessary to either enlarge the digital model of the bronze part by 2.5–3% or reduce the colored parts model by the same amount. However, since the final part needed to fit the wooden base, the latter route was not acceptable. After assembly of all color parts together by inserting bronze wires, minor finishing like soaking in super-glue was applied to make the colored parts more robust. A physical aging treatment was only required for the bronze wires, since the color parts’ aging effect could be created when generating the texture map (Fig. 55.23). The

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Fig. 55.17 RE/CAD modeling Fig. 55.15 Scanning

Fig. 55.16 Wood base of missing part

final replacement cloisonné was then evaluated by experts, deemed acceptable, and installed on the original relic (Fig. 55.24). A questionnaire was designed to evaluate the application of digital technologies in antique restoration, souvenir design, archiving in 2D and 3D databases, and defect analysis/repair. Experts and nonspecialists from the Palace Museum were asked to evaluate various outcomes in comparison to those produced using traditional methods using the criteria of quality, time, cost, accessibility, and feasibility of

Fig. 55.18 (a) Bronze model rendering. (b) Enamel model with colored map

remote working. The questionnaire was completed by three experts from the architecture, technology, and information departments, and two nonspecialists from sales and

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Fig. 55.21 Bronze wire part

Fig. 55.19 AM wax model

Fig. 55.20 Bronze part fixed with flagstone

administration. The experts evaluated the outcomes against all the criteria whereas the nonspecialists only evaluated the quality of the finished parts produced. They were asked to rate the digital method as being excellent, good, acceptable, or poor in comparison to the traditional methods used previously. The results (as shown in Table 55.3) were mainly positive and indicated that the use of the process chains resulted in the production of high-quality, cost-effective

Fig. 55.22 AM colored part after cleaning off the printing platform

outcomes. There were some issues arising that needed to be investigated with further experiments, such as aging treatments on AM materials and transportation for remote working. In addition, a wider group discussion was held involving people from additional departments, and a summary of comments is shown in Table 55.4.

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Fig. 55.24 Installation

Fig. 55.23 Assembling and finishing

55.3.5 Product Design: Dragon Plaque and Antique Coin The projects presented above show the contributions of AM in cultural heritage preservation by creating physical replicas with various process. However, most of the replicas still stayed in their respective museums for exhibition, which limited visitors’ daily interactions with them. In this section, two projects conducted by the authors are chosen to demonstrate creative product designs based on cultural heritage to “bring cultural heritage to broader masses of people.”

The first project is to develop a souvenir product based on a dragon plaque (Fig. 55.25) which is 500 mm in diameter. The 3D scanned data of the plaque was reduced to 250 mm diameter, and a translucent plate was created by manipulating the surface of the model into a hollow form and adding a plate shape to the outside of this. The Objet Vero Clear material was used in AM process, and the surface finish was quite impressive and required almost no post-processing. All the details of the high relief and hollow structure could be seen clearly inside the plate just like a delicate glass art-craft (Fig. 55.26). The plate can now be sold as a souvenir and the customer can use it to decorate their home or office where they can see it daily. The second project explored the possibility to bridge the “old” with the “new” by combining an antique coin from Song Dynasty (around 900 years ago) with a modern computer mouse (Fig. 55.27). As a tool that is used every day by many people, it is expected that cultural heritage can be realized in it. A computer mouse from the market was chosen for the experiment, and the antique coin was from a coin collector. The mouse and coin were then 3D scanned, and the 3D data was manipulated in software. For the mouse, the 3D data

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Table 55.3 Evaluation results Criteria 1. Quality

Accuracy

Measurements Visual effects

Resolution/details Color Texture Surface roughness

2. Time

Aging treatment/match with the original Measuring Design solution Manufacturing Finishing

3. Cost

Transport Installation Labor Material Error/failure

4. Accessibility

Labor Facility Material

5. Feasibility of remote working

Feedback and number of responses from experts Excellent 3 Excellent 1 Good 2 Excellent 2 Good 1 Good 2 Acceptable 1 Good 2 Acceptable 1 Excellent 1 Good 2 Needs further experimentation

Excellent 1 Good 1 Excellent 2 Excellent 1 Good 1 Excellent 2

Excellent 2 Good 1 Good 2 Acceptable 1 Excellent 2 Good 1 Good 1 Acceptable 2 Needs further experiments Good 3 Good 3 Excellent 1 Good 2 Excellent 2 Good 1 Acceptable 3 Excellent 2 Good 1 Excellent 1 Good 2 Excellent 2 Good 1

Table 55.4 Summary of comments and group discussion Advantages Accuracy is better than that achieved by traditional methods Multiple perspective and omnidirectional measurements Regular 3D scanning and comparative analysis Repairing accurately, combining with the original parts seamlessly Diversity of materials and effects brings developing prospects Database can be used for archiving, repairing, demonstration, and replication

Feedback and number of responses from nonexperts Excellent 2 Excellent 2

Issues to be solved Storage and manipulation for mass of data Feasible and easily operated process chains need to be applied universally in relic preservation area

was optimized with reverse engineering to make sure it can be used for reassembly after AM process. For the coin, the 3D data was optimized in Zbrush to make it as similar as possible to the original coin. For example, to make the edge of the coin as sharp as the original since in the raw data from 3D scanning, the edges were rounded. The data of mouse and coin are then merged together in Autodesk (Fig. 55.28) and printed with SLA resin material, painted, and then reassembled to get a new fully functional and highly personalized computer mouse, as shown in Fig. 55.29. The two product design cases show the possibility to bring cultural heritage from museum to society and daily life with support of AM. However, these attempts are still in the experimental stage, and concerns like high unit cost and copyright need to be further investigated in the future.

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Fig. 55.27 The antique coin and computer mouse Fig. 55.25 The golden dragon plaque

applications, for instance, the difficulties in simulating artifact materials with AM material. One strategy utilized was to integrate AM into a process chain to combine the strengths of each technology or technique in order to get the desired result, which is shown in Fig. 55.30. The process chain indicates that the project team needs to analyze the features of the original artifact and choose the proper AM machine and material; the replica model created by AM can either be used directly or used to create a mold or pattern for casting; finishing, such as manual painting and assembly, is usually needed to simulate the original artifact material and guarantee the final product is functional when required.

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Fig. 55.26 Product design based on the CH: dragon plate

55.4

Proposed Process Chain

Along with the related works in publications, the case studies conducted by the authors further demonstrated the feasibility of the use of AM in cultural heritage preservation and related product design. However, no technology is omnipotent, and the limitations of AM are also clearly realized in these

Limitations and Future Work

The case studies above show the feasibility of the application of AM in the CH area. With the integration of other technologies, the AM can play the distinctive role in the replication of different types of materials and product design. However, due to limitations on time, cost, and available technology and hardware resources, mainly powder bed fusion was used to produce 3D printed objects. In addition, the projects the authors conducted so far are mainly from museums in China, and therefore, the artifacts presented in the case studies are limited to the oriental culture. In the future, it is expected that the different types of AM can be tested on more cultural forms. For instance, recently the authors are about to work with a museum in the UK on cultural heritage preservation with AM technology.

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Fig. 55.29 Redesigned computer mouse Fig. 55.28 Merged 3D data

55.6

Conclusion

In 2014, Clark et al. [10] proposed that additive manufacturing was still at the early innovator stage, with another 15–20 years to go. During this period, it is still necessary to explore more possibilities to expand the application domains of AM, and cultural heritage preservation is one such domain. AM’s ability to create objects with intricate geometry enables the creation of replicas of relics, many of which have a complex structure. However, the complexity of cultural heritage artifacts is not only in their geometry but also in the visual aspects generated by materials or pigments. This brings a great challenge to AM as it still has significant limitations in material and color scheme. In addition, cultural heritage preservation should not be limited to producing

replica. With the support of AM, personalized souvenirs or products based on cultural heritage can be designed for people to use on a daily basis. In this way, AM plays a role in bridging the “old” with the “modern” and bringing cultural heritage to a greater mass of the public, which is significant for the purpose of preservation. Therefore, to complete the diverse tasks, AM should be integrated into a process chain together with other technologies and techniques, such as 3D scanning, CNC machining, and manual craftsmanship. The process chain requires the collaboration of people with different expertise, so teamwork is key to guaranteeing the quality of the work. The proposed process chain was generated based on the literature review and the authors’ work in the past. However, since each relic is unique and brings specific challenges, the process chain is still subject to modifications and optimizations in the future after more projects are conducted and investigated.

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Project Analysis

Customising solutions

3D scanning

Design and data manipulation

Data transferring

AM technology and material choice

Additive manufacturing

Material simulation

Moulding

Casting with chosen material

Assembly and post finishing Replica or product

Fig. 55.30 Process chain of the application AM in CH preservation and product design

References 1. Al-Baghdadi, M.A.S.: 3D printing and 3D scanning of our ancient history: preservation and protection of our cultural heritage and identity. Int. J. Energy Environ. 8(5), 441–456 (2017) 2. Al-Baghdadi, M.A.S.: 3D scanning, 3D virtual reality, and 3D printing for Najaf Holy City’s cultural heritage and identity. Int. J. Energy Environ. 9(5), 515–528 (2018) 3. Anam, M.A., Pal, D., Stucker, B.: Modeling and experimental validation of nickel-based super alloy (Inconel 625) made using selective laser melting. In: Solid Freeform Fabrication (SFF) Symposium, pp. 463–473. University of Texas at Austin, Austin, 12–14 Aug (2013) 4. Baker, J.: Anarchical artifacts: museums as sites for radical otherness. In: Witcomb, A., Message, K. (eds.) The International

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Bingjian Liu is Assistant Professor and Course Director of Product Design and Manufacture at the University of Nottingham, Ningbo, China. He received his BEng in Industrial Design from Shandong University, China, and his MSc and PhD in Industrial Design from Loughborough University, UK. His research interests include cultural heritage in product design with additive manufacturing, design thinking in new product development, and the integration of physical and virtual prototyping.

Fangjin (Virginia) Zhang received her master’s and doctorate degrees at Loughborough University Design School, and then she kept working in LDS as a Research Associate in the area of digital archaeological restoration with the British Museum UK, Palace Museum China, and Kyoto University Japan. Her main research and publications are in the areas of digital manufacturing and archaeological restoration, which have been presented at conferences in the UK, Australia, China, and Japan. She undertakes both research and commercial projects, keeps researching and developing enterprise, delivers educational courses and training in interdisciplinary subjects, and tries to fill the gap between knowledge and practice.

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Xu Sun is a Professor in Product Design and Manufacture at University of Nottingham Ningbo China. She is a Chartered Technological Product Designer of the Institute of Engineering Designers (iED, UK). She obtained her doctorate degrees from Loughborough University and Eindhoven University of Technology (TU/e) and was a postdoctoral research fellow at Leicester University and University of Nottingham. Her research in “Human-Centred Design” has produced new products on the market, over 20 patents, and over 70 peer-reviewed publications.

Adam G. A. Rushworth was born in Keighley, UK, in 1986. He received an MEng degree in Mechanical Engineering with Mathematics in 2011 and a PhD in Mechanical Engineering in 2016 from the University of Nottingham, UK. From 2015 to 2016, he worked as a Research Fellow at the University of Nottingham. Since 2016, he has been an Assistant Professor in Materials and Manufacturing in the Department of Mechanical, Materials and Manufacturing at the University of Nottingham, Ningbo, China. His research interests include robotics, mechatronics, additive manufacturing, and automation. He is an inventor on seven patents.

56

Tissue Engineering Pedro Gil Frade Morouc¸o

Contents 56.1

Tissue Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 941

56.2 56.2.1 56.2.2 56.2.3

Key Features on 3D Constructs . . . . . . . . . . . . . . . . . . . . . . . . Biocompatibility and Biodegradability . . . . . . . . . . . . . . . . . . . Mechanical and Topological Properties . . . . . . . . . . . . . . . . . . Manufacturing Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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56.3 56.3.1 56.3.2 56.3.3 56.3.4

AM Techniques for 3D Constructs Fabrication . . . . . . Inkjet Printing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Robotic Dispensing Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Laser-Induced Forward Transfer . . . . . . . . . . . . . . . . . . . . . . . . . Stereolithography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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56.4

Further Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 948

56.5

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 949

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 949

Abstract

A tissue or organ may fail due to trauma, tumor, congenital disease, or other pathology. When that occurs, the standard clinical procedure includes transferring healthy tissue to the damaged site in the same patient or transplanting a functional organ from a donor. Nevertheless, it is clear to see that there are great inconveniences: the shortage of donors, rejection risk, and the diseases broadcast. It has become essential to develop new medical therapies in this area, and tissue engineering (TE) evolved to be a solution. While there are numerous approaches in the TE domain, in this chapter, we will only focus on using additive manufacturing (AM) technologies to build 3D constructs aiming to mimic the native human tissues. Difficulties and constraints are presented, followed by the available methods to manufacture. Some examples are provided for hard and soft tissue, exploring the future expectations on the field. P. G. F. Morouço (*) Polytechnic of Leiria, Leiria, Portugal e-mail: [email protected]

Keywords

Bioprinting · Biomaterial · Bioactive scaffolds · Personalised medicine · Translational research

56.1

Tissue Engineering

Tissue engineering (TE) is an interdisciplinary field that applies engineering principles along life sciences to develop biological substitutes that can restore, maintain, or improve tissue function of their injured or diseased counterparts in vivo [1–3]. However, there are several challenges to overcome: the lack of renewables sources of functional and compatible cells, the lack of biomaterials that provide adequate properties (mechanical, chemical, and biological), and the high difficulty in generating high vascularization or diffusion within the matrix [4]. Research has reported significant breakthroughs in each of these domains [5], scaling from lab testing to animal and clinical trials in the past decade. It is, however, essential to gather a more profound knowledge in biology, materials science, chemistry, and engineering [5, 6], to scale up to everyday practice with disseminated strategies. TE’s field is widely multidisciplinary, including specialists in medicine, materials science, genetics, engineering-related disciplines, and life sciences [7]. Commonly, the aim is to develop a scaffold as a three-dimensional (3D) structure highly porous that would provide the structure for the setting, development, and proliferation of cells [8]. Scaffolds are used to fill tissue voids, provide structural support, and provide growth factors and cells that could form tissues within the body after transplantation [2, 9]. These perform as a pattern for tissue formation and generally comprise seeding and culturing cells in porous 3D scaffolds exposed in a bioreactor (a device that carries out diverse types of chemical or mechanical stimulus to the cells) to biophysical stimuli. Cell-seeded scaffolds may be cultured in vitro to synthesize tissues that can be introduced into a wound site or directly implanted into the injured area,

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_56

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and regeneration is induced in vivo [7]. These relationships between cells, scaffolds, and signals, are frequently named a triad [10] and can be assured by biofabrication strategies: bioprinting and bioassembly [11].

56.2

Key Features on 3D Constructs

Numerous scaffolds have been produced from a diversity of biomaterials and manufacturing techniques, aiming to regenerate different types of tissues [11]. Regardless of the used method, it is critical to design a scaffold according to biocompatibility, biodegradability, mechanical and topological properties, and manufacturing processes [12].

56.2.1 Biocompatibility and Biodegradability It is scoped that loaded cells usually act, migrating along the surface and through the scaffold regarding biocompatibility. They will start to proliferate and create a new matrix. The

a) 120

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scaffold should not trigger any undesired reaction to avoid any inflammatory response, leading to rejection by the body [7, 13]. This is a critical feature that should be combined with the degradability of the biomaterial. The scaffold must act as a support structure for a finite period, permitting a new healthy tissue to mimic the original native tissue [14]. Attention should be considered, as the products of this degradation must be nontoxic and capable of leaving the body without interfering with other organs. Therefore, it should degrade along with tissue formation, with a combined inflammatory response required with the controlled infusion of cells, such as macrophages. One of the attractive tissues that researchers have been trying to mimic is bone. Combining biomechanical and physiological features is challenging and has promoted a wide range of methodologies. For instance, using iron scaffolds made by extrusion-based 3D printing, authors obtained a porosity of 67%, pore interconnectivity of 96%, and a strut density of 89% after sintering [15]. With 28 days of in vitro biodegradation (reduced from 0.28 to 0.11 mg/cm2/day), the mechanical properties remained in the range of trabecular bone (Fig. 56.1).

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Fig. 56.1 Mechanical properties of the porous iron scaffolds: (a) compressive stress-strain curves, (b) the yield strength and elastic modulus, and (c) the ultimate strength and strain at failure of the scaffolds

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before and after in vitro immersion for up to 28 days. (Reprinted with permission Ref. [15] © 2021 Elsevier)

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56.2.2 Mechanical and Topological Properties Mechanically, constructs should provide features allowing [16] the surgical manipulation during implantation and having an adequate balance between the mechanical properties and their integrity to allow vascularization and cellular absorption [10]. Researchers should tailor the scaffold porosity, as the pore architecture is critical in cell culture and tissue design. This will promote homogeneous cell dispersion, cell differentiation, and host tissue growth after implantation [17]. Scaffolds must present an interconnected pore structure and high porosity to ensure cell introduction, nutrient propagation, the diffusion of waste products outside the scaffold, and the degradation of products that can leave the body without interfering with the remaining organs and tissues surrounding areas [7]. Furthermore, the mean pore size is also essential. Through the chemical groups (ligands) on the material’s surface, the cells interact with the scaffolds. The binder’s density is influenced by the available surface area within a pore at which the cells can adhere and depend on the scaffold’s average pore size [18]. Thus, the pores need to be large enough to allow the cells to migrate to the structure, where they bind to the ligands within the scaffold, but small enough to establish a satisfactorily high specific surface, leading to minimal binding with the efficient connection of the ligand [7, 19, 20]. Hence, a critical range of pore size may vary depending on the type of cell used and the tissue being handled [21, 22]. Using AM technologies, it is possible to produce accurate tissues for TE applications. Thus, researchers can control the design to address the issues mentioned above and even address vasculogenesis’s major problem. Recently, pre-vascularized nano-hydroxyapatite (nHA) functionalized PCL scaffolds were implanted into large bone defects [23]. This group developed a 3D printing strategy that in 12 weeks increased early bone formation. Further studies will

a)

demonstrate its suitability on larger scale models and be useful for tissues susceptible to diminished oxygen or nutrient availability (Fig. 56.2).

56.2.3 Manufacturing Process

56 The adopted manufacturing technology is critical to developing scalable manufacturing processes for the good manufacturing practice, promoting TE strategies into the clinic. That states that how a product will be delivered and made available to the clinic should be considered, as it will determine how the scaffold will be stored and handled [7, 8]. For instance, for bone TE, researchers should consider the scaffold’s volumetric fraction, the bone volume of the scaffold, the total volume of the bone, and the densities of scaffolds and mineral bone. Thus, the requirements to engineering a scaffold to be used in the vertebral column will be remarkably different from those used in the femur. The human body’s anatomical and mechanical complexity requires additional conditions to match a more distal or proximal implant at the same bone. The optimal mechanical properties and load-bearing as in native bone are still paramount to be clarified [24, 25]. Considering osteochondral tissue as a complicated hierarchical example, printability requirements are critical [12]. Indeed, when addressing osteochondral defects, not only attention should be given to bone and cartilage, as well as their interface. One possible strategy to obtain a combination of different biomaterials for constructing functionally graded scaffolds is using various techniques within the same system. Accordingly, we have recently proposed gathering on the same system a micro-extrusion, a multi-head hydrogel dispensing approach, and electrospinning modules [26] (Fig. 56.3).

b) 4 mm

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Fig. 56.2 Femoral defect study schematic. (a) Porous PCL scaffold design. Two PCL scaffolds were bioprinted; both were 4 mm in diameter and 5 mm high and coated with nHA. One scaffold was left empty while the other was filled with PV bioink. (b) SEM images depicting nHA

coating and confocal images of microvessels within scaffolds. In images i, ii, iii, and iv, the scale bars are 100 μm, 2 μm, 200 nm, and 50 μm, respectively. (Reprinted with permission Ref. [23] © 2021 Elsevier)

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a)

b)

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Fig. 56.3 The BioMaTE equipment consists of the following units: (A) micro-extrusion system, (B) multi-head dispensing module, (C) monitoring and photopolymerization modules, and (D) electrospinning system. (Reprinted with permission Ref. [26] © 2021 Trans Tech Publications Ltd.)

Using different technologies within the same equipment may provide convenient features to tackle the abovementioned issues. Significant advancements were achieved by Poietis Company, with a new generation clinical-grade system. Its GMP-compliant bioprinter enables the manufacturing of human living tissues in a closed system, under entirely aseptic conditions, within an isolator. Not only does it assures the repeatability of manufacturing operations but also ensures their complete traceability.

56.3

AM Techniques for 3D Constructs Fabrication

The fabrication of scaffolds was one of the pioneer applications of AM and one of the most successful, mainly because of its suitability to produce complex and customized structures [27]. Although scaffolds can also be manufactured using nonadditive processes, also known as conventional processes [28, 29], there are significant limitations to developing

tailored constructs. These techniques include: (i) solvent casting/salt leaching; (ii) phase separation; (iii) gas foaming; (iv) gas saturation; (v) melt molding; and (vi) particleleaching [29–34]. First, they do not provide adequate control of the pores’ size, geometry, and spatial distribution. Thus, constructing internal channels inside the scaffold is necessary. This drawback may lead to the inhomogeneous distribution of cells throughout the scaffold, lacking vascularization and subsequent nonuniform tissue growth. Secondly, commonly, their processing is based on toxic organic solvents, reducing the scaffold biocompatibility, making them unsuitable for living cells and biological molecules, long manufacturing times, and labor-intensive processes [28]. AM techniques have been used in the biomedical domain to overcome the limitations mentioned above. It is possible to obtain precise control over the architecture, shape, porosity, pore size, and pore interconnectivity in a wide range of materials through a layer-by-layer fashion. Therefore, AM technology is considered a more suitable TE scaffolds manufacturing approach [10, 29]. The first step to producing

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Tissue Engineering

scaffolds through AM techniques is to generate a model directly designed using CAD or obtained by medical imaging techniques (e.g., CT or MRI) that provide input data to develop a personalized model [35]. The template is commonly tessellated as an STL file, formerly cut in layers (slicing step). According to the CAD model, this last step may be uniform, leading to unvarying layers or adaptive, producing layers with varying thickness. Finally, the obtained data is physically reproduced using an AM system [29, 36].

56.3.1 Inkjet Printing Inkjet printing, also known as drop-on-demand printing, is a method that deposits cells and biomaterials to create 3D scaffolds with the benefit from other 2D printing [37]. It is a contactless technique with the distribution of a jet of tiny droplets of liquid material, called bioink, through a small hole on a substrate [17]. The jet stream specified in the software [38, 39] provides constructs loaded with cells capable of mimicking native tissue or organs [37]. Accordingly, the bioink can be printed as the cell culture medium and hydrogel [10, 40]. Also, it can read the digital data of a computer and reproduce it, layer-by-layer, depositing ink drops in successive layers previously printed [41]. The amount of different inks is dependent on the number of cartridges in the system. Each cartridge may be filled with varying precursors of hydrogel, cells, biological factors, or biomaterials with different mechanical properties [42–44], aiming for a tailored 3D construct. Using a new 3D inkjet printing process to fabricate anatomic site-specific tissue-engineered bone constructs, it was possible to mimic the morphometric and mechanical properties of human trabecular bone [45]. With more than >50% nanocrystalline hydroxyapatite, morphometric parameters were comparable to the bone templates from which they were fabricated. There are some advantages over these processes. Custom manufacturing, rapid production, low production cost, high resolution, reproducibility, versatility, ease of use, and speed in building scaffolds with 3D architecture are commonly stated. Yet, a significant drawback is the induced limitation on the polymeric materials that can be used. For many, the gelation time is longer than or equal to the time of deposition [37]. Besides, there are downsides in size limitation and biomaterials, a relatively low limit for fluid viscosity, and negligible mechanical properties. Moreover, with a small nozzle, cells become exposed to high shear forces during cell imprinting, leading to breakage or cell damage and inhibiting the possibility of printing at high cell densities, which is necessary to create functional tissues [10, 37, 41, 46]. The standard procedures to deposit solution droplets in a predefined pattern use thermal or piezoelectric energy [37]. In the former technique, small volumes of the print fluid are

945

vaporized by a sudden local temperature heating. Vapor bubbles collapse and jetted ink drops into the substrate [10, 17, 37]. Still, the generated heat can go up to 300  C, and the low evaporation can damage the deposited cells and cause transient pores in the cell membranes. Moreover, the thermal jet has considerable difficulties, such as the downward and nonuniform droplet size, limiting 3D biofabrication [10]. There is no heating required to adopt the impulse using a piezoelectric-actuated inkjet printing. Instead, an additive mechanical stimulation is applied by a proposed electric mechanism, creating a shock wave and, thus, allowing the deposition. Therefore, it controls the mechanical stress applied to the cells along the manufacturing process [17]. In other words, the piezoelectric crystals act within the compartment itself, increasing pressure and, as a result, ejecting the droplets [47]. The deposition occurs when an electric charge boosts vibration in the crystals [37, 48] (Fig. 56.4). Inkjet printing allows the processing of numerous types of polymer, ceramic, and composite materials at room temperature. It also enables the manufacture of constructs containing sensitive biomolecules (cells, growth factors, or drugs) using biocompatible binders, such as water-based binders [29].

56.3.2 Robotic Dispensing Systems The extrusion-based process is commercially recognized as fused deposition modeling (FDM) [29, 36, 49]. For this technique, small thermoplastic beads are solidified instantly

b

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Fig. 56.4 Illustrative representation of the inkjet printing system: (a) heater, (b) piezoelectric actuator, and (c) droplets of liquid material. (Original image from the author)

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after their extrusion in a layer-by-layer deposition method. It was developed at the end of the 1980s by S. Scott, and it turned out to be the basis for several other printing technologies [8]. Open source projects like Fab@Home promoted its use, significantly increasing its popularity and economic advantages [37]. The biomedical domain has been using it for manufacturing 3D constructs with biomaterials, with (also known as bioinks) or without cells [10]. An optimal bioink to be extruded must have the ability to be rapidly cross-linked (chemically or physically). This feature, along with a smaller shear for reduced resistance, will promote a successful extrusion of consecutive layers [37]. Equipment able to extrude biomaterials with a high cell concentration may accelerate neo-tissue growth and formation [38]. In this technique, fine thermoplastic polymers in filaments or granules are melted through an extrusion head, allowing the flux in the horizontal and vertical direction. A robotic device controls the deposition of the material in a 3D fashion. The material leaves the nozzle in a liquid state and hardens immediately [36], creating the first layer. This layer must be kept at a temperature slightly below its solidification point to

guarantee a successful adhesion between layers [8]. These processes can work with an extensive diversity of polymers, ceramics, and composites to produce 3D scaffolds for TE applications (e.g., bone, cartilage, periodontal, osteochondral, vascular) [29]. For example, using the same system, the combination of materials will dictate the final result’s properties. Taking poly(ε-caprolactone) and adding hydroxyapatite nanoparticles, we can obtain more mechanical strength [50], while adding poly(glycerol-sebacate), we can get remarkable flexibility [51] (Fig. 56.5). Furthermore, cell viability is enhanced with biocompatible materials, improving the mechanical properties throughout the printing process [37]. Although FDM is not compatible with cells that require super physiological temperatures, it may be modified to work with thermosensitive hydrogels [36] (Fig. 56.6). High print/form fidelity and complex multi-material constructions have stimulated the development of unique hybrid systems by combining different techniques within the same device. These consist of: (i) distribution system and stage with the ability to move along the three axes; (ii) light source to

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Fig. 56.5 (a) Bioextruder system and (b) stress-strain curve of the produced scaffolds (Reprinted with permission from Ref. [50] © 2021 Hindawi). (c) 3D structures of PCL/PGS. (Reprinted with permission from Ref. [51] © 2021 Trans Tech Publications Ltd.)

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Pneumatic system

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Fig. 56.7 Illustrative representation of a laser-induced forward transfer system: (a) laser pulse, (b) donor slide layer, (c) energy absorbing layer, and (d) cell-bioink layer. (Original image from the author)

b

Fig. 56.6 Examples of different approaches of the robotic dispensing systems: (a) inlet and (b) filament material. (Original image from the author)

activate a photoinitiator; and (iii) piezoelectric humidifier. Also, some equipment can use several printing heads, providing the solution to print various materials without retooling [10]. The main challenges faced by the extrusion-based processes are a higher printing speed and a higher resolution. Several investigations use a large variety of materials in the literature, as previously stated [8]. For bone TE applications, materials such as poly(ε-caprolactone) (PCL) and composite based on tricalcium phosphate (TCP) have been extensively used. The incorporation of ceramics aims to provide good mechanical and biochemical properties, providing anchorage places for growth factors [52]. Furthermore, some research mentions the use of unfilled polybutylene terephthalate scaffolds for trabecular bone repair. Although they do not mimic the natural bone function and chemical composition, their mechanical properties and microstructure are like native tissue [8, 52]. Finally, some experiments have tried to mimic natural bone function using hydroxyapatite nanoparticles [53].

living cells or molecules [54]. The materials are incorporated in a material irradiated by a nanosecond laser pulse, and the resulting eject is collected onto a receiving substrate [55]. It is based on the use of three layers of different components. The first is seated on a donor slide covered with a second layer of laser energy absorption and finally, the third layer with components of cell-bioink [56]. The focused laser pulses cause local evaporation of the absorbent layer, generating a high gas pressure and, consequently, imparting the bioink compound to the collector slide [56]. The resolution is determined by several factors: (i) laser (wavelength, repetition rate, and diameter of beam focus); (ii) bioink (viscosity, surface tension, and thickness); (iii) substrate (wettability, coating, and space); and (iv) layer absorption properties (elements and thickness) [10] (Fig. 56.7). The main advantages of this technique are precision (allowing accurate deposition of materials and cells in small 3D structures without negatively affecting cell viability or function), clog-free process (as it does not require the use of nozzles), and the use of a wide range of materials [10, 56]. Its easy configuration, high flexibility, and cost-effectiveness made this technique possible to implement in the industry [57, 58]. However, there are limitations such as the homogeneous cellular distribution (since it requires a rapid gelation process to obtain the desired size and shape) and some medical applications’ inhibition from having too much time to manufacture large 3D structures [10, 56]. It also remains difficult to apply due to its high sensitivity [54, 59].

56.3.4 Stereolithography 56.3.3 Laser-Induced Forward Transfer This method is increasingly being used in TE applications [10, 38]. The laser-induced forward transfer is a direct-write laser technique used to print biological materials, such as

Stereolithography (SLA) is one of the most popular additive manufacturing processes, and it is highly accurate. It is used for the production/fabrication of complex constructions involving ultraviolet (UV) curable liquid photosensitive polymer [8]. A laser beam selectively cures the polymer. Within all the SFF

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Fig. 56.8 Illustrative representation of a stereolithography system: (a) laser, (b) digital mirror device, and (c) movable platform. (Original image from the author)

techniques, it is the technology with the highest resolution and precision, and it is easily used with cells, hydrogels, polymers, ceramics, and composites [60] (Fig. 56.8). A CAD file is used in this technique, while the object geometry to be projected can be complemented by mathematical models and equations [8, 61]. A STL file (map of coordinates) is generated using the original CAD file to create the 3D model. All data is then loaded to the equipment, constituted by a photopolymerized liquid bath [8]. In other words, SLA is a manufacturing process that relies on the spatially controlled solidification of a liquid photosensitive polymer by photopolymerization [17]. The pattern is produced layer-by-layer by photolithography, through a laser, or by a UV lamp acting as a digital light projector [17]. In the former case, an inclined laser beam is used to cure a material reservoir’s surface areas [37]. After producing the 3D model/ object, the excess polymer is drain and removed [8]. Surface finishing is improved by immersing the object in a chemical bath to remove some irregularities [60]. Using the second approach, it is possible to use an instant creation of a pixelated light pattern (mask) using an array of micromirrors, which can be manually and independently rotated to an on or off state [17]. The design is illuminated on a resin’s surface, where it is solidified to a defined depth. In both cases, after each layer photopolymerization, the support platform is removed from surface to be recoated with liquid resin [17]. Exposure time and intensity should be optimized for each material and intended properties to obtain good adhesion to the previous layer [10, 41]. The commercially available materials used are typically epoxy or acrylate resins which cannot be used in scaffolds

because of the lack of biocompatibility and biodegradability. This makes the section of photopolymerizable biomaterials limited to SLA techniques for TE applications [10]. Still, any polymer with suitable viscosity and curing capacity can be used to create an SLA construct [37, 62]. Researchers can also use it to generate hydrogel scaffolds with natural or synthetic polymers that swell and are less rigid than usual [37]. Due to the high water content and soft tissue mechanics, hydrogels’ popularity increased [37]. To fabricate 3D biological constructs with SLA, cells can be encapsulated in photopolymerizable hydrogels, and the gelation of the cellhydrogel construct can be re-inducted by laser or UV light [41]. Photopolymerization is an attractive method to crosslink hydrogel-forming polymers, resulting in mechanically solid and stable matrices suitable for cell encapsulation. In doing so, the viability of the incorporated cells was no longer influenced by photopolymerization [41]. The most used materials in SLA are epoxy resins, some elastomers, PEG-based hydrogels, poly(propylene fumarate) (PPF), and other fumarate-based scaffolds, which are used in bone tissue regeneration due to their mechanical properties [8, 63, 64]. Compared to other manufacturing techniques, it offers exceptionally high accuracy and greater versatility in the design freedom and increasing availability of biologically relevant photopolymers. It is a promising technique as it is an automated process due to the scale of application [62]. The main limitation of this technique is that automated manufacturing is only possible using only one type of resin (or cell suspension) at a time. The rehydration can compromise the geometry of the construction [10, 17, 37]. Microarchitecture can be controlled with high vertical resolution and size features [37]. This technology offers the commitment of future multifunctional gel constructs, modeled with different cells, which can be fabricated using SLA and used for a wide variety of biomedical applications [10].

56.4

Further Directions

AM for 3D constructs has been focused on developing implants that lack a crucial element for mimicking native live tissues: its ability to change according to its function acutely. That is why leading research groups have recently proposed the four-dimensional (4D) biofabrication as an enhanced TERM approach: developing stimuli-responsive biomaterials that can be printed and dynamic to intended stimulation [65, 66]. Still, several challenges arise, namely (i) bioinks must be optimized to achieve successful biofabrication, (ii) processes must be mechanically designed to obtain the robust shape-changing capability of the constructs [67], (iii) specific bioreactors for complex tissue function maturation need to be invented, and (iv) evaluation procedures should be defined to examine the functionality

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Tissue Engineering

response [13]. Therefore, the most promising approach is to optimize the cell-construct interactions, becoming feasible for exploring computer modeling usage to explore further reactions further. Developing “smart” biomaterials to allow the dynamic changes of the structure [68], upgrading of the printing processes into a defined architecture for targeting tissues, automating the stimulus, and standardizing the assessment procedures to evaluate the result are crucial for enhanced TE approaches [69].

56.5

Conclusions

While tremendous work has been done in the last decades, much more needs to be done to achieve a scalable tissue engineering market. Improving from 2D to 3D and 4D, AM has demonstrated the unique key features that can be achieved. Likewise, the fantastic efforts developed in optimizing bioinks and processing conditions can assure us that the future of AM for TE is promising. Acknowledgments The author would like to thank Rui Silva for the illustrations. This research was supported by the European Regional Development Fund (FEDER) through COMPETE2020 under the PT2020 program (POCI01-0145-FEDER-023423).

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Pedro Morouço, Ph.D., is currently the dean of ESECS – Polytechnic of Leiria. Researcher at the Center for Innovative Care and Health Technology, his research focuses on bridging the gap between the lab and in vivo applications. In recent years, he has been invited to collaborate on several national and international projects and cooperate with several institutions (e.g., Università Cattolica del Sacro Cuore and Universidad de Vigo). He has authored and co-authored several scientific works, served as an editorial member in various journals, and been an invited speaker at multiple conferences.

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Olaf Diegel, Juan Schutte, and Simon Chan

Contents 57.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 953

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Fine and Decorative Arts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 954

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Art Conservation and Restoration . . . . . . . . . . . . . . . . . . . . . . 955

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Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 956

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Fashion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 956

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Jewelry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 956

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Film . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 958

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Tabletop Gaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 958

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Music . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 959

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Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 959

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 959

Abstract

3D printing provides an exceptional tool for the fabrication of many complex geometries, which allows unparalleled freedom to the creative industries. This chapter provides an overview of various innovative implementations of additive manufacturing technologies in the context of arts and culture. Discussions relating to how the technology has affected traditional artistic ventures (fine and decorative), facilitated growth in industries (architecture and film), helped preserve and restore historically and culturally significant works, and the implementation in user centric mediums (fashion, jewelry, tabletop gaming, and music) are explored with references to applied techniques, technologies, and industry adoptions provided.

O. Diegel (*) · J. Schutte · S. Chan University of Auckland, Creative Design and Additive Manufacturing Lab, Auckland, New Zealand e-mail: [email protected]; [email protected]; [email protected]

Keywords

Art · Culture · Wearables · Bespoke · Fashion · Design · Mathematics · Sculpture · Architecture · Archeology

57.1

Introduction

Over the past three decades, additive manufacturing (AM) has seen an ever-increasing presence in the arts. It has allowed much of what was, traditionally, just digital art to take on a whole new dimension by allowing it to transition into the physical domain. Indeed, there are now entire organizations, conferences, and exhibitions dedicated to 3D printed art and many artists who now use it as their main communication medium. One such organization is Ars Mathematica [1], an international nonprofit organization, founded in 1992, by Christian Lavigne and Alexandre Vitkine. It promotes the encounter of art, science and technology, with a particular focus on research related to digital objects in the electronic arts and the development of 3D and digital sculpture. Artists have always been great at exploring and pushing the limits of what new technologies can do. Southwestern University Professor of Art Mary Hale Visser states that “I wanted the topic to focus on the impact of 3D technology on the human mind as it endeavours to meet future challenges in the arts and sciences. Most of the publicity surrounding the invention of 3D printing has been focused on the rather mundane objects like small replicas of toys that anyone can now make with the aid of a personal 3D printer. What has not been discussed is how this technology will change the way in which human beings think creatively and its impact on various fields of knowledge.” [2]. It is this exploration of how this technology influences the way we think, express ourselves, and live that many artists and designers around the world are focused on. When looking at additive manufacturing from an arts and culture perspective, there are many separate areas that one

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can examine. But, of course, many of these areas are closely related to each other and crossover from one to the other.

57.2

Fine and Decorative Arts

Fine art is art developed primarily for aesthetics and beauty, as well as being thought-provoking, distinguishing it from decorative art or applied art, which also has to serve some

Fig. 57.1 Example of 3D printed mathematically generated model. (Image courtesy of CDAM Lab) Fig. 57.2 Printed aluminum dinosaurs by artist Gregor Kregar. (Image courtesy of CDAM Lab)

practical function, such as pottery or metalwork [3]. This definition is, of course, blurred, and when one looks at art across the ages, it becomes even more so. Additive manufacturing has even further blurred the distinction between fine and applied art, as it has allowed new levels of aesthetics, beauty, and thought process to be added to even the most common of objects. It has also helped to blur the lines between sciences and art, as we have seen countless artists, such as Bathsheba Grossman [4], Dizingof [5], and many others, use mathematics and science to drive, or even generate, their art (Fig. 57.1). Other artists use the complexity afforded by additive manufacturing to both prototype and manufacture their art. The advent of metal printers has also allowed artists who may traditionally be restricted by the constraints of the casting processes to explore new ways of using metal AM to create novel artworks. Witness the work of Gregor Kregar [6] who printed a range of inflatable balloon dinosaurs in aluminum as a way of exploring the potential of the technologies. The printed animals are, in fact, hollow, but to better contrast the idea of them being lightweight inflatable balloons, the unmelted powder of the metal AM process was left inside the sculpture to make them extra-heavy (Fig. 57.2). Although color 3D printers have been available since the mid-1990s with the plaster-based color 3D printers from Z-corp [7], the advent of more advanced full-color 3D printers by Stratasys [8] and Mimaki [9] that can handle not only billions of colors but also transparent materials has also opened new avenues in the arts. These color printers offer Pantone color matching, and the print quality is so detailed that it can become hard to distinguish the printed article from reality (Fig. 57.3).

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Indeed, the print quality of a 3D printed face can be good enough to fool the facial recognition systems on some mobile phones. This high-quality color 3D printing has allowed for a new range of 3D printed digital art that includes such luminaries as Neri Oxman [10], Christian Lavigne [11], and Kim

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Thoman [12]. The ability to embed full-color printing into clear materials opens up new doors to creativity (Fig. 57.4). 3D printing not only provides artists with a tool for realizing otherwise impossible to manufacture work but also a novel avenue for artists to commercialize their intellectual property. The flexibility of the artworks digital format allows the artist to utilize bureaus such as Shapeways [13] or iMaterialise [14] to better enable product distribution internationally. 3D printing is by no means an inexpensive manufacturing technique; however, the ability to easily scale artwork to be economically viable or accessible to an audience has significant potential in supporting art/artists.

57.3

Fig. 57.3 3D printed face that can fool facial recognition. (Image courtesy of CDAM Lab) Fig. 57.4 Morphogenesis: an exploration of the potential of fullcolor and clear 3D printing. (Image courtesy of CDAM Lab)

Art Conservation and Restoration

3D printing, combined with 3D scanning, has played a strong role in art conservation and restoration [15]. Around the world, works of art have been digitally scanned in order to preserve them in digital form in case they are destroyed or further deteriorate because of climatic conditions or erosion. An example of this is the “Buddha Vairochana with the Realms of Existence” statue for which highly details 3D scanned models are available from the Smithsonian museum. The limestone sculpture started its life in China during the Northern Qi dynasty (550–577), most likely carved by a team of craftsmen. Now that it has been digitally preserved, countless highly details 3D printed have been created to help disseminate this Asian work of art in physical from around the world (Fig. 57.5).

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Fig. 57.6 3D printed model of Lund’s Domkyrkan cathedral in southern Sweden. (Image courtesy of CDAM Lab)

produce works that are as much art as they are architecture (Fig. 57.6).

Fig. 57.5 Printed version of “Buddha Vairochana with the Realms of Existence” sculpture from 3D scanned digital file. (Image courtesy of CDAM Lab)

Before 3D printing and scanning, the only way to capture the rich content of a sculpture would have been through photographs or rubbings, impressions in black ink on white paper made directly on the sculpture’s surface which, of course, risk further deteriorating the sculpture. Today, anyone with a computer can zoom in on all its intricate details and carvings. The digital file of the Buddha now exists as a 3D model, enabling scholars to study the work as never before and providing worldwide access to this masterpiece of Buddhist sculpture.

57.4

Architecture

3D printing’s ability to recreate objects from digital information has been highlighted as having potential for the restoration of significant cultural landmarks. One example relates to the restoration of Paris’s Notre Dame Cathedral in which 3D data and the potential to reprocessing and print the original/ rubble material are being investigated [16]. Additionally, architects have been extensive users of AM technologies as it has allowed them to produce highly accurate models of their designs to show to customers. Over the past three decades, the dividing line between architecture and art has become increasingly blurred and many architecture students

57.5

Fashion

One of the more interactive artforms that 3D printing has had a significant impact on is that of wearable arts or fashion design. This can be seen in the large adaption of the technology in hobbies such as cosplay or live action role-play where enthusiasts have utilized AM to create various complex armors or even chain-mail substitutes (Fig. 57.7). Nervous Systems is a company which has seized this opportunity for artistic exploration. In their Kinematic Dress product [17], they have used a combination of 3D scanning, advanced modeling, and 3D printing to create a dress that not only fits perfectly to the scanned wearer/model but, through modification to the linkages within the item, can be made to move in an artistically defined manner (Fig. 57.8). 3D printing has also unlocked new avenues for fashion design in its ability to transform previously mundane or aesthetically unpleasant surfaces into desirable and personal items. This concept has seen a dramatic uptake in the development of custom prosthetic fairings or even the 3D printing of entire prosthetics (Fig. 57.9).

57.6

Jewelry

Many individuals have a very personal attachment to jewelry, and this has led to an international demand for custom jewelry. 3D printing’s capabilities to create highly complex geometries has presented a highly attractive avenue for jewelers. As such, many 3D printing companies such as 3D

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Fig. 57.7 3D printed chainmail fabrics for fashion design. (Image courtesy of CDAM Lab)

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Fig. 57.8 Kinematics dress by Nervous System. (Photo by Steve Marsel Studio)

Systems [18] and Formlabs [19] have created materials specifically designed to complement this market, with examples including photocurable wax resins well suited for the lost-wax casting process typical in jewelry manufacture (Fig. 57.10). 3D printing has also been applied to the direct manufacture of jewelry with many precious metals having now been

successfully 3D printed. Already companies, such as Cooksongold [20], have begun to utilize specialized machines such as the EOS M080 and EOS M100 to provide this capability as a service to jewelers. While these items still require post-processing similar to the casting practices, it further unlocks the jeweler’s ability to create highly complex and bespoke artistic pieces (Fig. 57.11).

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57.7

Fig. 57.9 3D printed prosthetics (one painted post print). (Image courtesy of CDAM Lab)

The ability to rapidly create complex and interactive componentry has also seen a significant uptake within the film and special effects industry. This is not only limited to its ability to create costuming but has major potential to optimize postproduction workflows. Companies such as Weta Workshop [21] have leveraged the power of 3D printing as a means to reduce the computational complexity required in generating interactive special effects. An example of which is the enormous processing required to emulate the physicsbased effects such as gravity, dynamic lighting, or water/ wind flow interactions with irregular surfaces [22, 23]. Through using a 3D printed part, the effects can be simulated practically thereby reducing potential post-processing requirements.

57.8

Fig. 57.10 Castable resin 3D printed by the company Complete3D on 3D System’s Figure4 3D printer. (Image courtesy of CDAM Lab)

Fig. 57.11 Examples of complex 3D printed jewelry by ODD. (Image courtesy of CDAM Lab)

Film

Tabletop Gaming

An interesting avenue for which 3D printing has empowered designers in new ways is the development of bespoke gaming products. This has led to a widespread adoption of the technology within communities such as players of the popular Warhammer Tabletop strategy games, Dungons and Dragons, Fallout, and many other such role-playing games [24]. 3D printing and accessibility of software such as Blender [25] or Autodesk’s Meshmixer [26] have enabled passionate individuals to innovate and develop novel personalized items, circumventing the limitations of proprietary models (Fig. 57.12).

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Fig. 57.13 Scarab ST guitar 3D printed through full-color material jetting. (Image courtesy of CDAM Lab)

Fig. 57.12 Examples of customized structures and characters for tabletop gaming. (Image courtesy of CDAM Lab)

57.9

Music

The music industry has done a lot of work in exploring how AM could be used to bring new instruments into being. From whistles and kazoos, to recorders and transverse flutes, almost all areas of music have been affected. AM has been used to recreate historical instruments as well as to create entirely novel instruments with unique sounds. However, from a commercial point of view, the area that has seen the most active use of AM has been in electric guitars. There have been a number of electric guitars produced using AM technologies. The earliest of these appears to be a guitar, produced with an SLA system, designed by Owain Pedgley and Eddie Norman at Loughborough University, and currently owned by Dr. Ian Campbell, in 2005 [27]. There has also been a number of guitars produced by Tim Thellin, of RedEye/Stratasys using FDM technologies [28]. FDM has also been used by Derek Manson of One.61 in New Zealand to produce an electric guitar [29]. There has also been an experimental music guitar/bass, created by Ziv Bar Ilan, called the Zoybar [30], which is commercially available, and uses SLS as its manufacturing technology. The Zoybar is available through Shapeways. Though a guitar, with a high level of user configuration options, it is not a fully conventional one as it is a fretless instrument so requires some specialized playing skills.

The first commercially available electric guitars and basses, becoming available in 2011, are those produced by ODD guitars [31], manufactured with SLS in New Zealand. These feature a nylon body, with an inner wooden core joining the bridge to the neck, and allow customization of hardware and shape by the customer. ODD Guitars has also produced an electric guitar with a 3D printed aluminum body (Fig. 57.13). It is important to note that, on all the commercially available 3D printed guitars to date, only the bodies have been 3D printed, the necks were made out of wood, and the rest of the hardware was manufactured using conventional manufacturing technologies.

57.10 Conclusions This chapter has provided an overview and exploration into the many use cases for AM within the creative industries. Not only is this technique’s uptake and effects continually growing within established fields it is also unlocking novel avenues for artistic and cultural exploration. This has allowed for both the realization of digital concepts within the physical domain as well as resulting in the creation of novel industries and services for artists. Many of these new fields are still in their artistic infancy with significant potential for further growth, thereby providing a highly desirable opportunity for the future growth within creative industries.

References 1. Mathematica, A., Lavigne, C., Vitkine, A.: https://www. arsmathematica.org/. Retrieved April 2021 2. Visser, M.: What things may come. Southwestern University Symposium/Sculpture Exhibit. https://www.southwestern.edu/live/files/ 4020-what-things-may-come-michelle-matisons (2015)

960 3. Reynolds, A.: Fine Art vs Decorative Art, REN Creative Works. https://adrianreynolds.ie/fine-art-or-decorative-art/ (2020) 4. Grossmn, B.: https://bathsheba.com/ (2021) 5. Dizingof.: https://www.3dizingof.com/ (2021) 6. Kregar, G.: http://gregorkregar.com/ (2020) 7. 3D Systems: Z corporation unveils 3D color printer with breakthrough affordability, ease of use, and office compatibility. https:// www.3dsystems.com/press-releases/z-corporation-unveils-3dcolor-printer-breakthrough-affordability-ease-use-and-office (2007) 8. Stratasys: Make it more realistic and accurate with PolyJet. https:// www.stratasys.com/polyjet-technology#imageCarousel (2021) 9. MIMAKI ENGINEERING CO., LTD.: Beautiful color expression. https://mimaki.com/special/3d_print/color.html (2017) 10. Hussey, M.: Chaise longue by Neri Oxman uses 3D printing to create a multi-coloured cocoon. https://www.dezeen.com/2014/04/ 03/3d-printed-chaise-longue-by-neri-oxman-forms-a-multicoloured-cocoon/ (2014) 11. TERRORDURE / RUBBISHEARTH.: http://christianlavigne.free. fr/videos/terrordure-rubbishearth.html (2016) 12. Thoman, K.: http://www.kimthoman.com/3d-printed-sculptures (2021) 13. Shapeways: 3D printing on demand. https://www.shapeways.com/ (2021) 14. Materialise: Your 3D printing service. https://i.materialise.com/en (2021) 15. Formlabs: How 3D printing brings antiquities back to life. https:// formlabs.com/asia/blog/how-3d-printing-brings-antiquities-backto-life/ (2018) 16. Reichental, A.: 3D printing Notre Dame’s restoration: thinking outside the 14th century box. https://www.forbes.com/sites/startupna tioncentral/2019/07/22/3d-printing-notre-dames-restoration-thinkingoutside-the-14th-century-box/?sh¼391bf83c6457 (2019) 17. Nervous Systems: Kinematics dress. https://n-e-r-v-o-u-s.com/ projects/sets/kinematics-dress/ 18. 3D Systems: 3D printing for jewelry manufacturing. https://www. 3dsystems.com/jewelry (2021) 19. Formlabs: High-detail 3D printing materials for designing and manufacturing jewelry. https://formlabs.com/asia/materials/jewelry/ (2021) 20. Cookson Precious Metals Ltd: World leading experts in precious metal additive manufacturing. https://www.cooksongold-am.com/ (2021) 21. Weta Workshop Limited: Build. https://www.wetaworkshop.com/ build/ 22. Zortrax: The use of 3D printing in films and movie production in hollywood. https://zortrax.com/blog/3d-printing-movie-hollywood/ (2017) 23. Stevenson, M.: 3D printing & movies – 3D printing behind the scenes. https://all3dp.com/2/3d-printing-movies-3d-printingbehind-the-scenes/ (2019) 24. Goldschmidt, B.: 2021 best sites for 3D printed Warhammer Stuff. https://all3dp.com/2/3d-printed-warhammer-stuff-best-sources/ (2021) 25. Blender: Free Software never looked this awesome. https://www. blender.org/features/ (2021) 26. Autodesk: Autodesk Meshmixer free software for making awesome stuff. https://www.meshmixer.com/ (2021) 27. Kantaros, A., Diegel, O.: 3D printing technology in musical instrument research: reviewing the potential. Rapid Prototyp. J. (2017) 28. Stevenson, K.: Print your Guitar. https://www.fabbaloo.com/blog/ 2009/12/27/print-your-guitar-html (2009) 29. McCue, T.J.: 3D Printed Guitar takes instrument design to new level. https://www.forbes.com/sites/tjmccue/2012/04/02/3d-printed-

O. Diegel et al. guitar-takes-instrument-design-to-new-level/?sh¼74922b9e4568 (2012) 30. Zoybar: About Zoybar. https://zoybar.net/about-zoybar/ (2020) 31. Diegel, O.: Guitars. http://www.oddguitars.com/scarabst.html (2011)

Olaf Diegel Professor of Additive Manufacturing, University of Auckland, New Zealand. Olaf is an educator and a practitioner of additive manufacturing (AM) and product development with an excellent track record of developing innovative solutions to engineering problems. In his role as professor of additive manufacturing, at the University of Auckland, in New Zealand, he is involved in all aspects of AM and is one of the principal authors of the annual Wohlers Report, considered by many to be the bible of AM. His current main area of research expertise is in design for AM. In his consulting practice, he develops a wide range of products for companies around the world. Over the past three decades, he has developed over 100 commercially available new products including innovative new theater lighting products, security and marine products, and several home health monitoring products, and, for this work, has received numerous product development awards. In 2012, Olaf started manufacturing a range of 3D printed guitars that has developed into a successful little side business.

Dr. Juan Schutte Research Fellow, Creative Design and Additive Manufacturing Lab. Dr. Juan Schutte is a passionate problem solver, driven by engineering projects that allow him to apply his design, mechatronics, and manufacturing expertise to make a difference. As a designer, he is a strong advocate for leveraging simplicity and modularity, an ethos inspired by his practical “not afraid to get his hands dirty” approach, which has led to the research and development of multiple efficient systems and products. As a researcher, he completed a PhD which developed a novel form of biomaterial-based additive manufacturing and is interested in research relating to tissue engineering, exoskeleton devices, and prosthetics. He is currently a Research Fellow at the University of Auckland’s Creative Design and Additive Manufacturing Lab, where he applies his creativity to pushing the boundaries of cutting-edge technology and consults with both industry and academia on the opportunities of 3D printing.

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Simon Chan Research Fellow, Creative Design and Additive Manufacturing Lab. Simon Chan is a mechanical engineer, holding a Master of Engineering degree from the University of Auckland. He has over 25 years of practical experience in New Zealand, specializing in product design, tool design, and die and mold manufacturing. Currently, he is working towards a doctoral degree in metal additive manufacturing (3D printing), focusing on injection mold applications.

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Claude Barlier, Christophe Abel, and Jean-Loup Rennesson

Contents 58.1

Analysis of the Custom Packaging Market . . . . . . . . . . . 963

58.2

State of the Art of Additive Manufacturing Applications in Packaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 964

58.3

The Additive Manufacturing Process ® Stratoconception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Principle of the Stratoconception ® Process . . . . . . . . . . . . . . Usable Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Post-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Main Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Benefits and Limitation of the Processes . . . . . . . . . . . . . . . . .

58.3.1 58.3.2 58.3.3 58.3.4 58.3.5 58.4

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58.4.1 58.4.2

Application of Additive Manufacturing to the Rapid Production of Packaging: The Pack&Strat ® Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 967 Context and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 967 Implementation of the Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 969

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Profitability Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 972

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Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 974

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Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 978

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Abstract

Among the many applications of additive manufacturing, the packaging domain is important to mention, in particular the production of packaging guaranteeing the integrity of prototypes or high added-value parts during their transport. This chapter includes an analysis of the custom packaging market and a state of the art of additive manufacturing applications in the packaging industry. Then it describes an innovative process particularly suited to this field of application, namely the Pack&Strat ® C. Barlier (*) · C. Abel CIRTES, Saint-Dié-des-Vosges, France e-mail: [email protected]; [email protected] J.-L. Rennesson INORI, Saint-Dié-des-Vosges, France e-mail: [email protected]

process, derived from the Stratoconception ® additive manufacturing process or sheet lamination of discontinuous plates (ISO 17296-2 standard). Keywords

Stratoconception ® · Pack&Strat ® · Rapid manufacturing · Rapid product development · 3D packaging · Protective packaging

58.1

Analysis of the Custom Packaging Market

Packaging is a booming market today. This global growth is driven by two key factors: • Increasing purchasing power in emerging countries, which stimulates the consumption of products with high added value, and generates increased demand for the consumption of packaging. • The rise of e-commerce, in a context of rapid development of Internet access. Globally, the turnover of this sector represented 2131 billion dollars in 2018, i.e., +14.3% vs. 2017 (source: Ecommerce Foundation). Packaging market trends are inducing major transformations in the packaging offer. • Custom Packaging Development of tailor-made solutions to meet specific customer needs through packaging personalization and customization tools. • Smart Packaging Modernization of industrial packaging manufacturing tools and digitization of processes through the development and integration of cutting-edge technologies: these

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5_58

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aim in particular to improve productivity, personalize the offer, and bring new promises of value. • Green Packaging Increasing integration of bio-sourced, compostable, and recyclable materials for more ecological packaging and transformation of manufacturing methods to meet environmental challenges (use of renewable energies, material recycling policy, etc.). Source: Xerfi study, The new challenges of the Packaging Sector, 2020 In this new context, additive manufacturing should advantageously be able to provide breakthrough solutions. To respond to these trends, some major packaging manufacturers, particularly those involved in e-commerce, are offering the design of adapted packaging, with optimized wedging functionalities. We can note that the study costs necessary to design such personalized packaging are of little importance because the proposed solutions only concern packaging in large series. In addition, bio-sourced materials are molded to replace thermoformed plastic packaging in large series too. One of the challenges of packaging in the context of e-commerce is to avoid the packaging and transport of empty spaces, in order to reduce carbon footprint. The difficulty is to adapt the dimensions of the secondary packaging used to co-pack several primary packaging of different dimensions. To do this, some online sales specialists use machines that scan the dimensions of the products to be shipped to make a corrugated cardboard box with the optimal dimensions. Several players of the foam packaging market are positioned in the custom packaging segment, in small series and in market sectors associated with high added-value products, such as automotive, medical, defense, aeronautics, and luxury. They offer wide ranges of protective foam packaging solutions with different types of foam, including cross-linked and non-cross-linked polyethylene and polyurethane foams, either cut or micro-milled, presented as custom foam case inserts, cushion pallets, end caps, etc., designed with standard CAD software programs. For such applications, the study costs necessary to design personalized packaging are more relevant when the proposed solutions concern packaging in small series or even more for unit packaging. In addition, the foam packaging market is characterized by solutions meeting the needs of ergonomics, practicality, and cost reduction, such as the Instapak ® Foam-in-Bag Packaging System, developed by the Sealed Air ® company, which allows products to be packaged using injected foam cushions. The Instapak ® process is based on the mixture of polymeric diphenylmethane diisocyanates (PMDI) and polyols for the production of an expanding polyurethane foam which makes it possible to create cushions adapted to the dimensions and shapes of the product to be packed. However, its use is less

C. Barlier et al.

compliant with the green packaging trend than packaging processes using corrugated cardboard or even non-crosslinked polyethylene foam.

58.2

State of the Art of Additive Manufacturing Applications in Packaging

The evolution of additive manufacturing processes now makes it possible to provide solutions in the packaging area. A first approach concerns packaging, seen from a marketing perspective, for which the additive manufacturing of products with complex shapes makes it easier to produce. In July 2015, experts from management consultancy McKinsey view the three-dimensional manufacturing process as a pioneering technology of the future in the cosmetics sector. The packaging producer Multi Packaging Solutions considers the additive manufacturing process – where any object can be produced by adding individual layers of material on top of each other – the technology of the future for the cosmetics industry. Individual packaging designs can be manufactured specifically in accordance with customer wishes and various design prototypes can be produced. However, this approach has so far only worked for one-off pieces like glass bottles or decorative elements for packaging closures; mass production is for the time being too time consuming and costly (Source: interpack Messe Düsseldorf GmbH). A second approach consists in using 3D printing to provide molded fiber manufacturers a competitive advantage by accelerating tooling fabrication. The new packaging market trend aiming to replace thermoformed plastic packaging by molded fiber materials makes this additive manufacturing application relevant for packaging in large series. But this is an indirect application in the packaging market (tooling) and not a direct application of packaging manufacturing. The third and last approach focuses on the realization by additive manufacturing of the internal parts of packaging to match the shape of prototypes or high value-added parts in order to guarantee their integrity during their storage, handling, or transport. Some truss lattice structures made of elastomeric polyurethane, built by photopolymerization of a resin (DLP), have been used to create protective shells requiring shock resistance and/or vibration isolation. The mechanical advantages of lattice structures are already being used to optimize 3D printed parts themselves, or as an interior support for the main part structure, due to their high strength to density ratio [1, 2]. It therefore makes sense to also use such lattice structures as protective shells, but the corresponding costs are very high and not suitable for general packaging applications. As most protective packaging materials are available as sheets, such as corrugated cardboard, foams, etc., the most adapted additive manufacturing process for packaging appli-

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Applications for Packaging

cations should be found in the standardized AM process family “sheet lamination from discontinuous plates,” namely STRATO (STRatoconception Additive TechnOlogy) process [3–5]. This chapter describes a process particularly suited to this latter approach, namely the Pack&Strat ® process, derived from the Additive Manufacturing Stratoconception ® process or sheet lamination of discontinuous plates. We first situate Stratoconception ® in relation to the seven families of standardized additive manufacturing processes. Then, a detailed description of the Pack&Strat ® process is given, as well as real examples of application and some tracks of profitability analysis.

58.3

The Additive Manufacturing Process ® Stratoconception

Additive manufacturing processes can be broken down into seven families [9] defined by the NF EN ISO 17296-2 standard [6] listed below. At a more or less initial stage, the materials used in AM are either in the form of liquids: • Photopolymerization of a resin under the action of a laser: SLA/DLP processes • Material jetting: MJ/PolyJet/NPJ/DOD processes or powders: • Binder jetting on a powder-type substrate: BJ/CJP processes • Powder bed fusion using a heat source: SLS/MJF/SLM/ DMLS/EBM processes • Directed energy deposition of material (powder or wire) using an energy flow (laser, electron beam, arc or plasma): DED/LMD-w/EBAM processes or solids: • Fused deposition modeling through a heating nozzle: FDM process • Sheet lamination of continuous roll: LOM process • Sheet lamination from discontinuous plates: STRATO (STRatoconception Additive TechnOlogy) process [3] Most of such additive manufacturing processes are not suited for packaging applications, mainly because of practical or economic reasons.

58.3.1 Principle of the Stratoconception ® Process A pioneering patented additive manufacturing process by layer lamination from plate materials, the STRatoconception Additive TechnOlogy (STRATO), was

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initiated and then patented by Claude BARLIER [7] in the mid-1980s, it was marketed in 1991. This additive manufacturing process using solid layers consists in breaking down the CAD model of the part by calculation into a set of elementary 3D layers, called “strata,” into which reinforcements and inserts are introduced. The elementary layers are nested next to each other (front/back) and made of a plate material from cutting by rapid micro-milling, by laser, by water jet or by cutter. Each thick 3D layer represents a slice which is very close to the initial CAD model – unlike other processes reconstructing the part from simple 2D layers – they are directly produced in 3 dimensions by cutting in 5 axes which makes it possible to obtain ruled surfaces or even better by fast 2.5-axis micro-milling. In the latter case, the profile is representative of the initial 3D CAD, in dimension, geometry, and surface roughness. To reconstruct the final object, the strata are then positioned using inserts or nested or even assembled using bridges to make parts with thin walls. The final assembly can be obtained by mechanical assembly, by structural adhesive bonding, by brazing, by diffusion welding, or by hot isostatic pressing (HIP) depending on the material and the targeted end applications. It is possible, in some cases, to finish the strata after assembly, by stacking. The means of positioning and the type of assembly are taken into account as soon as the object is decomposed and can participate in the mechanical strength of the parts. It is possible to slice the part according to several different planes, the surfaces of the layers can be skew, and each layer can be broken down into several parts. Like other additive manufacturing families, Stratoconcept ® III software implements the process from an STL file. However, the recent developments of TopSolid’Strato ® and StratoTop® software programs allow design for additive manufacturing by Stratoconception ® directly in native format from TopSolid’CAD/CAM (Fig. 58.1).

58.3.2 Usable Materials The usable plate materials differ depending on the application. The thickness of the layers is chosen by the user; it depends on the possible supplies of materials and the size of the parts to be produced. The varieties and shades of usable materials are very important. Most commonly used materials are cardboard, wood and wood compounds, a very wide range of polymers (ABS, PVC, PP PET, PMMA, polystyrene, etc., PU resins and foams or epoxy resins of various densities), and metals (aluminum of the 5000, 6000, or 7000 family; cupro-alloy, titanium, and inconel; and alloy steels such as 40CMD8, Z38CDV5, and XC48). In general, the Stratoconception ® process allows the use of any material that can be cut and assembled and that can be supplied in the form of plates (generally 3000
2000 mm)

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Fig. 58.1 Schematic diagram of ® Stratoconception . (Source: CIRTES)

Stratoconcept® software Placing 3D strata with inserts

STL/CAD file

Slicing - Select axis - Select pitch - Select inserts

Laying out - Select sheet size - Select material

Machine control

Z

Manufacturing 3D strata Rapid micromilling, hotwire, laser, cutter, ... Y

Assembling

Material sheet

X

Machining and turning-over station

Final prototype

Software, trademarks and patents – Claude Barlier – CIRTES – France – Stratoconception⁄, Straconcept⁄, Strat⁄, Pack&Strat⁄.

with a thickness of a few millimeters to a maximum of 100 mm, depending on the size of the part.

58.3.3 Post-processing The Stratoconception ® process does not generally require any particular post-processing, except for the production of thin-walled parts, in which case the process uses external supports (bridges) that must then be eliminated. In the case of steels, a heat treatment of quenching and tempering may be carried out. As with other processes, priming and painting the part may also be necessary depending on the end use.

58.3.4 Main Uses Stratoconception® can be used for the production of aesthetic, concept, or geometric prototypes, for direct parts, as well as for the production of models and tools for shaping metals and polymers. These rapid tools can be permanent in resin, in aluminum or steel and or ephemeral in wood, or in polystyrene. The process is also very suitable for the direct production of functional parts. It easily enables the integration of

functionalities between layers, such as nozzles, channels, sensors, etc., for the creation of smart parts and tools. The relevant fields are healthcare, architecture, design, art, automotive, aeronautics, naval industries, rail, and packaging. The tools relate to the processes of plastics (contact molding, thermoforming, blow molding, injection, etc.) and metal shaping (foundry, etc.), or the shaping of other materials such as glass or concrete. In particular, a large number of current applications relate to the production of large-size tooling intended for forming composites for aeronautics, naval, construction, etc (Figs. 58.2 and 58.3).

58.3.5 Benefits and Limitation of the Processes Stratoconception ® is renowned for being robust, flexible, and efficient for many industrial applications. It also makes it possible to use many materials. The process is very fast because only the contours are to be created by cutting the strata and thus it only requires very low power sources of energy compared to CNC machining in the mass. This process is marketed as fully integrated turnkey stations, or through its integration on 3- to 5-axis machine tools of an existing machine park. It is open to the use of all qualified materials available in plate so that a large field of

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967 Table 58.1 Main machine characteristics Cutting system Micro-milling Hot wire cutting Oscillating knife

Dimensions (No limitation* in Z) 600*420 – 6520*2200 mm 1200*1200 – 5000*2500 mm 800*1300 – 1800*2500 mm

Usable materials Any plate material Polystyrene Foams – corrugated cardboard

*Not Limited: the height of the part is not limited on Z axis of the machine (assembly in subparts outside the machine)

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Fig. 58.2 RAFALE 1/15th scale mock-up – Dassault Aviation supplier. (Source: CIRTES)

Fig. 58.4 Machine example – Giga STM G 3020 rapid prototyping and tooling station. (Source: CIRTES)

distributed as semiautomatic or fully automatic units (Table 58.1, Figs. 58.4 and 58.5).

58.4

Fig. 58.3 Rapid tooling in resin for foundry (2000
1000
400 mm). (Source: CIRTES)

activities can be explored. Moreover, the fact that layers may be assembled outside of the machine allows the realization of voluminous pieces, even very large or monumental pieces (i.e., of several meters), with very good details. Miscellaneous stations are available with different cutting systems and formats to fulfill any customer’s needs and are

Application of Additive Manufacturing to the Rapid Production of Packaging: The Pack&Strat ® Process

The patented application [8], Pack & Strat ®, derived from Stratoconception ®, is dedicated to 3D digital rapid packaging [4, 5]. It uses the rapid micro-milling process for wood, PE and PU foams, and PS; corrugated cardboard and foams are advantageously cut by oscillating knife.

58.4.1 Context and Challenges The packaging industry is undergoing rapid change: search for competitiveness, innovation, creativity, quality and reliability, traceability, speed, etc., in order to meet the requirements of the market, or more precisely of the markets,

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Fig. 58.5 Machine example – Strat’Auto 2116 rapid prototyping and tooling automatic station. (Source: CIRTES)

because it is necessary to distinguish the different aspects that the packaging can take according to the relevant product, the safety which must be brought to it, its transport mode, its shape and dimensions, whether it is shipped in bulk or individually, etc. The trend in the packaging market is to transform the offer by proposing: • Custom-made and personalization solutions (custom packaging) • Integrated digital solutions facilitating the package tracking (smart packaging) • Environmentally friendly solutions using recyclable, recycled, and bio-based materials (green packaging) The digital product design and development sector and its applications to additive manufacturing therefore represent a significant innovation potential for packaging. As close as possible to the product, especially in the case of luxury or high added-value products, the packaging must enhance the image of the product while protecting it. In other cases, it is necessary to focus on the service with new functionalities, the personalization in particular for unit products, the quick production of the packaging, and its “just in time” availability, meaning that the packaging arrives as soon as the product is manufactured, without having to be stored in large numbers.

®

Fig. 58.6 3D packaging produced by the Pack&Strat process (outer box þ inner packaging). (Source: CIRTES)

Pack&Strat®, process and software developed by CIRTES, therefore particularly fulfill these requirements for the packaging of individual parts or in small series (Fig. 58.6).

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58.4.2 Implementation of the Sector

must be packed in the same box, the software helps the operator to define the best positioning within the volume of the packaging, possibly standard boxes whose dimensions are available from a database. A set of standard tools, such as alignment, centering, rotate, or translate functions, is available to the operator. However, positioning using the mouse is also possible via a graphical interface (Fig. 58.8). If there is no standard box with suitable dimensions, the software helps find the dimensions of a specific box (Fig. 58.9). The cutting precision is also an important parameter on which, unlike many other processes, it is possible to strongly intervene. In most cases, each slice of the inner packaging is very quickly produced by 2-axis or 2D digital cutting machines such as laser, cutter, hot wire, or even waterjet cutting systems. However, for high-end packaging when a perfect 3D matching with the shapes of the part is requested, it is recommended to use 2 ½-axis ultrahigh-speed micromilling (UHSM) machines. As shown in Fig. 58.10, 2D cutting generates a step shape where the part lays on the angles. Each profile defined by this angle fits exactly the part and allows it to be very strongly maintained. Therefore, a specific attention must have been paid to the choice of the material to avoid abrasion of the part and crushing of the inner packaging itself: a wide range of materials can then be proposed to address these different problems (Fig. 58.11). Once the layout of the part and the dimensions of the box have been determined, different inner packaging configurations are proposed by the software (Fig. 58.12). The operator selects all or part of the various proposed features by modifying or not the default settings. Depending on several parameters such as shape complexity or weight, the ability to define the slicing direction combined with a choice between different materials and several unpacking directions improves the mechanical behavior and crushing resistance of the inner packaging as well as the integrity of the part (Fig. 58.12). The influence of the

The Modeling The starting point of the Pack&Strat ® process is a digital file of the part or object to be packed. The STL format, common to all AM processes, is also used here. Two possibilities occur: either the file exists because the part or object has been defined in CAD, or the file is not available. In the first case, the packaging is designed directly from the object file (Fig. 58.7). In the second case, where a scanning operation is mandatory, the most adapted 3D scanning solution shall be chosen according to the characteristics of the parts to be packed, in terms of dimensions and types of surfaces. There are now several 3D scanning solutions, portable or not, which fulfill the needs of the Pack&Strat process and are offered upstream of the packaging solution. The Packaging Design This is the main step of the process, from the 3D file of the part to be packed, or from a set of 3D files if several parts

Fig. 58.7 Digital definition of the part to be packed, either directly obtained from CAD or through the object scanning. (Source: CIRTES)

Yp

Xp Zp Zp Yp Xp

Ze Ze Xe

Ye

Xe

Ye

Positioning along the vertical axis

Fig. 58.8 Definition of the packaging volume and positioning of the part inside it. (Source: CIRTES)

Angular orientation

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Fig. 58.9 Box configurations. (Source: CIRTES)

Material

Box

4 flaps

X 300,000 300,000 1000,000

2D cutting

2 axes

Y 300,000 250,000 1500,000

1 flap

Z 300,000 300,000 1500,000

3D cutting

2 axes 1/2

Fig. 58.10 Cutting precision. (Source: CIRTES)

structure of materials has also been demonstrated by several studies [1, 2]. Hence, mixing materials may be useful: for example, honeycomb cardboard can be used for one inner area and foam for another area. The economic and ecological side of the process is reinforced not only by using recyclable raw materials, such as corrugated cardboard, but also by reducing the inner packaging to some areas of the part and the outer box to optimized dimensions. The production time as well as the quantity of material can thus be considerably reduced.

The Other Functions of the “Pack&Strat ®” Software In order to improve handling and insertion into the outer box, adjustments can be made to each of the previously defined inner packaging zones. The possibility of creating strapping

Cover

Case

OK

paths to hold the different layers, which constitute the inner packaging, also makes it possible to dispense with any outer box (Fig. 58.13).

Making the Packaging As soon as all data necessary for the realization of the packaging is validated, the software automatically generates the inner packaging layers, their optimized nesting next to each other in the chosen plate material and, if this is the case, the cutting and creasing of the cardboard used to make the outer box. The toolpaths are transmitted to the cutting machine (Fig. 58.14). As soon as the layout is cut out, all layers just need to be collected to proceed with the packaging (Fig. 58.15). The layers are then extracted from the layout to be directly positioned in the box and/or around the part to be packed to constitute the packaging (Fig. 58.16). Depending on the previously defined options, the set of packaging layers can be strapped together to be directly used or be set in an outer box (Fig. 58.17). Widely/Commonly Used Materials The Pack&Strat® process provides a variety of materials adapted to the needs of the packaging. The current trend is towards recyclable or even recycled materials, and the cost of packaging is also an important criterion. With the Pack&Strat® process being fast and not requiring special technical knowledge, a large percentage of the packaging cost price only relies on material cost. Thus, materials such as corrugated cardboard or honeycomb or some polyethylene foams are very widely used. However, more noble materials such as wood, cork, and high-end foams are also perfectly suitable and complete this non-exhaustive range of materials: the process accepts any plate material available on the market, as long as it can be cut.

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Fig. 58.11 Material selection. (Source: CIRTES)

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Box

Cardboard

X 300,000 300,000 1000,000

Y 300,000 250,000 1500,000

MDF

Z 300,000 300,000 1500,000

Oak

Birch

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Fig. 58.12 Choice of positioning of the inner packaging. The software adapts the layout of the inner packaging to the different shapes. In case of undercut, it suggests a typology as shown on the right. (Source: CIRTES)

Area 1 Empty area

Area 2

Simple object: one inner packaging area

Type 1 Simple object = one unpacking direction

Machines Compatible with the Process A wide range of machines is available for cutting packaging layers generated by Pack&Strat ®. Some of them are better suited for cutting materials than others. Expanded or extruded polystyrene, used less and less mainly for ecological reasons, will be more easily worked on hot wire cutting or fast micro-

Object with complex shapes: several inner packaging areas

Type 2 Object that clears on both sides of 1 plane

Type 3 Object with complex shapes

milling machines, while for corrugated cardboard, that will rather be on knife or laser cutting machines (Fig. 58.18). The development of suitable post-processors makes it possible to open the standard range of packaging stations to existing machine parks. This allows the process to be distributed to companies already equipped with cutting machines.

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Fig. 58.13 (a) Addition of a grip recess to facilitate the extraction from the box. (b) Addition of strapping paths and chamfers at the four corners. (Source: CIRTES)

Fig. 58.14 The software automatically manages the contours of the strata, their layout, and the cutting toolpaths. (Source: CIRTES)

Fig. 58.15 Cutting the layers. (Source: CIRTES)

58.5

Profitability Analysis

Packaging costs are often considered sparingly, depending on the added value of the part to be transported or stored of course.

With regard to the profitability analysis of a custom-made packaging process, qualitative aspects are taken into account such as the aesthetics of the inner packaging (product footprint), which is appreciated for luxury products, and the protection of the parts during their transport. But the quantitative aspects are the most studied, namely the manufacturing cost which includes the tooling costs in some cases, material, machining, and handling costs. As part of a cost-benefit analysis, all of these costs should be compared, not just the cushioning material cost. As an example, let us consider the packaging of aeronautical parts in parcels of 10 units, each part is protected by bubble wrap, placed in a kraft pouch, and then put in a box. About 60 parcels are shipped per week, i.e., 600 pieces. With a custom-made inner packaging in corrugated cardboard, it is

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Fig. 58.16 Setting up the packaging. (Source: CIRTES)

58 Fig. 58.17 Strapped inner packaging (a) or set in a box (b). (Source: CIRTES)

Micro-milling

Oscillating knife cutting

Laser cutting

Hot-wire cutting

®

Fig. 58.18 Four types of machines developed for the Pack&Strat process. (Source: CIRTES)

possible to place 24 pieces in the same box, perfectly arranged on 3 trays of 8 units each. In addition to the obvious improvement in the protective capability and the aesthetics of such a packaging, it provides a cost gain of 35%. Indeed, even if the cost of

custom-made cushioning (material and manufacturing time) is 1.35 times higher than the “bulk” cushioning material (bubble wrap and kraft pouch), the handling cost for packing parts is 3 times lower. All costs are reported and compared per unit.

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Additional cost gain is achievable, such as the reduction in transport costs since with the new packaging, the company only has 25 parcels (of 24 units) to ship instead of 60 parcels (of 10 units) and also a reduction of the environmental impact (lower carbon footprint and better recyclability of packaging). When small series of parts are considered or products whose specifications and dimensions have to be often modified, other gains are also easily quantifiable, such as reduction of storage costs for empty boxes and sometimes waste of packaging that has become obsolete, but also drastic reduction of packaging study costs at each time of product modification.

Fig. 58.19 Packaging of a turbocharger. (Source: CIRTES)

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58.6

Case Studies

The first applications of Pack&Strat ® were carried out for high added-value and relatively fragile prototype parts which had to be protected to be shipped to the customer. Such packaging had received a more than favorable feedback in view, not only of its effectiveness in terms of protection but also of the effect of simplicity and aesthetics that it exudes. Now its use is more widespread. Several cases are described in this chapter. Pack & Strat ® enables the multiplication of packaging design capacities: the software is simple, ergonomic, and makes it possible to design complex packaging without

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going through a design studio. Pack&Strat ® makes possible shapes that would normally be inaccessible in small series. For the automotive sector, Pack&Strat ® contribution is multiple. The solution is indeed used at different levels. At Bugatti Automobiles, for instance, the majority of the car components are stored in Pack&Strat ® packaging. That facilitates their stacking, even if the part has a complex shape and is fragile; they are also used to safely ship spare parts to dealers, especially abroad. In addition, the car parts used in the assembly lines are set on kitting trays with 3D inlays,

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designed and manufactured by Pack&Strat ®, ensuring a perfect hold of the parts between the storage area where the kitting trays are built and the assembly lines (Fig. 58.19). ® The use of inner packaging areas in Pack&Strat does not only limit the use of raw material but also standardizes the dimensions of the outer boxes for some items. Elements of the same type but of different sizes can thus be packed in the same way by simply adjusting the length of the spacers positioning each inner packaging zone, as it can be the case for half drive trains with different shaft lengths.

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Fig. 58.20 Examples of multicolor packaging of Jules Ferry’s bust (Pierre Noël Museum) and of the Océane sculpture by Dominique POLLES. (Source: CIRTES)

Fig. 58.21 Protection of final artworks. (Source: CIRTES)

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In the case of artwork, for example, the process can combine foam packaging within a wooden crate. The foam is cut in 2D on an oscillating knife cutting machine or, as below, in 3D by micro-milling. Such cushioning ensures a good distribution of the support and effectively protects the surfaces of the artwork (Fig. 58.20). Alternating colors enhances the aesthetics of the packaging.

Fig. 58.22 Protection of the master model made by the artist or from a ® 3D model produced in Stratoconception . (Source: CIRTES)

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Pack&Strat ® packaging is ideal for the luxury sector; Pack&Strat ® packaging helps improve customer perception of the products. Indeed, the customer who unpacks the product finds a rational, elegant packaging which reinforces the image of quality (Fig. 58.21). This protection system can also be adopted for the transport of master models (Fig. 58.22), often very fragile, between the artist’s studio and the production areas of the final artwork. Some parts, sensitive to shocks or in contact with hydrocarbon oil, need to be stored in specific boxes (Fig. 58.23). The process enables an inner packaging which adapts itself not only to the content but also to the container, as it is the case in Fig. 58.24. In this case, the part is also in contact with cutting fluids derived from hydrocarbons; cork is therefore a durable solution that is perfectly suited to 3D cutting by micro-milling. When using packaging for some dry tools of the same type (i.e., without traces of hydrocarbons), corrugated cardboard has proven to be one of the most economically and environmentally viable solutions. The cutting tool manufacturer SECO has integrated a Pack&Strat ® station for the on-demand manufacturing of custom packaging into its special tool production unit in order to properly pack the special parts of its premium customers, without any risk of breakage (Figs. 58.24 and 58.25).

Fig. 58.23 Example of inner packaging in cork for a tool holder case for SECO tools. (Source: CIRTES)

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Fig. 58.24 Example of packaging of a special cutting tool. (Source: CIRTES)

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At the GE Healthcare plant in Buc (Yvelines), packaging manufacturing has also been internalized: GE now produces itself on demand the packaging of its subsystems used for medical imaging and reduces storage space for packaging crates. Previously, GE transported a lot of empty space in its packaging. They now have packaging adapted to the products. They not only use Pack&Strat to package finished parts but also to make 1-to-1 scale mock-ups for engineering and to have a representation of the footprint of medical systems; to produce recyclable packaging; and to manufacture LEAN kitting trays to store parts and tools for workshop servants. CIRTES, at the origin of the process, uses it to send its own AM parts made in Stratoconception, whether they are presentation parts, aesthetic prototypes, or pieces intended for POPA (Point-Of-Purchase Advertising).

Fig. 58.25 Examples of packaging of special cutting tools and their tool holder. (Source: CIRTES)

Fig. 58.26 Example of packaging of a Rafale mock-up for a Dassault Aviation equipment manufacturer. (Source: CIRTES)

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Fig. 58.27 Example of packaging of a PMMA warhead for armament. (Source: CIRTES)

Fig. 58.28 Packaging of a large metal part for an aeronautical equipment manufacturer. (Source: CIRTES)

The Rafale scaled model for Dassault Aviation presented below (Fig. 58.26), made of PU resin by Stratoconception ®, is packaged in a wooden crate with an inner packaging in layers of extruded PE foam cut by Pack&Strat ® micromilling. This solution effectively protects all surfaces. Transparent, highly fragile, functional parts can also benefit from this type of ad hoc protection. For example, a PMMA warhead, manufactured in Altuglas using the Stratoconception ® process, is perfectly packaged in its ship® ping crate with polystyrene layers cut on a Pack&Strat machine by rapid micro-milling (Fig. 58.27). This Stratoconception ® part in alloy steel – Z38CDV5 (Fr), 2.2343 (DIN), and H11 (US) – but deformable due to its thinness and high-added value – achieves its safety in a polystyrene cushioning cut by hot wire (Fig. 58.28). This

example shows the capabilities of the process to produce very large packaging. Different levels of parts can be mounted without any risk of collision, which saves space in the transport step and to lower costs.

58.7

Conclusion

Additive manufacturing, so far used to produce models, tools, and direct parts, continues to extend its scope to new sectors. The “field of possibilities” is now open to the digital production of packaging and the 3D packaging of parts for industrial or individual use.

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The Stratoconception1 process was able, naturally enough, to initiate this innovation, from its basic concept and the industrial plate materials it uses. Indeed, the transformation of corrugated cardboard and foams, which are preferred materials for traditional packaging, are basic materials that are well known and qualified in Stratoconception1. For many years of R&D, the Pack&Strat1 process and its original method have been the subject of patents, software development, and the adaptation of a range of specific machines. It fits well the trend of the packaging market which is currently transforming the offer by proposing custom-made and personalization solutions (custom packaging), integrated digital solutions facilitating the package tracking (smart packaging), and environmentally friendly solutions using recyclable, recycled, and bio-based materials (green packaging). The applications of the process are already numerous and industrial references are multiplying. The INORI start-up is now dedicated to the commercial development of the process at the international level.

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Claude Barlier received his PhD in Mechanical Engineering at the former ENSAM Paris (now Arts et Métiers ParisTech). He was Professor of Additive Manufacturing at the Mines-Telecom Institute (IMT) until 2016. In the 1980s, he initiated a research that led to the patented process of Additive Manufacturing Stratoconception ® and the machining monitoring system Actarus ®. In 1991, he created and since then has managed CIRTES Corp., which has become a leader in additive manufacturing (rapid prototyping and tooling) and advanced machining. In 2001, he launched the Higher Institute of Design Engineering (PBC-InSIC), and in 2011, he created the INORI Innovation Platform, which he has chaired ever since. He also founded the VirtuReaL Fast Product Development cluster in Saint-Dié-des-Vosges, France. He is the author of numerous patents, publications, and books, and coauthor of the reference book “Fabrication Additive” (Dunod 2015–2020).

References 1. Brennan-Craddock, J., et al.: The design of impact absorbing structures for additive manufacture. J. Phys. Conf. Ser. 382, 012042 (2012) 2. Chen, X., et al.: Light-weight shell-lattice metamaterials for mechanical shock absorption. Int. J. Mech. Sci. 169, 105288 (2020) 3. Barlier, C.: Le procédé de prototypage rapide par STRATOCONCEPTION®, Actes des premières Assises Européennes du Prototypage Rapide, Ecole Polytechnique, Palaiseau, 2–3 juin 1992 4. Barlier, C., Abel, C., Di Giuseppe, D., Delebecque, B.: Pack&Strat ®, Procédé Original d’Emballage additif par Stratoconception ®, Assises Européennes de Fabrication Additive – Paris, 25, 26 et 27 juin 2013 5. Barlier, C., Abel, C., Monsallier, F.: Une solution numérique de FA opérationnelle dédiée à l’emballage rapide 3D, 19èmes Assises Européennes de la Fabrication Additive Rapide, Ecole Centrale de Paris, 24–26 juin 2014 6. NF EN ISO 17296-2:2016 Fabrication additive – principe généraux – Partie 2: vue d’ensemble des catégories de procédés et des matières de base, AFNOR 7. Barlier, C.: Procédé pour la création et la réalisation de pièces par C.A.O et pièces ainsi obtenues. Brevet français N 91–02437 (26 février 1991), Brevets européens N EP 0 585 502 (OEB 27/8/ 92). Février 1991 8. Barlier, C., Debboub, R.: Procédé de conception d’un emballage par Stratoconception intégré au procédé de conception du produit à emballer, Brevet international N 2 913 912. Mars 2007 9. Barlier, C, Bernard, A.: Fabrication Additive, Du Prototypage à l’impression 3D, 2eme édition, DUNOD 2020

Christophe Abel obtained his M.Sc. in Mechanical CAD/CAM (DESS) at the University of Metz. He is working as a R&D engineer at CIRTES SA. Since 1998, he has participated in the development of products resulting from the Stratoconception® process, especially the Pack&Strat ® software. He is also involved in all training courses provided by CIRTES, particularly around the digital chain and rapid product development.

Jean-Loup Rennesson obtained his M.Sc. Engineer in Chemistry at the former European Higher Institute of Chemistry of Strasbourg (EHICS), now renamed Ecole européenne d’ingénieurs de Chimie, Polymères et Matériaux (ECPM). He received his M.Sc. in Theoretical Chemistry and Computer Science at the University of Strasbourg and his B.Sc. in Computer Science at the University of Strasbourg. He is Consultant, INORI authorized sales agent.

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Index

A Abrasive flow machining, 842 Absorptivity profile group (APG), 217 Acetone fumigation, 564 Acoustic actuator, 373 Acoustic mixers, 614 Acoustic sensing experimental principles and methods, 524–525 with other monitoring techniques, 525, 526 Acoustic sensors, 480, 505 Acrylonitrile butadiene styrene (ABS), 540 Active optical systems, 805 Adaptive slicing, 430 Additive assurance, 507 Additive manufacturing & design (AMD), 896 Additive manufacturing file format (AMF), 261 Additive manufacturing metal specialist, 872 Additive processes, 868 AddUp experts, 911, 912 Adhesive bonding, 837 Ad hoc protection, 978 Adjoint approach, 290 ADMIRE, 858 Advanced manufacturing and AM, 889 automation, 888 and Industry 4.0, 888 robotics, 888 technologies for clean production, 102 Advanced persistent threats (APT), 312 Aeronautical equipment manufacturer, 978 Aeronautical part, 911 Aerospace, 56–57, 83, 127, 200, 329–330 Aerospace Industries Association (AIA), 643 Aesthetics, 954 Agile and leagile paradigm, 82 Agile development approach, 62 Airflow systems, 919 AISI 304/304L stainless steel, 701, 703, 704 AISI 316L stainless steel, 700, 702 AISI 420 stainless steel, 706 Al-Cu alloys, 716 Al-Si alloys, 715, 745 AlSi10Mg alloy, 743, 747 ALSTOM, 915 Altair Optistruct, 294 Alumina, 598, 600 Aluminum, 713, 718, 719, 722 Aluminum alloys, 716, 720, 752 Aluminium nitride (AlN), 598, 605

Aluminium oxide (Al2O3), 600 AM adoption aerospace industry, 56–57, 329–330 automotive industry, 58 change management, 66–67 design, materials and process, 881 education (see AM education) industry, 885–886 manufacturing industry sectors, 56 medical industry, 57–58 skills based training, 886–888 workforce, 882 AM education E&WD, 883–885 gaps and opportunities, 883 trends, 882, 883 and workforce development, 882 American Society for Testing and Materials (ASTM), 46, 59, 73, 572, 577-581, 640, 829 American welding society (AWS) D20 committee, 150 AM European skills strategy deployment, 860 Flagship activities foreseen, 862 forecast methods, 860 foresight scenarios, 860 gap drivers, 860, 861 observatory, 860 real case, 860 roadmap, 860, 861 SAM, 860 shortages, 860 short-term, 860 skills mismatches and gaps, 860 Skills Strategy Roadmap, 860 technology, 860 3D Printing Trend Report 2021, 860 AM impact over SCM aerospace industry, 83 automotive industry, 83 business model solutions, 82 healthcare industry, 82 Just-In-Fact manufacturers, 81 SC configuration, 82 AM implementation, 56, 57, 61, 65 digital process chain, 66 trial-and-error adoption approach, 65 AM industry adoption applications, 885 Certified AM Professionals, 886 competency levels, 885

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 E. Pei et al. (eds.), Springer Handbook of Additive Manufacturing, Springer Handbooks, https://doi.org/10.1007/978-3-031-20752-5

981

982 AM industry adoption (cont.) multi-disciplinary, 885 qualification and certification, 886 training and education, 886 workflow, 885, 886 AM316L SS alloy, 767 AM process chain, 74 AM build process, 242 AM machine preparation, 241 computer-aided design, 235 data preparation, 235 generic process chain, 233 heat treatment, 244, 245 laser powder-bed fusion, 234 layer-based processes, 234 manufacturing processes, 233 materials, 233 mechanical post-processing, 244, 245 part orientation and support structures, 235, 237, 238 part removal, 242–244 post processing, 234, 244 principle, 234 process parametrization, 234, 239–241 quality, 234, 246, 248 slicing, 238, 239 surface finishing, 246, 248 3D-file, 234 3D objects, 233 2D layers, 233 two-step process approach, 234 AM processes, 59, 897 BJ, 19–20 DED (see Directed energy deposition (DED)) emergence and commercialisation, 21 ISO/ASTM 52900, 4 ME, 15–17 MJ, 12–14 PBF (see Powder bed fusion) SL, 17–19 VPP, 5–6 AMSC Roadmap, 539 AMSENSE, 508 AM SS 316 L, 758 AM threat categories data in-/exfiltration, 306 illegal part manufacturing, 305–306 sabotage, 305 technical data theft, 304–305 AM training, 889 and education (see Education) manufacturing, 902 professional societies, 898, 899 qualification/certification, 893 quality, 900–902 readiness, 899, 900 requirements, 894–896 U.S. Universities, 896–897 Analyse phase, tool, 790 Analysis of Variance (ANOVA), 790 CTQs, 791 humidity, 793 Analytical hierarchy process (AHP), 200 Analytical method, 210 Anderson Darling test, 788 Anisotropy, 179, 426, 574, 578, 579, 717, 745

Index Annealing, 845, 847 Annealing heat treatment, 743 aluminium alloys, 742 HIP, 743 Ti6Al4V alloy, 742 Anodic polishing, 826 Antenna, 910–911 Antenna Pointing Mechanisms, 918 Antiquesportfolio, 94 Anti-waste bill for a circular economy, 109 Application engineer for Additive Processes, 872 Applications of AM advantages, 908 AM-based value chain, 908–909 antenna, 910–911 application fields, 907 automotive field, 909, 910 ball-joint, 909, 910 cold plates, 913, 914 gear lever, 909, 910 pedals, 909, 910 perfume glass bottle, 914–915 rapid product development, 907 rapid prototyping, 907 3D printing, 915, 916 Arcam, 50, 51 Arc-based DED processing, 466, 467 Architecture, 956 Array eddy current (AEC) sensor, 507 Arringatore statue, 925 Arts challenges, 953 conservation and restoration, 955–956 decorative, 954, 955 and education, 331 fashion design, 956–958 film, 958 fine, 954, 955 jewelry, 956–958 music, 959 tabletop gaming, 958, 959 wearable, 956–958 Artificial intelligence, 108, 809, 882, 888 Artificial neural network (ANN), 809 Artistic copyright, 95 ASTM, see American Society for Testing and Materials (ASTM) ASTM B243, 396 ASTM F42, 147–149, 151 ASTM B213, 445 ASTM B213-20, 729 ASTM B214-16, 728 ASTM B964, 445 ASTM D3795–20, 730 ASTM E10–18, 738 ASTM E18–20, 738 ASTM E92–17, 738 ASTM E466, 737 ASTM E467, 737 ASTM E468, 737 ASTM E606, 737 ASTM F3122-14, 672 ASTM International Additive Manufacturing Center of Excellence (AM CoE), 884, 887 ASTM International (F3049-14, 2014), 644 ATEX-defined safety standards, 105

Index Atmosphere, 390, 391 Atomization, 394 Austenitic stainless steels, 766 AISI 316L and 304L, 700 porosity, 701 SLM process, 700 tensile properties, 701 Authorial input, 94 Automatic manufacturing, 425 Automatic tool changer (ATC), 428 Automation, 882, 888 vibratory bowl feeders, 917–918 Automation and digitization of processes and products, 68 Automobile industry, 330–331 Automotive field, 909, 910 Automotive industry, 58 Avio Aero, 48, 51, 52 AWS D20 committee, 150

B Backscattered electron (BSE) signal, 732 Balling phenomenon, 393, 399, 502, 803 Ballistic particle manufacturing (BPM), 13 Ball-joint, 909, 910 Ball milling, 613 B2B sector, 52 B2C sector, 52 Benefit, 199–206 BE Semiconductor Industries AG (BESI), 119 Bespoke, 957, 958 Better products, 203 Big-Area Additive Manufacturing (BAAM), 12 Big Data, 882, 888 Binary, 372 Binary Al-Si, 714 Binder jet 3D printing, 454 Binder jetting (BJT), 5, 178–183, 185–195, 551, 609, 836 advantages, 452 beamless AM, 443 binder specifications, 446, 447 challenges, 444 commercial timeline, 20 CPJ, 20 definition, 19 derivatives, 19 drying step, 444 ExOne, 20 Extrude Hone, 19 fabrication, 444 ink-jet technology, 19 materials and applications, 452, 453 MJF, 20 optimization steps, 452 post-processing (see Post-print processing) powder characteristics, 445, 446 PP, 19 precision metal AM parts, 20 primary parameters and corresponding effects, 445 printing and post-printing process, 444 process steps, 443 SPJ, 20 3DP, 19 variations on processing steps, 447–449 Voxeljet, 19 Bioextruder system, 946

983 Bioinspired design, 281 Biological coupling, 275, 276 Biological effects, 275, 276 Biologically inspired design, 274 BioMaTE equipment, 944 Biomedical industry, 330 Biomimetics, 273–276, 281 Biomimicry, 273–276, 281 Bionics, 273 Bioprinting, 96, 553 BioTRIZ, 275, 276 Blockchain technology, 33 Boeing, 56 Bonding, 343, 344 Bone regeneration, 330 Borides, 606 Boron carbide (B4C), 598, 603 Brinell hardness, 738 Bronze model rendering, 933 Bubble jet, 373 Build bed, 447, 448 Build direction, 178–180, 182, 185–187, 193, 194, 196, 235 Building blocks, 863 Build rates, 242, 400 Build time, 183, 186 Buoyancy, 220 Burnishing, 827 Business as usual, 90 Business model innovation, 45 Business models AM ecosystem, 32 blockchains, 44 comparisons, 48–50 consumer-centric, 44 emergent firms, 49 emerging industry, 44 firm’s activity system, 44 firm’s value proposition, 44 four Vs (see Four Vs business models) home fabrication, 44 managerial implications, 51–52 open source design, 51 patterns, 44 value creation, 44 value network, 50–51 Business opportunities, 31, 32, 34, 40 Business students, 884 Buy-scenario, 38

C Cable guides, 915, 916 CAD file, 89 computer program, 89, 95 copyright and protection, 96 design data, 90 designing, 93, 94 intellectual creation/personal touch, 89, 90 printing and distributing, 93 sharing/disseminating, 96 sharing, 93 trade secrecy and contractual agreements, 96 Candidate characteristics (CCs), 813 Canon production printing, 15 Capstone (senior) design, 896 Carbides, 602

984 Carbon3D Inc., 50, 51 Carbon, 603 Carbon based components, 603 Carbon fibers, 632 Carbon materials, 51 Carnegie Mellon University (CMU), 896 Cascade control strategy, 483 Case studies, 907 heat exchangers (see Heat exchangers) hybridization, 916–917 serial productions, 916–920 Castable resin, 958 CATIA, 915 Cavilus HF illumination system, 498 Cavitar CAVILUX diode, 502 CECIMO AM working group (AM WG), 103, 111 CECIMO national associations, 103 Cellular automata, 227–229 CE marking, 104, 106 CEN/TC 438 committee, 149, 150 Ceramic-based BJ system, 19 Ceramic matrix composites (CMC), 548, 606 Ceramic oxide, 600 particle’s shape, 600 purity, 600 size, 600 surface area, 600 Ceramic particles, 607, 608 Ceramic powder, 560 Ceramics, 597, 599 Ceramic yield, 605 Certification, Qualification & Standardisation (CQS), 864 Certification, 248, 545 Certified AM Professionals, 886 Certified Industrial Technician for Additive Manufacturing, 872 Certified prosthetists and orthotists (CPOs), 122 Challenges, 400 Channels, 410, 414, 912 Characterization, 617 ceramic materials, 617 suspensions, mixtures, slurries, 617 3D printed samples, 618 Charge-coupled device (CCD) camera, 487 Chemical and electrochemical processing, 826 Chemical bath, 847 Chemical etching, 844 Chemical hazards, 560 Chemical processes, 844, 847 Chemicals Strategy for Sustainability, 107 Chemical vapor smoothing, 847 Chemical vapor deposition (CVD), 616 Choice of methods identification of parts with major design changes, 204, 205 minor design change, 203 Chromium carbides, 767 Chromium-molybdenum steel, 746 Circular Economy Action Plan (CEAP), 108 CIRTES, 968, 977 Class D fire extinguishers, 542 Classical/physical modeling, 477 Classification, labelling and packaging (CLP) regulation 1272/2008, 107 Classification framework, 248 Cleaning processes, 845–846 CLLAIM, 858, 863 EU project, 868 job profiles, 878

Index occupational profiles, 868, 875, 876 professional profiles, 875 profile, 873 profiles operator, 876 programme, 873 qualification framework, 868, 871–873, 876 CM industries, 83 CNC machining, 425 CO2 emissions, 895 Coating spray, 258 Coaxial grains, 768 Cobalt chromium alloys (CoCr), 57 Co-Cr-Mo (CCM) alloys, 769 Cold Isostatic Pressing (CIP), 426 Cold plates, 913, 914 Cold spraying (CS), 821 Co-legislators, 105 ColorJet printing (CJP), 20 Colored digital model, 926 Colored physical models, 926 Columnar to equiaxed transition, 224 Commercial alloys, 769 Commercial ecosystem, 32 Commercialization timeline, 21 Commercial machine manufacturers, 646 Commercial matrix, 630 Commercial thermoplastics, 576 Commissioner, 96 Competence Unit, 863 Competencies, 868 Competency requirements characteristics, 868 design and pre-process, 868–870 in-process, 870 operation of AM systems, 868 post-process and finishing, 870 Complementary metal-oxide-semiconductor (CMOS) sensor, 485, 487, 491, 502, 507 Complex ceramic architectures, 612 Complexity, 200–203 Complexity for free, 116, 117 Complex structures, 615 Compliance, 290, 291, 295 environments, 109 Compliant mechanism, 288, 290 Composites, 548 materials, 632 reinforcements, 631 Computational aided engineering (CAE) simulation, 823 Computational modeling, 897 Computational numerical controlled (CNC) machining strategy, 823 Computed tomography (CT), 254, 258, 266 Computer-added design (CAD), 74, 233–235, 322, 460, 823, 895, 908, 918, 969 CAD/FEA experience, 900 design, 95 features, 260 file, 89, 90, 93–96 model, 254, 260, 262, 607 model developer, 74 software programs, 964 software suite, 89 3D CAD data, 873 3D CAD model, 5, 869 Computer-aided manufacturing (CAM), 823 Computer automated manufacturing process and system (CAMPS), 13

Index Computer-based methods, 270 Computer numerical control (CNC), 32, 41, 128–130 Condition to operate, 538 Conductivity, 382 Conformal cooling, 296 Conformal HLM, 431 Conical shape heat source model, 216 Consolidation, 614, 615 Constrained fitting approach, 254 Construction biomimetics, 274 Construction graph, 95 Consumer goods, 58 Contact-based systems, 256 Contact 3D scanner, 256 Contact measurement systems, 650, 805–807 Contact surface, 339 Contamination, 450 Continuing education (CE), 883 Continuing Education Units (CEUs), 897 Continuous DLP (CDLP), 350, 360–365 Continuous fiber composites, 633 Continuous-jet binder deposition systems, 449 Continuous jetting, 372 Continuous liquid interface production (CLIP), 6, 50 Control phase, 794 Convective flow effect, 222–223 Conventional layer-upon-layer additive manufacturing, 50 Conventional machining, 57, 59 Conventional manufacturing (CM) processes advantages of AM, 129 aerospace and medical industries, 127 automation, 127 casting, joining, forging and machining methods, 128 industries, 130 parameters, 129 thin layers of materials, 127 Conventional technologies, 911 Coordinate measuring machine (CMM), 254, 256, 805, 807, 808, 829 Coordinate systems and test methodologies, 574 Copper, 453 alloys, 913 Copper doped tricalcium phosphate (Cu-TCP), 277 Copyright law CAD file, 89 governed by, 89 private use exception, 91, 92 WCT, 89 Copyright protection creativity work, 88 European Commission Study, 89 rightholder’s permission, 88 Cordierite, 601 Correspondence, 262 Corrosion behavior, 746, 747, 751, 752, 760–762 AlSi10Mg alloy, 752, 762, 764 AM/MS microstructure, 765 AM titanium alloys, 768 Co-Cr-Mo alloys, 769 EDX and XRD analysis, 766 electrical conductivity, 763 hot pressing HP, 768 inconel alloys, 769 316L SS and LRM, 767 316L stainless steel, 765 overlapping layers, 762 SHT heat treatment, 769

985 SLM/CCM alloys, 770 SLM alloys, 765, 768 Ti6Al4V alloy, 768 Corrosion measurements, 763 Corrosion resistance, 766, 828 Corrosion response, 770 Cosmetics industry, 964 Cost, 178, 179, 183, 185–187, 189, 191 Cost model by Baumers, 37 by Hopkinson and Dickens, 36 by Lindemann, 37 by Ruffo, Tuck and Hague, 36 Cost strategic plan, 37 COVID-19 pandemic, 103, 110, 540, 544, 885, 887 Crack compliance method (CCM), 649 Cracks, 803 Craft manufacturing, 81 Creativity, 277, 283 Creep test, 737 Critical pressure, 211 Critical to quality (CTQs), 780, 782, 786, 788, 789 activities, 786 customer requirement, 783 hardness, 789 Kano model, 783 VOCs, 783 Cross-sectional image, 339 Crystallization, 181, 188, 915 Crystallographic texture, 680, 681 and grain morphology, 679 CSEM redesign, 918 Cultural heritage preservation, 923 Culture, 953 architecture, 956 Curing, 449, 848 Customer requirements, 782 Customization, 33, 200, 202 Custom-made device (CMD), 110 Custom packaging, 963, 979 Custom products, 203 Cutting precision, 826, 969, 970 Cutting process, 115, 730 Cybersecurity, 79, 882, 888, 889 Cyber supply chain risk management AM, 79 definition, 79 manufacturing industry, 79 network demand patterns, 79 research field, 79 Cyber virtual supply chain risk, 78 Cyclic fatigue, 828

D Data acquisition, 260 Data association, 262 Data-driven modeling, 477 Data in-/exfiltration, 309, 311 Data manipulation techniques, 931 Data per se, 91 Daylight Polymer Printing (DPP), 6 De-binding, 449, 604, 607, 614, 615 Decentered square growth algorithm, 228 Decimation, 265 Declaration of conformity, 104

986 Decorative art, 954, 955 DED-CLAD ®, 916, 917 DED process, 916 Deep belief network (DBN), 506 Defects characterization, 798 detection sensitivity, 799 end quality, 799 geometric defects, 800, 802 internal, mechanical and feedstock, 800–803 NDE (see Non-destructive evaluation (NDE)) PBF-manufactured parts, 798 propagation in PBF process, 799, 801 Test Artefacts (TA), 808, 809 Define phase, 779, 780 Deformations, 244 Degrees of freedom (DOF), 335 Delamination, 803 Dematerializing supply chain, 76, 81 Dendritic arm spacing primary, 224 secondary, 224 Dendritic solidification, 224 Densification, 450, 614 HIP, 451, 452 infiltration, 450 pressureless sintering, 450, 451 printing, 450 Design for Manufacturing (DFM), 895 Density filtering, 291–293 Density reduction, 589 Dental aligners, 121, 122 Deposition rate, 461 De-risk AM, 895 Design, 611, 956, 957 approaches, 611 configurators, 68 engineer, 885, 887 and execution, 839–840 intent, 254 principles, 178, 183, 191, 192 and removal of supporting structure, 328 strategy, 203 Design for additive manufacturing (DfAM), 62, 131–133, 202, 288, 884, 893–895, 897–899, 908 Design guidelines angle of support-free overhangs, 193 anisotropy, 179, 180 digital resolution, 182 early determination of part orientation, 186, 187 function oriented design, 183, 185 hybrid parts and integrated components, 189 integration of functions, 185, 186 layer-by-layer process, 178 material minimalism, 187 material properties, 195 materials and processes relationship, 179 maximum overhang length, 195 minimal and maximum hole diameters, 195 minimal gap width, 194 minimal wall thickness, 193 physical resolution, 182, 183 process characteristics, 178 purpose of, 177 residual build material, 182, 190–192 stair-case effect, 178, 179

Index stress and warpage, 180, 181 support structures, 181, 187, 188 tolerances, 189, 190 Design strategies, 277 CAD tools, 270 conceptual design, 269 creativity, 270 design process, 270 generative design, 269, 270 high-performance computing, 270 manufacturing process, 270 requirements, 270 technical decisions, 269 topology optimization, 269, 270 Desktop manufacturing (DTM), 7 Desktop metal, 20, 50, 52 Destructive testing, 896 Differential scanning calorimetry (DSC), 449 Differential thermal analysis (DTA), 449 Diffraction pattern, 728 Digital imaging and communications in medicine (DICOM), 57 Digital light printing, 6 Digital light processing stereolithography (DLP), 350, 351, 355, 358, 360, 363, 366 Digital light projection (DLP), 355–358, 549 Digital light synthesis (DLS), 6 Digital manufacturing, 888 Digital materials, 13 Digital metal, 20 Digital process chain, 57, 58, 60 Digital replication, 254 Digital resolution, 182, 183 Digital single-lens reflex (DSLR) camera, 499 Digital transformation, 882 Digital workflows, 122, 123 Dimatix printer, 383 DiMatteo’s analogue method, 21 DIN EN ISO 6520-1, 783, 788 Diode area melting (DAM), 821 Direct digital manufacturing, 81 Directed energy deposition (DED), 4, 178–183, 185–195, 213, 234, 459, 516, 551, 552, 673, 821, 822, 824–826, 835–836, 882 advantages, 11 applications and commercial systems, 12, 470–471 arc-based DED processing, 466, 467 chronological history, 12 commercial DED machine, 459 conventional welding processes, 459 defects, 468–470 definition, 9 deposition, 673 electron beam with wire feed, 464–466 feeding mechanisms, 673 feedstock material, 460 heat transfer, 676 interstitial elements, 691 laser-based powder-blown DED, 11, 462 laser with wire feed, 464 LCVD, 11 LENS, 11 linear heat input, 461 and L-PBF, 691 metallic melt pool, 460 microstructure and mechanical behavior, 467–468 multi-layer laser cladding system, 11 multi-material printing, 459

Index NASA engineers, 11 and PBF processes, 676 printing process, 460 processes and characteristics, 462 process types, 460 publications, 460 repair and coating applications, 460 spatial resolution and quality, 463 three-dimensional welding, 11 Westinghouse Electric Corporation, 10 Direct ink writing (DIW), 336, 611 Direct laser deposition (DLD), 12 Direct laser fabrication (DLF), 11 Direct laser writing (DLW), 5 Direct layer monitoring, 498 Direct light processing (DLP), 120 Direct [Material/Energy] Deposition (D[M/E]D) process, 426, 430 Direct material jetting, 13 Direct metal deposition (DMD), 11 Direct metal laser melting, 390 Direct metal laser sintering (DMLS), 8, 390 Direct metal printing (DMP), 7 Direct shell production casting, 19 Direct-write laser technique, 947 Discrete element methods, 211 Dispersion, 612 Disruptive manufacturing process, 21 Dissolution-precipitation, 592 DIYers, 92 DMAIC approach, 778, 779 DMLS-AlSi10Mg alloy, 762 DMLS process, 753 DMP-meltpool event volume, 496 Dual-metal heat exchanger, 913 Dual Vocational Education and Training (Dual VET) programmes, 871–868, 873, 875, 876 Ductility dip cracking, 662 Duplex Stainless Steels (DSS), 707 Dynamic electrical noise, 919 Dynamic lighting, 958 Dynamic transmission electron microscopy (DTEM), 735

E EBM process, 823 EC aims, 109 EC industrial policy initiatives, 111 E-commerce, 963, 964 Econolyst, 49 Ecosystem, 204, 883 EC task force, 102 Eddy-current testing, 829 Edison Welding Institute (EWI), 17 Education and AM training, 898–900 U.S. Universities, 896 Educational Association of the Bavarian Economy, 872 Education &Workforce Development (E&WD), 883–885 EH&S event, 539 E-learning, 887 Electrical connection interfaces, 918 Electrical discharge machining (EDM), 244, 843 Electric guitars, 959 Electrification and novel materials, 139, 140 Electrochemical EIS measurements, 765 Electrochemical polishing, 826

987 Electrolytic polishing, 826 Electromagnetic compatibility (EMC), 105 Electromechanical components, 919 Electron backscatter diffraction (EBSD), 732 Electron beam, 390, 459, 460, 464, 466 Electron beam additive manufacturing (EBAM), 11, 460, 516 Electron beam DED, 471, 825 Electron beam freeform fabrication (EBF3), 11 Electron beam layer manufacturing, 11 Electron beam melting (EBM), 4, 6, 8, 9, 390, 629, 640, 700, 728, 821 Electron beam powder bed fusion, 391, 392 Electron beam powder bed fusion additive manufacturing (E-PBF AM), 641 Electron-beam powder bed fusion (EBM), 718 Electron beam wire-fed DED, 466 Electron discharge machining (EDM), 824 Electronics, 381 Electron microscopes, 728 Electro optical systems (EOS), 6, 7 Electroplating, 847 Electropolishing, 826 Electrospark deposition, 844 Electro-strengthening, 844 Electrothermal process, 843–844 EMC directive, 105, 106 Emerging firms, 44, 49, 52 Emissions of ultrafine particles, 540 Empirical cumulative distribution function (ECDF), 503 Empirical method, 210 Emulsion evaporation, 592 Enamel filling, 931 Enamel firing, 931 Enclosures, 540 End quality, 799 optical scan technique, 805, 806 XCT, 804, 805 Energy, 34, 35, 37, 38 consumption, 35 beam, 392 dosage equation, 354 parameters, 392 source modeling, 214–217 Energy dispersive spectroscopy (EDS), 732 Enhanced products, 33 Enterprise resource planning (ERP), 202, 203 Environment, health and safety (EH&S), 537–540, 544, 5448 Environmental product declaration (EPD), 540 Environment hazards, 542 Equiaxed transition, 682 Equipment for potentially explosive atmospheres (ATEX) Directive, 105 EU Circular Economy Action Plan, 97 EU funded projects ADMIRE, 858 AM qualifications, 857 CLLAIM, 858 EWF, 857 IAMQS, 857, 862, 863 ManuFUTURE Vision 2030 Strategy, 857 new qualifications and skills, 863–865 SAM, 858, 859 EU Green Deal, 97 EU industrial sector, 111 EU legislators, 111 EU Machinery Directive, 101 EU Medical Device Regulation, 101

988 EU policy actions, 103 EU policy framework, 111 EU policymakers, 110 EU Product Liability Directive, 108 EU Regulations and policies impacting AM AM machines (see Regulations impacting AM machines) pillars, 103 primary regulatory obligations, 103 products developed with AM (see Regulations impacting Products developed with AM) European Chemicals Agency (ECHA), 106, 107 European Commission (EC) initiatives, 102 European Committee for Electrotechnical Standardisation (CENELEC), 147 European Committee for Standardisation (CEN), 147 European Industrial Strategy, 102 European Observatory, 860–863 The European Parliament and the Council of the European Union, 104 European Patent Convention (EPC), 90 European Patent for the Common Market, 95 European Qualifications Framework (EQF), 858 European Standardisation Organisations (ESOs), 147 European Telecommunications Standards Institute (ETSI), 147 European Union Aviation Safety Agency (EASA), 643 European Union (EU), 60 EU rules, 109 Eutectic silicon structure, 753 Evolutionary structural optimization (ESO), 278 EWF Quality Assurance System, 858 EWF Quality System rules, 863 Exceptions and limitations (E&L), 91, 96 External physical supply chain AM organization, 80 3D printers, 80 OEM, 80 Extrusion-based additive manufacturing process, 211 Extrudate, cross-sectional geometry, 337, 338 Extrusion flow, 342, 344 Extrusion processes, 585

F Fabrisonic LLC, 17 Face milling, 434 Factories of the Future Research Association (EFFRA), 163, 164 Famergie platform, 912 Farsoon technology, 7 Fashion design, 956–958 Fatigue, 451 failure, 737 strength, 746 Feasibility, 177, 178, 192, 193, 195 Feasible design, 185, 187 Fe-Cr alloys’ surfaces, 766 Feedstock, 179, 181, 187, 190, 191, 445, 446, 452 disperse particles, 728 equilibrium torque, 730 flowability, 729 material, 21, 459, 460, 462, 464, 470, 611 microscope, 728 powder characteristics, 728 sieves analysis, 728 Femoral defect study, 943 FEM, see Finite element method (FEM) Ferrous and non-ferrous metals, 875 FFF-based printers, 553 Fiber Bragg grating (FBG), 505

Index Fiber-matrix adhesion, 635 Fiber-matrix interactions, 633, 635 Fiber reinforced AM (FRAM) process, 628 Fiber reinforced composites, 633 continuous fiber, 633 FRAM study, 633 Fiber reinforced plastic (FRP), 433 Fibers, 607, 634 Field programmable gate array (FPGA) controller, 483 Filaments, 540 File formats, 182 File size, 265 Filler, 341 Filling parameters, 238 Filling patterns, 238 Film, 958 Filtering, 291–292 Filters, 542, 543 Fine art, 954, 955 Finite element analysis (FEA), 676, 823 Finite element method (FEM), 289 Finite element simulation, 483 Fire detection, 543 Firm level AM adoption challenges, 59 implementation implications, 60, 61 manufacturing costs, 58 organisation-related factors, 59, 60 SME, 58 technology-related factors, 59 1st order benefits, 118 Fish-scale microstructure, 753 5M method, 790 Flame-holding, 915 Flammable metal powders, 561 Flat 2D photographic images, 3 Floating exhaust system, 910 Flowability, 395, 445, 729, 730 Flow measuring probes, 919–920 Foam packaging market, 964 Fockele & Schwarze (F&S), 4 Focused ion beam (FIB), 735 Forecast methods, 860 Forging, 930 Form follows function, 184 FormUp 350 machine, 911 Foundational courses, 897 Foundry mechanic, 871 Four VS Business models AM industry, 44 GE, 47–48 HP, 46–47 representation, 44 Stratasys, 45–46 3D systems, 46 Fraunhofer Institute for Applied Materials Research (IFAM), 16 Fraunhofer Institute for Ceramic Technologies and Systems (IKTS), 15 Fraunhofer theory, 728 Freeze-Form Extrusion Fabrication (FEF), 16 Friction stir additive manufacturing challenges and future research, 420–421 defects, mechanical properties and microstructure, 417–418 description, 416–418 Functional components, 735 Functional integration, 246 Functionally-graded lattice, 294, 298 Functionally Gradient Matrix (FGM), 426 Functional materials, 453, 454

Index Function-driven design strategy, 33, 184, 203 Fused deposition modeling (FDM), 15, 45, 87, 336, 540, 610, 629, 836, 925, 945 Fused filament fabrication (FFF) process, 16, 139, 336, 730, 778

G Gage Repeatability and Reproducibility study (Gage R&R), 787 Galvanometer-based laser processing control, 491 Galvanometer-based melt pool imaging system, 491 Gap drivers, 860, 861 Gap width, 194, 195 Gas atomization, 660 Gas porosity, 660 Gaussian power distribution, 462 Gaussian process-based predictive map, 810 Gaussian process (GP), 809 G-code, 239 Gear lever, 909, 910 Gelcasting, 616 General Electric (GE), 139 AM, 47, 48 approach, 47 Arcam investment, 48 HP, 48 LEAP engine, 47 longest-established technology companies, 47 General hazards, 559 General Product Safety Directive (GPSD), 107, 108 Generative design, 281–283 applications, 270, 272 architectural models, 271 artificial intelligence, 272 BIM-based process, 271 CAD environments, 273 cellular automata, 271 characteristics, 273 complex process, 273 creativity, 271, 272 elements in relations, 272 genetic algorithms, 271 genetic programming, 271 history-based parametric CAD system, 270 hybrid design spaces, 273 integrated generative design framework, 271 L-systems, 272 parametric modelling, 271 performance-driven, 270 problem definition, 273 random sampling method, 270 shape grammars, 272 solar panels, 271 space-filling generative design, 273 swarm intelligence, 272 techniques, 270, 271 topology optimization, 272, 273, 276–282 two-dimensional (2D) sketches, 273 workflow, 270 Generic AM-design process, 116, 117 Geometric accuracy, 521 Geometrical assessment, 649 Geometrical modified group (GMG), 217 Geometric Benchmark Test Artefact (GBTA), 808 Geometric defects, 800, 802 Geometric dimensional and tolerancing (GD&T) analysis, 829

989 Geometric prototypes, 966 Geostationary orbit (GEO) missions, 919 Germanium (Ge) photodiode, 496 Giant Composite Prints, 18 Giga STM G 3020 Rapid Prototyping, 967 Glass fibers, 632 Glass-like carbon components, 604, 605 Glassy carbon, 604 Global AM industry, 55 Gloves, 543 Gluing, 837 Goggles, 544 Gold plating, 931 Google searches, 897 Gradient method, 290, 291, 294 Grain morphology, 681, 684 GranuDrum, 395 Graphical interface, 969 Graphite, 603 Gravity, 958 Great Baltimore Fire of 1904, 146 Green body, 607, 614 Green packaging, 964, 968, 979 Green samples, 618 Grinding, 827 GTAW DED processing, 467 Guidelines, EH&S Standards, 539

H Hafnium diboride, 606 Hall/Carney flow test, 395 Hall flowmeter, 729 Hall-Petch hardening, 826 Hand finishing, 246 Hands-on training, 883 Hard metal composites, 453 Hardness test, 738 Hard X-ray photons, 527 Harmful substances, 562 Harmonized system for assessment, 862 Hatch distance, 239 Hausner ratio, 395 Hazards, 548, 560, 561, 563–566 Health, 542 Health hazards, 549, 551 Hearing aids, 120, 121 Heat conduction, 214 Heat convection, 217 Heat exchangers, 138, 296 CEA, 912, 913 copper alloys, 913 dual-metal heat exchanger, 913 FormUp 350 machine, 911 L-PBF process, 913 manufactured, 911 methanation exchanger-reactor, 912 multi-material, 913 PrintSky, 911 selective powder deposition, 913 stainless steel, 913 Temisth, 911 thermal equipment, 911 Heat management, 137–139 Heat radiation, 217

990 Heat source, 214 line, 215 point, 214 surface heat, 215 volumetric, 215 Heat transfer, 217–218, 682 Heat treatment, 244, 245, 398, 707, 716, 741, 744, 747, 752, 753, 766, 825, 826, 908 Co-Cr alloy, 747 cooling rates, 742 distortions, 742 to 15-5 PH alloys, 747 material, 742 temperature/time, 742, 743 HEWAM, 911 Hewlett-Packard (HP) AM, 47 ambition, 46 business-to-business market, 47 collaborations, 47 fourth industrial revolution, 47 MJF technology, 47 Siemens, 47 silicon valley technology pioneer, 46 strategic rationale, 47 3D designers, 47 traditional rivals, 47 Hexaaryl-bisimidaxolyl (HABI), 362 High-Area Rapid Printing (HARP), 363 High cyclic fatigue (HCF), 828 Higher education (HE), 858, 883, 884 Higher order benefits, 40 High-magnification microstructures, 689 High-pressure torsion (HPT) technique, 767 High speed sintering (HSS), 9 High-temperature materials, 919 Hole diameter, 192, 194, 195 Hollow featured additives, 586 Home 3D printing, 91 Homogenization, 288, 294 Honeycomb cardboard, 970 Hopkinson and Dickens’ cost model, 36 Hot cracking, 719, 722 Hot isostatic pressing (HIP), 244, 329, 398, 426, 451, 452, 666, 743, 825, 826, 845, 965 pressure application technique, 759 temperature, 759 treatment, 759 Hot melt extrusion (HME) process, 336 Hounsfield scale (HU), 260 House of Quality (HOQ), 780, 784, 785 HP-branded 3D printers, 47 HP’s Metal Jet Printing (MJP), 9 Hybrid-AM machining process, 826 Hybrid digital-physical frameworks, 74 Hybridization, 427 DED-CLAD ®, 916, 917 DED process, 916 Inconel 718, 916 internal chamber and channels, 916 L-PBF process, 916 machining and welding, 917 MMB-Volum-e, 916, 917 Hybrid layered manufacturing (HLM), 426 MSMA-HLM, 440 sequence of operations and the tools, 437 tools, 440

Index Hybrid manufacturing (HM), 80, 426, 842 composite mold with conformal cooling channels, 433 egg template, refrigerator, 429 stages, 428 synergic integration, additive and subtractive manufacturing, 426 Hybrid metal systems, 748 Hybrid processes, 615 approach, 428 energy sources, 431, 432 kinematics, 430, 431 materials, 432–434 and multiple technologies, 426, 427 slicing, 429, 430 types, hybridization, 427 Hydride De-Hydride (HDH), 394 Hydrocarbon oil, 976 Hydroxyapatite, 602 Hyperspectral cameras, 501

I Ideal design, 185–187 Identification methods machine learning based identification of AM part candidates, 202 suitable AM processes for given parts, 199 suitable parts for AM processes, 200, 201 Illegal part manufacturing, 305–306, 309 Imaging or thermal imaging, 646 iMaterialise, 955 Impact Assessment Study, 104 Impedance-based structural health monitoring (SHM), 310 Improved delivery, 33 See also Supply chain Improve Phase, 792 Inconel, 910 alloys, 769 625 L-PBF AM artefacts, 650 718 alloy, 747 Incremental launch, 33 Indirect costs, 36 Indium gallium arsenide (InGaAs) photodiodes, 482, 484 Induction heating, 844 Industrial AM Industry Council (IAMIC), 861 Industrial AM segment, 102 Industrial CT scanning, 258, 259 Industrial grade AM processes, 672 Industrial implementation, 67 Industrial internet of things, 888 Industrialization, 57, 60, 68, 890 Industrial manufacturing solution, 43 Industrial parts, 295 Industrial policy communication, 102 Industrial resilience, 103 Industrial revolution, 145 Industrial sectors, 116 Industrial strategy, 103 Industrial Technologies Directorate, 163 Industry 4.0 (i4.0), 120, 167, 888 Industry-based training programs, 883 Infiltration, 450, 453 InfiniAM Sonic, 509 InfiniAM spectral software, 509 Information biomimetics, 274 InfoSoc Directive, 91 InfraRed (IR) thermal imaging, 519, 807, 808 Inhalation, 542 Inherent strain method, 298, 299

Index Inhibitors, 67 In-house production, 918 Inkjet printing, 381, 945 In-Line, 478 Inline coherent imaging, 491–493 Innovation methods, 274–276 In-process depth meter (IDM), 494 In-scan process, 478 In-situ measurement modules, 827 In situ/operando X-ray techniques high-speed X-ray imaging, 529–531 in situ X-ray diffraction, 531 X-ray μ-CT, 528, 529 In-situ monitoring, 810 Inspection, 438, 440 Inspection and Quality Control Engineer, 885 Inspector, 868, 871–873, 875, 876 Instapak ®, 964 Integrating sphere radiometry (ISR), 523, 524, 527, 531 experimental principles and methods, 523 integrating sphere, 523 ISR with other monitoring techniques, 524 Integration of function, 185, 186 Intellectual property (IP), 87, 202 Intellectual property rights (IPR) aim, 87 3D printing, 87, 88 Interdendritic zone, 714 Internal, mechanical and feedstock-related defects balling, 803 cracks, 803 delamination, 803 layers’ adhesion, 803 porosity, 800, 801, 803 surface and texture, 803 Internal flaws, 435 Internal market and consumer protection, 107 Internal physical supply chain classification, 79 internal network, 79, 80 mixed process AM-CM process, 80 Internal stresses, 761 International AM Qualification Council (IAMQC), 861 International AM Qualification System (IAMQS), 857, 862, 863 International Electrotechnical Commission (IEC), 147 International Organisation for Standardisation (ISO)/American Society for Testing and Materials (ASTM), 821 International Organization for Standardization (ISO), 59, 147, 149, 640, 829 International Telecommunication Union (ITU), 147 Internet of Things, 108 Invention of the wheel, 429 Inventory, 200, 201, 203, 204 Investment, 90 IR camera, 500 Iron scaffolds, 942 ISO 13517, 445 ISO 17296-3, 829 ISO 27548, 540 ISO 4324, 445 ISO TC 261, 559 ISO14040:2006, 40 ISO14044:2006, 40 ISO/ASTM, 148–158, 572, 779 ISO/ASTM 52900, 4, 77, 672, 779 ISO/ASTM 52903–1:2020, 573

991 ISO/ASTM 52907:2020, 445 ISO/ASTM 52911-1, 288 ISO/ASTM 52920, 778, 779 ISO/ASTM 52921, 235, 248, 574, 578 ISO/ASTM 52924, 248 ISO/ASTM 52925, 248 ISO/ASTM 52931, 542, 779 ISO/ASTM 52933, 540 ISO/ASTM 52942:2020, 886 ISO/ASTM-52950, 235 ISO/ASTM CD 52931, 561 ISO/ASTM CD 52932, 549 ISO/IEC Directives, 146 ISO/TC 261, 148–149 ISO 9001, 540, 545 Isotropic carbon, 604 Iterative Closest Point (ICP), 262

J Jewelry, 956–958 Just-In-Time manufacturing (JIT), 76, 81

K Kano model, 783 Kevlar and glass fiber composites, 630 Kevlar fibers, 632, 633 Key characteristics (KCs) AM part (KCpart), 812 AM process (KCprocess), 812, 813 definitions, 810 identification, 812, 813 implementation, 811 management, 811 manufacturing and optimization phases, 810 properties, 811, 812 QC, 811 selection, 811 Keyhole porosity, 399, 661 Key performance indicator, 200, 204

L Labor, 35, 36 Lack of fusion pores (LOF), 758 Lack-of-Fusion Porosity, 392, 393 Lagrange multiplier, 290 Laminated object manufacturing (LOM), 17, 408, 426, 551, 837 Langurrer’s approach, 293 Large-scale additive construction, 345 Laser-based DED (L-DED), 11, 516, 517, 519–523, 528–531, 825 Laser-based post-processing, 844–845 Laser based powder bed fusion (LB PBF), 57, 116, 128, 390, 391, 475, 516–526, 529–531, 792, 825, 872, 875, 876, 909, 913, 914, 916 acoustic sensors, 480, 503–506 EB-PBF, 673 features size, 673 industry solutions, 481, 507–511 off-axis system, optical sensors, 479–480, 495–503 optical on-axis sensor systems, 479, 481–495 powder bed, 673 principle, 673 production-integrated measurement techniques for, 477 residual stresses, 676 of Ti6Al4V, 673

992 Laser-based powder bed fusion of metal (LPBF-M), 32, 37, 38, 178, 180–183, 186, 919 Laser-based powder bed fusion of plastic (LPBF-P), 32, 36, 39, 180–182, 189, 778 Laser-based powder-bed fusion of polymer (L-PBF-P), 61, 918, 919 Laser-based powder-blown DED, 462, 471 Laser-based process, 844 Laser-based wire-fed DED, 464–468 Laser-beam heat source models, 218 Laser beams, 391 Laser chemical vapor deposition (LCVD), 11 Laser cladding, 11, 21 LaserCUSING, 9 Laser DED, 825 Laser energy sources, 432 Laser engineered net-shaping (LENS), 11, 426, 459, 460, 760 Laser-induced forward transfer system, 947 Laser metal deposition (LMD), 11, 460 Laser metal fusion (LMF), 9 Laser micromachining, 848 Laser polishing, 828, 848 Laser powder bed fusion, 391 Laser powder bed fusion additive manufacturing (L-PBF AM), 641 Laser remelting, 828 Laser scanner, 254, 257, 258 Laser scan process, 753 Laser shock peening (LSP), 827, 828 Laser sintering (LS), 586 Laser welding, 10, 464 Laser with powder deposition, 460 Latent heat, 217 Lattice, 611 Lattice density distribution, 294–296, 299 Lattice structure, 294, 297, 298 Lattice topology optimization, 279 Lattice unit cell, 293, 297 Layer-by-layer appearance, 840–841 Layer-by-layer manufacturing approach, 607 Layer-by-layer process, 178, 179 Layer realization, 435 Layers’ adhesion, 803 Layer-specific cross-sections, 115 Layer spreading, 448 LENS 3D printer system, 459 Level set method (LSM), 278 Life cycle analysis (LCA), 32, 40 Life cycle assessment (LCA), 117, 540, 544 Life cycle cost analysis (LCC), 32, 40 Lifshitz, Slyozov and Wagner (LSW) theory, 666 Light-emitting diode (LED), 6 Light optical microscope (LOM), 646, 648 Light scattering, 352, 353 Lights off factory, 889 Lightweight, 200–202 aircraft components, 882 design, 58 Limited market segment, 109 Linear friction welding (LFW), 821 Linear heat input, 461 Linear weld density, 410 Line heat source, 215 Liquation cracking, 661 Liquefier, 214, 218, 219 Liquid crystal display (LCD), 356 Liquid deposition modelling (LDM), 16 Liquid phase sintering, 450

Index Liquid plastic, 4 Load-bearing structures, 57 Logistics management, 74 Long-term implementation success, 60 Lost-wax casting process, 957 Lot size one, 116 Low-cost online business model, 44 Low earth orbit (LEO), 919 Low Force Stereolithography (LFS), 6 Luminaries, 955 Luxexcel, 13

M Machine, 31–33, 35–37, 39, 40, 59, 241, 908 adaptability, 447 cleaning, 908 components, 241 cost, 35 maintenance, 241 manufacturer, 714 Machine learning (ML), 202, 204, 888 in-situ monitoring, 810 principle, 809 process optimization and defects prediction, 810 Machinery directive (MD), 104 Machinery regulation, 104 Machining and mechanical conversion, 826 Macroscale approach, 210 Macroscopic isotropy, 635 Magnetic particle inspection (MPI), 829 Magnetic resonance imaging (MRI), 258 Magneto-hydro-dynamic actuator, 374 Maintenance repair and overhaul (MRO), 80 Major design change, 203, 204 Makerbot subsidiary, 49 “Making” and “repairing”, 3D printing, 93, 95, 97 Malicious insiders, 312 Manipulability, 924 Manual arc-based DED technique, 10 Manual restoration, 924 Manufacturing costs, 919 Manufacturing-driven design strategy, 203 Manufacturing engineer, 885 Manufacturing process, 178, 184, 185, 199–201, 203, 205, 908 ManuFUTURE approach, 170, 171 challenge, 170 education, 171–173 EIT Manufacturing, 163, 164 environmental impact, 164, 165 Europe’s manufacturing industry, 163 industrial transformation, 163, 164 international competition, 164, 165 manufacturing industry acts, 170 objective, 170 research and innovation priority domains, 168, 170 science and technology challenges, 166–168 strategy and building blocks, 165, 166 training, 171–173 Maraging steel (MS1) heat treatment conditions, 754 heat treatment properties, 753 temperature-dependent phase transformations, 754 XRD, 754 Marangoni convection, 220

Index Market awareness and exuberance, 45 Market support, 60 Mask, 543 Mass customization, 81 Mass manufacturing, 81 Matching algorithms, 262 Material extrusion (MEX) method, 4, 5, 178–183, 186, 188, 189, 195, 211, 265, 549, 550, 560, 561, 572–575, 836, 918 acceleration and deceleration, 338 additive manufacturing (AM) techniques, 335 AKF, 17 AM process, 337 applications, 344 bonding, 337, 339, 340 categories, 336, 341 CEM, 17 commercial timeline, 16, 17 composite fabrication, 342, 343 cost and maintenance, 342 cross-sectional image, 338 derivatives, 15 direct ink writing technique, 336 extrusion flow, 335, 338 FEF, 16 FFF, 16 history, 15 HME technique, 341 inks, 341 LDM, 16 limited material, 344 liquification, 337, 338 MakerBot, 16 material preparation and loading, 337 micropenning system, 17 meso and micro structure fabrication, 17 MLS, 16 motion control, 338, 339 multi-material printing, 342, 343 Newtonian behavior of fluids, 338 path planning, 338, 339 pressure, 337 printer, 16 print speed, 343, 344 quality, 336, 343 SDM, 17 semi-liquid gel-like material, 341 semi-liquid material, 338 slurries, 342 solidification, 336, 337, 339, 340 support generation and post-processing, 340, 341 thermoplastics, 16, 341, 342 2D cross-sections, 335 volumetric flow rate, 338 Material jetting (MJ), 178, 181, 195, 551, 837 additive manufacturing (AM), 371 advantage, 380 aluminium substrate, 378 AM technology, 385 applications, 13, 381 bonding, 377 BPM, 13 characteristics, 385 chronological facts, 14, 15 components, 377 continuous jetting, 372 density, 380

993 deposited material, 372 derivatives, 12 Dimatix printer, 383 discontinuous jetting, 373, 374 DOD MJ technology, 13 drop-on-demand approach, 381 electronics sector, 381, 382 inter-droplet/substrate-droplet interfaces, 378 inter-droplet metallurgical bonding, 378 interfacial temperature, 378 liquid/molten material, 372 manufacturing process, 385 MDS, 15 mechanical characteristics, 378 metallic materials, 377 metals, 374–376 microstructure, 378 MJP, 13 MMJ, 15 multi-functional additive manufacturing, 385 multi-material printing, 13 Object 260 Connex, 384 pharmaceuticals, 383 photopolymers, 12, 15 physical properties, 378 polymer inks, 377 polymer jetting, 385 polymers, 375–377 process, 377 properties, 381 space, 382 structures, 378 technology, 372 temperature, 378 tensile fractography, 380 tensile properties, 378 3D components, 381 3D printing, 371 tissue engineering, 382, 383 Xerox’s Liquid Metal 3D Printer (Magnetojet), 383 Young’s modulus, 381 Materials, 32, 34–38, 40, 59, 897, 899 characteristics and categories for, 322 cost, 35 engineer, 885 extrusion, 549, 550, 836 knowledge, 900 minimalism, 187, 188 properties, 195, 196 recycling, 244 Mathematics, 953, 954 Matrix material, 607 composite, 628 polymer, 628 residual stresses, 628 Measure phase, 786, 790, 791 CTQs, 787 DMAIC, 786, 787 software tools, 786 Measuring device, 254 Mechanical machining processes, 827 Mechanical mixing, 592 Mechanical property, 392, 716, 717 creep, 737 fatigue failure, 737 functional components, 735

994 Mechanical property (cont.) hardness, 738 S-N curve, 737 uniaxial tensile test, 735 Mecuris solution platform, 122 Medical applications acrylic-based photopolymers, 135 AM processes, 135 biologic tissue, 135 biomaterials, 134 bone regeneration, 135 ceramics, 136 classified, 134 cobalt-chromium alloys, 135 components, 134 cranial surgery, 137 dental practices, 135 external medical devices, 134 fibre-reinforced AM, 135 human organ tissues, 135 innovative research, 135 medical-grade 3D printed ceramics, 135 metallic medical devices, 135 metals, 136 physical modelling, 134 3D printed dental devices, 136 3D-printed drugs, 135 Medical device coordination group (MDCG), 110 Medical device regulation (MDR), 109–111 Medical devices, 110 Medical fields, 57 Medical implants, 296 Medical sector, 886 MedTech Europe, 111 Melt compounding, 593 Melting mechanism, 218–220 Melt point, 375 Melt pool, 220–223, 461, 531 Mesh-dependent optimization methods, 281 Mesh model, 260 Mesoscopic approach, 210 Mesostructure, 573 Metal 3D printing, 910, 925 Metal AM process, 910, 912 Metal-based Additive Manufacturing Processes, 875 Metal casting process, 127, 128 Metal cutting mechanic, 871–873, 876 Metal foils, 410, 411, 413 Metal inert gas (MIG) cladding system, 430 Metal injection molding (MIM), 542 Metal ions, 824 Metallic components, 4 Metallic materials, 745, 841–843 Metallographic examinations, 875 Metallurgical investigations, 648 Metallurgy, 538 Metal matrix composite (MMC), 433 Metal powder dust explosion, 560 Metal powders, 548, 560, 870 Metal printers, 954 Metal printing, 516 Metals, significant traces, 542 Metals, 374–376, 680, 684 Methanation exchanger-reactor, 912, 913 Method of moving asymptotes (MMA), 291 Metrology, 803, 804, 829

Index Micro and nano additives, 591 Microcracks, 719, 721 MicroCT, 652 Micro-dosing system (MDS), 15 Micro-droplet deposition methods, 382 Micro-electro-mechanical systems (MEMS), 384 Micro laser sintering (MLS), 8 Micropen writing/micropenning, 17 Micro plus continuous digital light manufacturing (cDLM), 6 Microscopic approach, 210 Microstereolithography (μSLA), 355 Microstructure, 224, 229, 743 Microvoids, 719 Microwave sintering, 451 Mie theory, 728 Milled cleat, 184 Milling, 434, 827 Mini extruder deposition (MED), 610 Minimum order quantity (MOQ), 889 Minor design change, 203, 204 MIT’s BJ process, 19, 20 Mixing, 397 MMA, see Method of moving asymptotes (MMA) MMB Volum-e group, 914, 915 Model based definition (MBD), 254 Modelling and data processing methods, 210, 322–323 Modify for AM (MfAM), 895 Mo effect, 767 Mold industry, 331 Momentum gyroscopes, 918 Monomers, 375 Morphology, 394 MPa vacuum system, 8 Mullite, 600 Multi-beam L-PBF, 677 Multi-biological effects, 275, 276 Multi-criteria decision making, 200 Multidisciplinary team, 896 Multi jet fusion (MJF), 9, 20, 47, 58 MultiJet modelling (MJM), 13 MultiJet-printing (MJP), 13 Multi-layer laser cladding, 11 Multi-material AM, 342–344, 913 Multimaterial fabrication, 366 Multi material jetting (MMJ) system, 15 Multi-material L-PBF, 913 Multimaterial vat switching methods, 366 Multi-material VPP system, 6 Multiphase Jet Solidification (MJS), 16 Multi-Station Multi-Axis HLM (MSMA-HLM), 440 Multivariate Adaptive Regression Splines (MARS), 809 Multi-wire TIG system, 434

N Nano-hydroxyapatite, 943 Nano metal jetting (NMJ), 13 Nanoparticle jetting (NPJ), 13 Nanotechnology Research Center, 542 NASA-STD-6030 specifies AM requirements, 894 National Electrotechnical Committees (NCs), 147 National Institute of Personal Protective Technology (NIOSH), 542 Natural fibers, 632 Nearest neighbor regression (NNR), 809 Near-net-shapes (NNS), 825 Negatively pressured area, 543

Index Neodymium-doped yttrium aluminum garnet (ND:YAG), 8 New circular economy action plan, 109 New consumer agenda of 2021, 108 New product development, 32–34, 39, 40 New qualifications and skills, 863–865 New requirements, 111 Newtonian sintering model, 339 NF EN ISO 17296-2 standard, 965 NFPA 484-2012 Standard, 542 Nickel-based superalloys, 453, 655, 727 AM process and parameters, 658 as-printed microstructure, 665 composition, 656–657 cracking, 661–662 defects, 659 heat treated microstructure and mechanical properties, 665–666 microstructural and mechanical properties, 657–658 porosity, 660 Nickel-Titanium (Ni-Ti) implants, 829 Ni-Mn-based Heusler alloys, 454 9 AM programs, 897 Nitride powders, 605 Non-commercial use, 92 Non-contact-based systems, 256 Non-destructive evaluation (NDE), 896 end quality inspection, 804–805 infrared thermal imaging, 807, 808 post-manufacturing, 804 protocols, 804 RUS, 807, 808 selection and applicability, 804 SEM, 807, 808 tactile/contact measurement, 805–807 ultrasonic inspection, 807 Non-destructive testing (NDT), 640, 650, 829 technician, 885 Non-engineering students, 884 Non-isotropic behavior, 572 Non-metallic materials, 846–848 Non-molten particle arrangements, 325 Non-oxide materials, 602 borides, 602 carbides, 602 carbon, 602 nitrides, 602 Non-planer slicing (curved layer) technique, 824 Non-sparking scoops, 542 Notches, 825 Nucleation, 224 NURBS, 261

O Off-axis system, optical sensors, 479–480 camera, 498 diode and camera, 497, 502–503 optical tomography, 503 Off-process, 478 Off-shopfloor, 477 Ohio State University (OSU), 896 Ohnesorge number, 446 Online configurators, 32 Online marketplaces, 94 On-machine, 478 On-shopfloor, 477 Operational risks, 78

995 Opportunistic design guidelines, 177, 178 Optical-form measurement, 805, 806 Optical microscopy, 730 Optical on-axis sensor systems, 479 camera, 485 diode and camera, 489 inline coherent imaging, 492 low coherence interferometry, 493 low coherence interferometry and camera, 495 photodiode, 483 Optical penetration depth, 215 Optical scan technique, 805, 806 Optical sensors, 805 Optical systems, 257 Optimization part design, 244 problem, 290 of the quality, 237 Optomec DED machine, 11 Optris SN 8029001, 483 Order fulfilment process, 33, 34, 39, 40, 203 Organic polymers, 376 Organizational culture, 60 Original equipment manufacturer (OEM), 32, 33, 63, 154, 861 Orthotics & prosthetics (O&P) products, 122 Oscillation amplitude, 412, 421 OSHA standards, 539 Osteochondral tissue, 943 Out-of-copyright works, 96 Overhang, 181, 185, 187, 188, 193–195 filtering, 293, 294 minimization, 237 Oxidation, 541

P Packaging, 915 box dimensions, 969 custom, 963 e-commerce, 963, 964 foam packaging market, 964 green, 964 indirect application, 964 inner packaging, 971 manufacturers, 964 marketing perspective, 964 multi packaging solutions, 964 personalized, 964 protective, 964 purchasing power, 963 smart, 963 3D printing, 964 Packing bed density, 394 Painer, 94 Part consolidation, 200, 202 Part count reduction, 204 Part finishing techniques, 245 Particle size, 391 Particle size distribution (PSD), 396, 645 Part material and process mechanism, 837–838 Part modification, 237 Partner standards developing organization (PSDO), 149 Part orientation, 186, 236, 237 Part preparation, 237 Part removal, 242–244 Pascal’s principle, 825

996 Passive optical systems, 805 Patent infringement, 95–97 Patent law complex multi-level system, 90 EPC, 90 EU Biotechnology Directive, 90 morality exclusion, 90 patenting 3D printed technologies, 90 patent protection, 91 private and non-commercial use, 92, 93 research and experimental use, 93 spares and repairs, 93 valuable design data protection, 91 Patient-specific medical instruments, 58 Pay-as-you-go basis, 51 Pedals, 909, 910 Pedoscope, 538 Peening, 426 The Pennsylvania State University (PSU), 896 Perfume glass bottle, 914–915 Personal implications, 67 Personalized packaging, 964 Personal protective equipment (PPE), 243, 549 Phase field models, 225 Phenix 900 system, 9 Photogrammetry, 255 Photoinitiator, 564, 607 Photoionizers, 605 2-photon polymerization process, 358 Photon sensors, 531 Photopolymerization, 585, 607 Photopolymers, 4, 564, 572, 578–582 17-4 PH stainless steel, 705, 706 Physical and chemical explosion hazards, 561 Physical resolution, 182 Physical supply chain components, 75, 76 definition, 74 upstream and downstream linkages, 75 Piezoelectric actuator, 373 Planetary centrifugal mixer, 614 Plasma rotating electrode process (PREP), 394 Plaster-based 3D Printing (PP), 19 Pneumatic actuator, 373 Point cloud, 260 cleaning, 263, 265 Point heat source, 214 Point matching, 262 Point-Of-Purchase Advertising (POPA), 977 Policy framework, 107 Polishing, 931 Polishing process, 764 Polyamide, 586, 925 Polyamide 11 (PA 11), 576 Polyamide 12 (PA 12), 576 Poly(ε-caprolactone) (PCL), 383 Polycarbonate (PC), 915 PolyJet, 13 Poly lactic acid (PLA), 383, 540 Polymer 3D printers, 896 Polymer 3D printing, 900 Polymer composite, 589 Polymer derived ceramics (PDCs), 603 Polymer filament feedstock, 730 Polymeric carbon precursors, 604 Polymeric diphenylmethane diisocyanates (PMDI), 964

Index Polymeric materials, 571, 592 Polymer infiltration and pyrolysis (PIP), 616 Polymer matrix, 628 Polymer powder consumption, 585 Polymers, 375–377, 548 Polymers designer, 863 Poly(methyl methacrylate) (PMMA), 277, 978 PolyPor C plastic processes, 19 Poly-shape, 909, 910 Polythiophene (PEDOT), 382 Polyurethane, 377 Poly vinyl alcohol (PVA), 383 Poly vinyl chloride (PVC), 17 Porcelainite, 600 Porosity, 244, 325, 396, 399, 757, 760, 800, 801, 803, 812–813 Porous ceramics, 611 Position-based visualization method, 488 Positioning and orientation, 235 Post-print processing, 444 binder burnout, 449–450 curing and depowdering, 449 densification (see Densification) Post processing of AM, 32, 33, 36, 37, 59, 60, 178, 185–187, 191, 192, 254 CAD modelling, 823 CAE simulation, 823 CAM, 823 CNC machining strategy, 823 DED, 821, 822 design workflow, 823 FEA, 823 heat treatment, 825, 826 HIP, 825, 826 implementation, 822 inspection and testing, 827, 829 machining, 823 manufacturers, 822 needs in metal, 841–842 needs in non-metal, 846 PBF, 821, 822 powder removal, 823–825 production workflow, 823 requirements, 329, 895 risks of anisotropic shrinkage and warpage, 823 substrate, 823–825 support structure, 823–825 surface finishing, 826 surface modification, 826 treatments, 435 Post-scan process, 478 Potential hazards, 548, 551–553, 559, 560 Powder agglomerates, 613 Powder bed, 444–449, 451 Powder bed fusion additive manufacturing (PBF AM), 4, 21, 115, 211–213, 220, 242, 305, 389, 394, 516, 550, 551, 560, 564, 575–578, 585, 673, 797–799, 801, 821, 822, 824, 825, 835 advantages, 390 applications, 399, 400 challenges, 400, 401 chronological history, 9, 10 classification, 6 derivatives, 6 on diverse metallic materials, 643 DMP process, 7 EBM, 8, 9 empirical energy density, 642

Index employed techniques, 640 EOS, 7, 8 and E-PBF AM, 641 equipment, 561 fusion mechanism, 641 high density energy beam, 6 HSS, 9 laser and electron beam, 391, 392 LaserCUSING, 9 LMF, 9 L-PBF and EB-PBF, 673 machine parameters, 392 machine manufacturers, 640 metallurgical investigation, 646 part properties and characterization, 398, 399 post-processing techniques, 397, 398 powder characterization, 644 powder parameters, 394–397 process parameters, 642 QC steps, 644 quality control, 640 scanning strategy and process parameters, 643 scan patterns, 677 SHS, 9 SLM, 8 SLS, 7 structural integrity, 641 surface texture characterization, 650 technologies, 6 tensile properties, 647 3D CAD model, 641 Powder bed preheating, 676 Powder-blown deposition, 462 Powder bottles, 541 Powder characteristics, 394 Powder characterization, 644 Powder deposition, 448 Powder metallurgy (PM) AM, 821, 825 Powder morphology, 644 Powder parameters, 392, 394 Powder particle size distribution, 729 Powder production, 394, 761 Powder recycling, 396 Powders, 539, 540 Powder sieving, 244 Powder spreading, 211, 213 Power, 398 Powder feedstock and processing, 722 Precipitation hardening (PH) stainless steels, 705 Preheating, 394 Pre-processing, 260, 611 Pre-scan process, 478 Pressure-assisted infiltration, 450 Pressure drop, 211, 220 Pressure infiltration, 847 Pressureless sintering, 450, 451 Principle of exhaustion, 95 Printer hardware, 76, 77 Printhead, 448 Printing at home, 92 parameters, 391 temperature, 553 PrintSky, 910, 911 Private and non-commercial use exception, 92, 93, 96

997 Private use exception, 91, 92 PRIZM matrix, 275 Proactive detection, 811 Process and performance defects, 329 Process capability analysis, 787, 788 Process chain, 937 costs, 244 Process categories, 548 Process characteristics, 178 Process concentration, 203, 204 Process classification and equipment, 321 Process engineers, 863 Processing biomimetics, 274 Processing materials, 126 Processing parameters, 116, 391, 635, 717 Process monitoring, 647 manufacturing processes, 646 for PBF AM, 646 Process parametrization, 239–241 Process planning, 425 Process qualification, 242, 248 Process signatures melt pool morphology and layer geometry, 520 spatters and vapor plume, 520 temperature of melt pool and build layer, 520 Process simplification, 33 See also Supply chain Process-specific limitations, 236 Process-structure-property relationships, 900 Process window, 392 Product designs, 926, 935–936 Product development, 898 Production, 199–204, 907 technician, 885 scale, efficiency and cost, 327 technologies, 73 tools, 33 Production integrated measurement technologies, 476 levels of integration, 477 modeling, 477 Product liability directive, 108 Product lifecycle, 81 Product Lifecycle Management (PLM), 203, 254 Product-specific regulation, 109 Product value stream map, 38 Professional Development Hours (PDHs), 897 Professional societies, 898, 899 Profitability analysis, 972–974 Project charter, 780 Protection, 95 Protective packaging, 964 Prototyping, 33, 35, 199, 202–204 Prusa, 51 PSPM ball joint, 910 p-value, 790

Q qp-relaxation method, 290 Quad (quadrilateral) mesh, 260 Qualification, 248 Qualifications and/or Competence Units (CU), 861 Quality, 344, 345 bonding, 343, 344 challenges, 838–841

998 Quality (cont.) staircase error, 343, 344 surface roughness, 338, 343 voids, 339 Quality assurance (QA), 516, 857, 862, 870 Quality control (QC), 254, 639, 652 AM parts, 798 KCs, 811 ML (see Machine learning (ML)) PBF AM process, 640 robust qualification and certification, 640 variabilities, 798 Quality criteria, 248 Quality engineer, 884 Quality function deployment (QFD), 204, 780, 784 Quality information framework (QIF), 254 Quality inspection, 254 Quality management system, 241, 246, 248 Quality of AM assessment, 902 consistency–IP and ownership, 901 content–agnostic and unbiased, 901, 902 educational institution, 901 experience–AM and instructors, 901 pedagogy–learner focused, 902 time commitment, 901 value–using AM and ROI, 901 Quenching, 845

R Radiation-based processes, 848 Rafale scaled model, 977, 978 Rail-specific standard, 915 Raindrop packing algorithm, 211 RAMP, see Rational approximation of material properties Random forest network ML, 810 Random packing program flow chart, 212 Rapid product development, 907 Rapid prototyping, 4, 571, 907 Rapid tooling, 967 Rational approximation of material properties (RAMP), 289 Raw materials, 77, 101 Reaction bonded silicon carbide (SiSiC), 602 Reaction bonding, 617 Reactive additive manufacturing (RAM), 581 Reactivity, 543 Readiness, 899, 900 Recital 7 Software Directive, 89 Recoater, 448 Recognition of Prior Learning (RPL), 858 Recoil, 220 Reconditioning, 244 Recyclability, 392, 396 Recyclable raw materials, 970 Recycling, 37, 182 Redesign process for AM, 297 Reducing inventory, 76 Reducing setup, 76 Reducing transport, 76 Reducing waste, 82 Reference system, 262 Reference value, 178, 188, 192–196 Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), 105, 106 Registration process, 262 Regression model, 38, 39

Index Regression tree (RT), 809 Regulations impacting AM machines, 59 ATEX Directive, 105 CLP, 107 ECHA, 106 EMC Directive, 105, 106 European Machinery Directive, 104–105 REACH, 106 relevant regulations, 106 Regulations impacting Products developed with AM conventional technologies, 107 GPSD, 107, 108 MDR, 109–111 product-specific regulation, 109 Reinforced learning (RL) approach, 505 Reinforcement, 340, 342, 592 filler, 341 learning, 202 phase, 628 Reinforcing materials, 548, 630 CF, 632 glass fibers, 632 Kevlar fibers, 632 Reliability, 919 Re-meltings and thermal cycles, 743 Removal of support structures, 244 Replica manufacturing, 615 Replication, 615 Requirements with AM, 200–204 AM-enabled solutions, 894 cost, 895 critical path, 895 de-risk, 895 design for AM, 895 design knowledge, 896 destructive testing, 896 DFM, 895 economical, 895 feasibility, 895 feasible, 895 material(s), 894 MfAM (Modify for AM), 895 multidisciplinary team, 896 non-destructive evaluation , 896 pathfinder, 895 post-processing requirements, 895 product development process, 894 risk, 895 schedule, 895 shapes and geometries, 895 stages of product development, 894 testing and qualification, 896 test specimens, 896 viability, 894, 895 volumetric inspection, 896 witness coupons, 896 Research and development (R&D), 60 Residual build material, 182, 190–192 Residual stress (RS), 210, 214, 649, 675, 677, 761 AM manufacturing technology, 760 DMLS component, 760 LENS, 760 Residual stress management (RSM), 426, 427, 435 in-situ processing, 435 post-processing, 435 pre-processing, 435 Resins, 605, 607

Index Re-skilling, 887 Resolution, 182, 183 Resonant ultrasound spectroscopy (RUS), 807, 808 Restriction of Hazardous Substances Directive, 106 Restrictive design guideline, 178 Reverse engineering (RE), 276 accuracy, 254 acquired point clouds, 266 active methods, 256 AM processes, 254 applications, 254 classification, 255 contact technology, 256, 257 digitization, 255 fields, 255 industrial CT scanning, 258, 259 iterative closest point algorithm, 266 non-contact technology, 257 passive methods, 255, 256 PBF-LB/M process, 266 point cloud, 262, 263, 265 quality control, 265 re-design, 254 scanners, 255 statistical data, 265 STL format, 261 thermoplastic materials, 266 3D CAD nominal model, 266 3D scanning application, 254, 259, 260 2D deviation analysis, 265 Revolving or rotating drum, 395 Rheometer, 395, 645 Risk assessment, 79, 104, 544 Risk identification, 79 Risk mitigation, 79 Risk monitoring, 79 Risks, 538 Robocasting, 15, 17 Robotic dispensing systems, 945–947 Robotics, 882, 888 Robustness, 918 Rockwell hardness, 738 Rofin fiber laser, 495 Root Cause Corrective Action (RCCA), 539 Rotating drum, 396 Rotation speed, 614 RUAG Space Switzerland Nyon (RSSN), 918

S Sabotage, 305, 309, 310 SAC/TC 562 committee, 150, 155 Sacrificial bridges, 919 Safety, 539, 564 management methods, 560–561 manager, 884 working environment, 545 Sand, 452 casting, 331 Scaffolds, 941 AM techniques for 3D constructs fabrication, 944–948 biocompatibility and biodegradability, 942 manufacturing process, 943–944 mechanical and topological properties, 943

999 Scanning, 393 DLP, 359, 360, 362 parameters, 393, 394 Scanning electron microscopy (SEM), 630, 802, 807, 808 Scan speeds, 391, 399 Schlieren imaging, 526–528 Sciaky’s EBAM technique, 11 SCIP database, 106 Screening, 200, 201, 204 Sculpture, 953–956 2nd order benefits, 118 SECO tools, 976 Sector-specific skillsets, 884 Segmentation, 260 Segment model, 3 Selection criteria, 201, 205 Selective deposition lamination (SDL), 17 Selective heat sintering (SHS), 9 Selective lamination composite object manufacturing (SLCOM), 18 Selective laser melting (SLM), 6, 8, 390, 609, 329, 700, 728 AB and HT1, 702 AISI 420, 707 and EBM process, 700 gas atomization, 706 materials, 700 mechanical properties, 704 performance, 706 process parameters, 704 and TEM analyses, 702 YS/UTS ratios, 704 Selective laser sintering (SLS), 6, 122, 390, 426, 586, 589, 591, 609, 925 advantages, 586 commercial thermoplastic polymers, 586, 587 dry mixing method, 592 general SLS process, 586 melt compounding, 593 PBF process, 586 polymer composites, 586–591 polymeric materials, 592 solution-based methods, 592–593 thermoplastic polymers, 586 Selective powder deposition, 913 Semi-automatic or fully automatic units, 967 Semi-ellipsoidal power distribution, 216 Sensing signals and instruments experimental setup and detection parameters, 520 IR imaging, 519 thermal measurement with point detectors, 519 visible-light imaging, 517, 518 Sensitivity analysis, 291, 293, 294, 299 Sensitivity filtering, 291 Sensors, 517 Serial productions with AM automation, 917–918 flow measuring probes, 919–920 SRAs, 918, 919 Servitization, 68 Shape complexity/weight, 969 Shape deposition manufacturing (SDM), 17, 426 Shaped metal deposition (SMD), 460 Shape from shading, 256 Shape from silhouettes, 256 Shape optimization, 278 Shape retention, 339, 342

1000 Sharing of CAD files, 92 Shear forces, 613 Sheet lamination (SL), 5, 178–183, 185–191, 193–195, 551, 837–838 CAM-LEM, 18 carbon fiber sheets, 18 commercial timeline, 18, 19 derivatives, 17 EWI, 17 LOM, 17 PSL, 17 SDL, 17 SLCOM, 18 types of, 408–415 UC, 17 Shock resistance, 964 Shoe Fluoroscope, 538 Shortlist, 199, 200, 204, 205 Short wave infrared (SWIR) thermal camera, 503 Shot peening, 245, 827 Shrinkage, 615, 800 Sieve analysis process, 728 Silica (SiO2), 598, 600 Silicon carbide (SiC), 598, 602, 603 Silicon carbonitride (Si3N4C), 603 Silicon dioxide (SiO2), 600 Silicon nitride (Si3N4), 598, 605 Silicon oxycarbide (SiOC), 603 SIMP, see Solid isotropic material with penalization (SIMP) method Simple shapes, 825 Single pass jetting (SPJ) technology, 20 Singular value decomposition (SVD), 263 Sintering, 450, 600, 607, 614, 615, 845, 847 Six sigma, 778, 780 Skills-based matrix, 888 Skills based training AM, 886, 887 curriculum, 886 different populations, 888 framework, 887, 888 matrix, 887 Skills intensive technology, 887 Skills priorities, 860 Skills strategy in additive manufacturing (SAM) project, 858–860, 863 Skills strategy roadmap, 860, 884 Skin contact, 542 Slicing, 238, 239, 870 Slicing approaches, 431 Slip ring assemblies (SRAs), 918, 919 SLM 316L austenitic steel, 702 SLM 316L SS samples, 767 SLM 316L stainless steel, 701 Slurry, 608 Slurry homogenisation, 613 Small and medium-sized enterprises (SME), 58, 61–62, 898 Smart packaging, 963, 968, 979 Solar array drive mechanisms (SADMs), 918, 919 Solid concepts and harvest technologies, 45 Solid creation system (SCS), 6 Solid freeform fabrication, 4 Solid ground curing (SGC), 6, 426 Solidification, 223–229, 337, 341, 683, 687, 714, 716 bonding, 337, 339, 340 cellular automata, 227–229 chemical reaction, 339 contact surface, 339

Index cracking, 661 nucleation, 224 parameters, 224 phase field models, 225 temperature, 339, 340 Solid isotropic material with penalization (SIMP) method, 278, 279, 288–290, 292, 294, 299 Solido 3D printers, 17 Solid object ultraviolet plotter (SOUP), 6 SolidScape, 426 Solidscape’s wax printers, 13 Solid state sintering, 450 Solution-based methods, 592 Solution heat treatment (SHT), 743 Sonic layer machine suite, 17 Sonotrode, 410–412 Spare part, 199, 200 Spark plasma sintering (SPS), 139 Spatially resolved acoustic spectroscopy (SRAS), 504 Specification, 200, 201 Spectral-domain optical coherence tomography (SD-OCT) method, 494 Spectroscopy, 766 Spot Size, 393 Spreadability, 395, 396 Stainless steel, 700, 768, 913 Staircase effect, 178, 179, 237, 244, 329, 800 Staircase error, 343, 344 Stakeholders, 32, 33, 39, 40, 860, 889 Stand-alone graduate certificates, 897 Standardization, 539 Standards, AM advantages, 146 aerospace-specific, 159, 160 ASTM F42 committee, 147–149, 152–154 ASTM standards and specifications, 156 AWS D20 committee, 150 CEN/TC 438 committee, 149, 150 certification, 146, 148, 154 factors, 154 GB/T standards, 159 industrial concepts, 145 industry, 151, 156 ISO/IEC directives, 146 ISO/TC 261 committee, 148, 149, 152–154 ISO standards, 157 non-industry specific standards, 154 purchase specifications, 154 qualification, 146 regulation, 146, 147, 154 requirements, 154, 157 SAC/TC 562 committee, 150, 155 standardization bodies, 147 supply chain, 146, 158 types of rules, 146, 147 Standards development organizations (SDOs), 898, 899 Statistical analysis, 790 Steels, 452 Stefan-Boltzmann law, 217 Stereolithography (SLA), 4, 5, 21, 46, 121, 139, 343, 350, 351, 353–355, 358–362, 365, 549, 607, 640, 821, 882, 947–948 STL/AMF/3MF file, 74, 178, 235, 260, 261, 292, 908, 969 Strain-age cracking, 662 Strapped inner packaging, 973 Strata, 965 Stratasys, 13

Index acquisitions, 45 AM, 45 company’s initial business model, 45 direct service bureau, RedEye, 45 expertise, 45 FDM technique, 45 in-office prototyping, 46 Makerbot retail stores, 45 market leader, 45 operation fields, 45 segments, 45 3D modeler, 45 3D printing, 45 Stratasys’s FDM patent, 16 STRatoconception Additive TechnOlogy (STRATO), 965 Stratoconception ®, 18, 978 benefits and limitation, 966, 967 defined, 965 liquids, 965 machine characteristics, 967 post-processing, 966 powders, 965 principle, 965, 966 solids, 965 usable materials, 965, 966 uses, 966, 967 StratoTop ®, 965 Stress, 180, 181, 188, 193 Stress constraints, 290, 295 Stress corrosion cracking (SCC), 747, 828 Structure-borne acoustic emission (SBAE), 503 Structured light scanners, 254, 257 Structured light (SL) scanning, 258 SubD (subdivision) modelling, 261 Substances of very high concern (SVHCs), 106 Sub-surface porosity, 703 Subtractive Manufacturing (SM), 425 Superluminescent diode (SLD) based ICI system, 493 Supervised learning, 202 Supervisor, 868, 871–873, 876 Supplier, input, process, output, and customer (SIPOC), 781 Supply chain, 33, 40, 200, 201, 203 Supply chain management (SCM), 74 AM impact, 74, 76, 81–83 elements, 81 Supply chain risk management classification, 78 definition, 77, 78 digitalization, 79 disciplines, 79 origin, 78 research community, 78 risk management concept, 78 Supporting structures, 181, 183, 187, 188, 191, 193, 195, 237, 277, 397 removal, 244 Support mechanism, 430 Support vector machine (SVM), 809 Surface, 803 adaptation, 260 driven process, 541 engineering, 826 film nature, 761 finishing, 395, 826 heat source model, 215 modification, 826–829 patches, 253, 260

1001 porosity, 660 quality, 245, 328–329 roughness, 244, 338, 344, 760, 827, 828 scanning, 57 texture characterization, 649 topography, 827 Surfactant-facilitated latex, 592 Sustainability, 108, 109 Sustainable development (SD), 540, 544 Swainson’s computer, 4 Swelling, 800

T Tabletop gaming, 958, 959 Tactile measurement system, 805–807 Tafel polarization curves, 765 Tangible accessibility, 924 Target costing, 204 Targets, 262 TBGA AM readiness model, 900, 901 Technical challenges, 516 Technical manager, 884 Technical elective courses, 884 Technical product designer, 871, 873 Technology companies, 50 Technology expert business model, 44 Technology push approach, 60 Technology readiness level (TRL), 478 Temisth, 911 Temperature gradient mechanism, 180 Tempering, 845 Tensile properties, 648, 692, 693, 746 Tensile tests, 875 Tesselated model, 253 Test artefacts (TA), 808, 809 Texture, 803 β-textures, 681 Theft of technical data, 310 Theory of inventive problem solving (TRIZ), 275 Thermal applications, 137–139 Thermal (bubble jet) actuator, 373 Thermal cycles, 684 Thermal deformation, 297–299 Thermal energy density (TED), 510 Thermal energy Planck (TEP), 510 Thermal gradients, 181, 467, 675, 679 Thermal parameters, 394 Thermal processes, 826, 845, 847 Thermal sensing, laser AM processes, 519 Thermal spray, 542 Thermal treatment, 610, 845 Thermography system, 500 Thermogravitational analysis (TGA), 449 ThermoJet solid object printing, 13 Thermo-mechanical analysis, 297, 298 Thermoplastics, 341, 342, 571, 572, 579, 628 ABS, 342 advantage, 572 composites, 629 for material extrusion, 573–575, 579 polymers, 377, 586, 629 for powder bed fusion, 575–578, 580, 581 Thermoset polymers, 571, 572, 581, 583, 628 Thermosets, 581, 583 Thin-walled conformal cooling, 64

1002 3D-as-a-service subscription business model, 47 3D cutting, 976 3D file, 969 3D models, 547 3D object, 896 3D packaging, 967, 968, 978 3D printed devices, 110, 111 3D printed product life cycle analysis, 111 3D printed related inventions, 96 3D printers, 4, 104 3D printing, 126, 127, 305, 896, 897 and accessibility, 958 art (see Arts) bureau service, 97 cable guides, 915, 916 castable resin, 958 chainmail fabrics, 957 color, 954, 955 and digital sculpture, 953 emergence, 88 engineer, 886 entire prosthetics, 956, 958 fashion design, 956 guitars, 959 human mind, 953 jewelry, 957, 958 Lund’s Domkyrkan cathedral, 956 mathematically, 954 print quality, 955 and scanning, 956 Scarab ST guitar, 959 service bureau, 96 software, 886 3D scanning, 21, 253, 955 3D solid model, 896 3D systems, 957 acquisitions, 46 AM, 46 collaborations, 46 digital platform, 46 non-hardware revenue stream, 46 rapid prototyping, 46 revenue streams, 46 SLA, 46 technology demonstrations, 46 3D printing, 45 3D systems thermojet platform, 13 3D manufacturing format (3MF), 261 3D metal printing, 910, 914 Three-dimensional data sets, 57 Three-dimensional (3D) shape acquisition systems, 253 Three-dimensional (3D) TO, 292 Three-dimensional printing (3DP), 19 Three-dimensional shaking mixer, 613 316L SS alloy, 756 Three-Roll Mill machine, 613 Thyssen Laser-Technik TCS pyrometer, 497 Ti–5Al–5Mo–5V–3Cr alloy, 686 Ti6Al4V alloy, 677, 679, 682, 684, 688, 743, 745, 761, 768 Time of flight (ToF) sensors, 257 Tissue engineering, 382, 383, 941 inkjet printing, 945 laser-induced forward transfer, 947 robotic dispensing systems, 945–947 stereolithography, 947–948 Titania, 601

Index Titanium aluminide (TiAl) powder, 821 Titanium carbide (TiC), 603 Titanium diboride (TiB2), 606 Titanium dioxide (TiO2), 601 Titanium nitride (TiN), 605 Titanium powders, 539 Titanium (Ti) alloys, 57, 671, 684, 719, 755 AM, 672, 673, 693 components, 672 composition, 675 DED and L-PBF, 691 factors, 675 parameters, 674 PBF and DED, 672 properties, 672 Ti6Al4V, 671 Tolerances, 189–191 Tool-less manufacturing, 115 Tool path, 239 Topography, 803 Topology optimization (TO), 200, 276–283 density function and target problem, 289 design variable update, 290 filtering, 291 heat exchangers, 296 industrial and medical parts, 295 lattice density distribution optimization, 294 lattice unit cell, 296 optimization problem, 290 original concept, 288 RAMP method, 289 SIMP method, 288 STL generation from density distribution, 292 support in AM processes, 292 thermal deformation, 298 Trade-off methodology matrix, 200 Trade related aspects of intellectual property (TRIPS), 89 Traditional 2D printer business model, 47 Traditional flexible technology, 81 Traditional manufacturing processes, 73, 74 Traditional supply chain, 74 Training courses, 898 Training guidelines, 862 Transfer phenomena and fluid flow analysis, 220 Transmission electron microscopy (TEM), 735 Triangular mesh, 261 Triangulation method laser scanning, 258 scanning devices, 257 structured light (SL) scanning, 258 Tricalcium phosphate (TCP), 947 TruPrint machine, 510 Tungsten carbide (WC), 598, 603 Turbine entry temperature (TET), 655 Turbocharger, 974 2D detectors, 519 2D digital cutting machines, 969 Two-photon polymerization (2PP), 5 Two-wavelength pyrometer, 483

U UK Intellectual Property Office (UKIPO), 88 UL/ANSI 2904 standard method, 540 UL3400, 542 Ultimaker, 50–52

Index Ultrafine particles (UFPs), 540, 553, 560, 562 Ultra-high definition (UHD), 356 Ultra-high speed micro-milling (UHSM) machines, 969 Ultra-precision accuracy, 245 Ultrasonic additive manufacturing (UAM), 17, 320 challenges for future research, 413–415 defects, mechanical properties and microstructure, 410–411 description, 409–411 process parameters, 412–413 Ultrasonic bath, 846 Ultrasonic cleaning, 848 Ultrasonic consolidation (UC), 17, 837 Ultrasonic inspection, 807 Ultrasonic nano-crystal surface modification (UNSM), 828, 829 Ultrasonic shot forging (UPT) method, 761 Ultrasonic testing (UT), 807, 829 Ultrasonic transducers, 504 Ultrasonic vibration-assisted powder deposition, 448 Ultrasonic welding, 837–838 Ultraviolet radiation, 564 Umbrella organizations, 858 Underwriters laboratory (UL), 898 Uniaxial tensile test, 735 Unidirectional fiber composites, 634 Unidirectional/multidirectional woven composites, 18 The University of Maryland (UMD), 896 University of Texas at El Paso (UTEP), 897 Un-melted powder, 954 Unsupervised learning, 202 Unsupervised ML, 810 US Food and Drug Administration (FDA), 57 U.S. Universities, 898

V Vacuum-assisted infiltration, 450 Vacuum cleaners, 542 Value capture, 44 Value chain, 101 Value cluster, 33–34, 40, 202–205 Value creation, 44, 918 Value-driven identification process, 205 Value network, 44, 52 Value proposition, 44 Vapor depression region forms, 718 Vaporization, 215 Vat photopolymerization (VPP), 4, 36, 178, 180, 187, 549, 550, 564, 834 additive manufacturing (AM) technologies, 349 chronological history, 7 CLIP, 6 commercialized versions, 6 cross-generational, 365, 366 definition, 5 derivatives, 5 development, 6 DPP, 6 energy dosage, 351 history, 5 hybrid scanning DLP, 358–360 light scattering, 352, 353 liquid photosensitive resin, 351 multimaterial, 365, 366 patent rights, 5 printers, 6

1003 SGC, 6 SLA, 5 3D printing, 349 Vectoflow GmbH, 919 Vertical machining centre (VMC), 428 Vibration isolation, 964 Vibratory bowl feeders, 917–918 Virtual supply chain CAD model files, 78 competitiveness, 74 conceptual model, 75 cybersecurity risks, 78 definition, 74 design files, 78 value adding processes, 74 web-enabled capabilities, 74 Virtual 3D models, 4 Viscosity, 607 Visible-light and thermal sensors, 517 commercial systems, 522, 523 geometric accuracy, 521 microstructures, 521 process signatures from sensing signals (see Process signatures) sensing instruments (see Sensing signals and instruments) structural defects, 522 Visible-light cameras, 517 Visible-light imaging, 517, 518, 520 Visual inspection, 829 Vitreous carbon, 604 Vocational education and training (VET), 858 CLLAIM, 871 design and pre-process, 872–874 dual programmes, 868 educational offers, 871, 872 evaluation, 876 in-process, 873, 875 methodology, 872 post-process, 875–876 Voice of customer (VOC), 782 Voids, 339, 411, 412, 419, 838 Volatile organic compounds (VOCs), 540, 553, 560, 562–564 Volta potential difference, 762 Volumetric DLP (VDLP), 350, 351, 364, 365 Volumetric heat source, 215 Volumetric inspection, 896 VormVrij’s LUTUM V4 ceramic printer, 16 Voxel-based BJ process, 20 Voxeljet, 9, 19

W Wall thickness, 192, 193 Warm isostatic pressing, 847 Warpage, 180, 181, 186–189, 191, 824 Warping, 210, 800 Waste electrical & electronic equipment directive, 106 Waste framework directive 2008/98/EC, 106 Wearable arts, 956–958 Weber number, 446 Weld spatters, 244 Weta Workshop, 958 Wire arc additive manufacturing (WAAM), 64, 131, 460, 466 Wire-based AM processes, 868 Wire-based directed energy deposition, 223

1004 Wire cladding, 431 Wire feed, 460 Wire filling, 931 Workflow, 884–886 Workforce, 883, 886 World copyright treaty (WCT), 89 World rallycross championship (WRX), 910 World standards cooperation (WSC), 147

X XML framework, 254 X-ray computed tomography (XCT), 734, 803–805, 829 X-ray diffraction (XRD), 733 X-ray imaging, 734 X-ray micro-computed tomography (μCT), 380, 528, 529

Index Y Young’s modulus, 701, 736 Ytterbium fiber laser, 486 Yttrium Aluminum Garnet (YAG), 9

Z Z Corporation (Z Corp), 19, 954 Zeolites, 602 Zirconia, 598, 601 Zirconium carbide (ZrC), 603 Zirconium diboride (ZiB2), 598, 606 Zirconium dioxide (ZrO2), 601 Zirconium orthosilicate, 602 Zirconium silicate (ZrSiO4), 602 The Zoybar, 959