Ergonomics for Improved Productivity: Proceedings of HWWE 2017 (Design Science and Innovation) 9811590532, 9789811590535
This highly informative and carefully presented book focuses on the fields of ergonomics/human factors and discusses the
131 11 29MB
English Pages 1057 [996] Year 2021
Contents
Editors and Contributors
About the Editors
Contributors
Satyan Steering Gear
1 Introduction
2 Basic Mechanical Steering Gear in Use at Present
3 Application of FECG on Roads Straight and Curved
4 Satyan Steering Gear
5 Theoretical Analysis of the Mechanism
6 Performance of Satyan Steering Gear
7 Discussion
8 Conclusion
Appendix
References
Enhancing Walking Stability of Foot Deformities Patients by 3D-Printed Ankle Foot Orthosis
1 Introduction
1.1 The Right AFO for Every Patient
1.2 Gait Data Reference System
1.3 Additive/Rapid Prototype Technology
2 Methodology
2.1 Manufacturing Techniques of AFO
2.2 Gait Analysis of Foot Drop Patients
3 Results and Discussion:
References
Analyzing the Important Factors Causing Fatigue in Industrial Workers Using Fuzzy MCDM Technique
1 Introduction
2 Fuzzy DEMATEL Method
3 Results and Discussion
4 Conclusions
References
Prioritizing the TQM Enablers in HCEs for Improved Performance: An AHP Approach
1 Introduction
2 Literature Review
2.1 TQM in HCEs
2.2 Identification of Enablers Categories and TQM Enablers in HCEs
3 Research Methodology
3.1 AHP Background
3.2 Prioritization of TQM Enablers in HCEs
4 Discussion
5 Conclusion
References
Development of Bottom-Wear Size Chart for Indian Male Youth
1 Introduction
1.1 Subject
1.2 Body Dimensions
1.3 Procedure and Equipment
2 Results and Discussion
2.1 Data Preparation and Initial Analysis
2.2 Sizing Analysis
3 Development of Size Charts
4 Validation of Size Charts
5 Comparative Analysis of the Size Charts Developed
6 Conclusion
References
Occupational Health Hazard of Workers Engaged in Food Processing Unit of Assam
1 Introduction
2 Methodology
2.1 Selection of Sample
2.2 Data Collection
3 Results and Discussion
3.1 Workers in Fruit Processing Industries Activities
3.2 Prevalence of Ergonomic Risk Factors
3.3 Work-Related Health Problem/Musculoskeletal Problem Faced
3.4 The Design Development
4 Conclusion
References
Ergonomic Evaluation of a Car Interior: A Case Example on Shelby Cobra
1 Introduction
2 Methods
2.1 Design of Car Interior of Shelby Cobra Working Model
2.2 Questionnaire Survey and Observational Study
3 Results and Discussion
3.1 Driver Experience for the Interior of the Shelby Cobra Model
4 Conclusion
References
Ergonomic Risk Assessment and Postural Analysis of Indian Agricultural Workers
1 Introduction
2 Methodology
2.1 Subjects
2.2 Work Schedule
2.3 Questionnaire Survey
2.4 Working Posture
2.5 Statistical Analysis of Existing Tool
2.6 Statistical Analysis of Modified Tool
3 Results and Discussion
4 Conclusions
References
Ergonomics in the Kitchen of Working Women of MIG Families (A Study of Aligarh City)
1 Introduction
1.1 Significance of the Study
1.2 Objectives of the Study
2 Methodology
3 Result and Discussion
3.1 Personal Profile of Respondent and Its Correlation with Fatigue and Various Pains
3.2 Kitchen Arrangement and Its Correlation with Fatigue and Various Pains
3.3 Kitchen Practices Followed by Women and Its Correlation with Fatigue and Various Pains
3.4 Kitchen Laws Followed by the Women
4 Conclusion
References
Physical Effects on an Assembly of Modeled Teeth and Mandible Using Finite Element Analysis
1 Introduction
2 Procedure
3 Result
4 Future Prospect
References
A Case for Re-Examining Office Furniture Norms in India
1 Introduction
2 Discussion
2.1 Comfort and Well-Being
2.2 Sit/Stand Workstations
2.3 Office Work
2.4 Limited Typing Ability
2.5 Presbyopia
2.6 Comfort and Well-Being
3 Conclusion
References
Advergames Are More Persuasive Among Different Online Advertisements
1 Introduction
2 Literature Review
2.1 Text-Only Ads and Text Plus Photograph Ads
2.2 Advergames
2.3 Enjoyment
2.4 Engagement
2.5 Persuasion
3 Hypotheses
4 Methodology
4.1 Experiment
4.2 Participants
4.3 Measures
4.4 Stimuli Material
5 Results
6 Implications and Limitations
References
Analysis of the Critical Factors for Integration of Sustainability with Lean Practices for Indian Manufacturing Enterprises
1 Introduction
2 Factors Affecting Integration of Sustainability with Lean Practices
3 Methodology
3.1 Interpretative Structural Modeling (ISM)
3.2 MICMAC Analysis
4 Major Contribution
5 Future Scope
6 Conclusion
References
Enhancing Human Productivity in Stress-Oriented Jobs: A Proposed Model
1 Introduction
2 Literature Review
3 Methodology
4 Result and Discussion
5 Conclusions
5.1 Proposed Recommendations
6 Future Scope
References
Effect of Noise-Induced Stress on Bus Drivers of Faridabad (India)
1 Introduction
2 Subjects and Method
3 Result and Discussion
4 Conclusion
Appendix-A
References
Ergonomic Study on Foundry Workers
1 Introduction
2 Methodology
2.1 Worker Selection and Data Collection
2.2 Dimensions and Instrument Used
2.3 Statistical Analysis
3 Result and Discussion
4 Conclusion
References
Modernizing Ergonomics Through Additive Manufacturing Technology
1 Introduction
1.1 Linking AM Technology Features with Ergonomics
2 Need of the Study
3 Potential Use of AM Technology in Ergonomics
3.1 Cost
3.2 Material Flexibility
3.3 Customization
3.4 Rapid Availability
3.5 Weight Reduction
4 Adoption of AM Technology
5 Research Direction and Future Scope
6 Conclusion
References
Factors Affecting Work-Related Musculoskeletal Disorders in Caregiving Staff at Hospitals and Medical Organization
1 Introduction
2 Literature Review
3 Methodology
4 Results
5 Discussions
6 Conclusion
References
Redesigning Agricultural Tools Using Anthropometry of Male Agricultural Workers of Dayalbagh Region, Agra, India
1 Introduction
2 Methods
2.1 Subjects
2.2 Body Dimensions
2.3 Equipment Used
3 Results
4 Discussion
4.1 Redesigning Grip Diameter for Hand Tools like Sickle, Spade, and Khurpi
4.2 Redesigning Weeder Handle Height by Considering Anthropometric Data of This Region
4.3 Redesigning Thresher With Ergonomic Considerations
5 Conclusion
References
Effect of Environmental Parameters on Performance and Fatigue of a Worker Performing a Metal Pouring Operation
1 Introduction
2 Methodology
2.1 Subjects
2.2 Experimental Design
2.3 Experimental Task
3 Results and Discussions
4 Conclusions
References
Design of Land Leveller Height Measuring Physiological and Psychophysical Parameters
1 Introduction
2 Methods
2.1 Subjects
2.2 Experimental Design
2.3 Heart Rate Measurement
2.4 Postural Discomfort Measurement
2.5 Procedure
2.6 Observations
3 Results
4 Discussion
5 Conclusion
References
Integrated Supply Chain Problems and Organizational Ergonomics: An Insight
1 Introduction
2 Methodology Adopted
3 Results and Discussion
4 Conclusion
References
Ergonomic Interventions for Manual Material Handling Tasks in a Warehouse
1 Introduction
2 Methodology
3 Results and Discussion
4 Conclusions
References
Ergonomics in Product Design—Past, Present, and Future: A Review
1 Introduction
2 Ergonomic in Past
2.1 Suitable Tools Design
2.2 The Ergonomic Design of Utensils for Daily Necessities
3 Ergonomics at Present
4 Tendencies for the Future
5 Conclusion
References
A Comparative Analysis of a Mouse and Touchpad Based on Throughput and Locations for a Laptop Computer
1 Introduction
2 Methodology
2.1 Interface Design
2.2 Experimental Setup
2.3 Variables
2.4 Procedure
3 Result
4 Discussion
5 Conclusion and Future Scope
References
Ergonomic Assessment of Chaff Cutting Task
1 Introduction
2 Methodology
2.1 Participants
2.2 Muscle Groups
2.3 Instrumentation
2.4 Design of Experiment
2.5 Procedure
3 Results and Discussion
4 Conclusion and Future Scope
References
Experimental Study of Rate of Heat Release of Sprays in Supercritical Direct Injection Combustion System Using Sensor
1 Introduction
2 Experimental Setup
2.1 Experimental Setup and Description
2.2 Experimental Methodology
2.3 Rate of Heat Release (ROHR) Calculation in Direct-Injection Constant Volume Combustion Chamber
3 Results and Discussions
3.1 Maximum Rate of Heat Release Characteristics
4 Conclusion
References
Analysis of Health Issue and Musculoskeletal Problem for Workers in Manufacturing Sectors
1 Introduction
2 Methods and Materials
2.1 Participants
2.2 Experimental Design and Protocols
3 Results and Discussion
4 Conclusions
References
Analysis of Working Postures Leading to Musculoskeletal Disorders Among Employees in Garment Manufacturing Units—A Case Study
1 Introduction
2 Motivation and Objectives of Applied Research
3 Methodology of Research
3.1 Preliminary Study
3.2 Questionnaire Design and Administration
3.3 Identification and Selection of Postures for Analysis
3.4 Selection of Tools for Analysis
3.5 Selection of Expert System
3.6 Outcomes of the Investigation
4 Recommendation of Ergonomic Interventions and Prescriptions
5 Conclusion and Future Scope of Research
References
Suppressed Articulatory Rehearsal Mechanism, Gaze Behavior, and Direction Following in Distracted Driving
1 Introduction
1.1 ARM of Working Memory
1.2 Eye Movement and Driving
2 Methodology
2.1 Design
2.2 Participants
2.3 Procedure
3 Results
4 Discussion
References
Experimental Study of Ignition and Combustion Characteristics of Dieseline Spray in Supercritical State
1 Introduction
2 Experimental Setup
2.1 Experimental Setup and Description
2.2 Experimental Methodology
3 Results and Discussion
3.1 Ignition Delay
3.2 Duration of Combustion
4 Conclusion
References
Electromyographic Analysis of Low Back Muscles of Occupational Workers: A Review
1 Introduction
2 Electromyography
3 Literature Review
4 Discussion and Conclusion
References
Isometric Push/Pull Strength of Indian Male Participants at Three Handle Heights
1 Introduction
2 Materials and Methods
2.1 Subjects
2.2 Equipment and Procedure
2.3 Data Analysis
3 Results and Discussions
3.1 Push and Pull Strength Models
4 Conclusions
References
Postural Analysis, Occupational Health, and Ergonomic Intervention of Welding Workers in Different Small-Scale Welding Units: A Report
1 Introduction
2 Background
3 CAD Modeling of Human Body
4 Discomfort Formulation
5 Methodology
6 Framework and Flowchart
7 Results
8 Discussion
8.1 Factor Associated with Musculoskeletal Symptoms
8.2 Prevalence of Musculoskeletal Symptoms
8.3 Workstation Design Guidelines
8.4 Application of the Guidelines and Its Evaluation in a Prototype Workstation
9 Conclusion
References
Strength Index of Axle Housing of Pre-ROPS Agricultural Tractors
1 Introduction
2 Review of Literature
3 Design Consideration
3.1 Axle Housing Strength Index
4 Materials and Methods
5 Results and Discussions
5.1 Strength Index of Axle Housing
References
Ergonomic Hazard Identification and Assessment of a Garment Factory in KSA—An Exploratory Study
1 Introduction
2 Methodology
3 Analysis and Discussion
3.1 Survey and Interviews Findings
3.2 Observations and Hazard Identification
4 Conclusion
References
Impact of Exposure to the High Noise Level on Occupational Health of the Weavers Engaged in Handloom Sectors in India: A Case Study from Bargarh District
1 Introduction
2 Methodology
3 Results
3.1 Comparison of Noise Level at Loom Workstations
3.2 Comparison of Resting Heart Rate of the Weavers at Loom Workstations
3.3 Cognitive Workload Analysis
3.4 Analysis of Responses to Questionnaire Constructed for Subjective Evaluation of the Impact of Noise
3.5 Correlation Matrix Month-Wise Versus Question-Wise
4 Discussion
5 Conclusion
References
Evaluation of Agricultural Waste Natural Fiber as an Acoustic Absorber for Reduction of Industrial Noise
1 Introduction
2 Methodology
3 Results and Discussion
4 Conclusion
References
Impact of Heat Stress and Its Impression on Cardiac Jeopardy Among Construction Laborers: A Consequence for a Climate Change Imminent
1 Materials and Methods
2 Results
3 Discussion
4 Conclusions
References
User-Centered System Design for Indian Small-Scale Industries: Case Study on Pottery Industry
1 Introduction
1.1 Related Studies
2 Methodology
2.1 Participants
2.2 Procedure
3 Results
3.1 Proposed Solution
4 Discussion
5 Conclusion
Appendix
References
Space Ergonomics: Analysis of Artificial Gravity Model and an Improved Proposed Model
1 Introduction
2 Literature Review
3 Methodology
3.1 Variable G from Head to Feet
3.2 G Variation in Body Angle Change
3.3 Reducing Stresses and Angular Momentum Change
3.4 Reducing Coriolis Effect
4 An Improved Proposed Model
References
Assessment of Checkout Operator’s Workload in Organized Retail Stores of India
1 Introduction
2 Materials and Methods
2.1 NASA Method
2.2 Application of NASA
3 Results and Discussion
3.1 Demographic Information of Checkout Operators
3.2 Workload Dimensions and the Overall Workload
3.3 Correlation Between Workload Dimensions and Overall Workload
4 Conclusion
References
Ergonomic Evaluation and Work Table Design for Wood Furniture Manufacturing Industry
1 Introduction
2 Methods
2.1 Participants
2.2 Questionnaire
2.3 Posture Analysis
2.4 Designing of Work Table
2.5 Statistical Analysis
3 Results and Discussion
4 Conclusion
References
Technical Intervention for Assessment of Physiological Characteristics as Function of Operating Force in Traditional Agricultural Operations
1 Introduction
2 Materials and Methods
2.1 Experimental Setup and Instruments
2.2 Selection of Subjects
2.3 Data Collection and Analysis
3 Results and Discussion
3.1 Physiological Parameters Recorded During the Operation
3.2 Effect of Exerted Force on Physiological Parameters
4 Conclusion
References
Effect of Vibration Intervention on Forearm Muscles to Improve Grip Strength: A Systematic Review
1 Introduction
2 Methods
2.1 Search Strategy
2.2 Inclusion Criteria
2.3 Exclusion Criteria
3 Results and Discussion
4 Conclusion
References
Relationship Between Grip Strength and Anthropometric Variations—A Systematic Review
1 Introduction
2 Methods
2.1 Search Strategy
2.2 Inclusion Criteria
2.3 Exclusion Criteria
3 Results and Discussion
4 Conclusion
References
Ergonomic Assessment of Work-Related Musculoskeletal Disorders and Comfort of Students in Mechanical Workshop
1 Introduction
2 Materials and Methods
3 Data Analysis
3.1 Percentage Analysis
3.2 Analysis of Musculoskeletal Disorders (MSDs)
3.3 Comfort Level Analysis
4 Results and Discussion
5 Recommendations
6 Conclusion
References
A Comparative Study of Thermal Environment Between Two Varieties of Pantry Car Available in Indian Railway
1 Introduction
2 Research Method
2.1 Study Location and Period
2.2 Participants and Tools
3 Result and Discussion
3.1 Psychometric Chart Analysis
3.2 Statistical Analysis for Comparing Between Both Types of Pantry Car Using Independent Sample Test
4 Conclusions
References
Gender Differences in Sleep Apnea—A Questionnaire Study
1 Introduction
1.1 Risk Factors of Sleep Apnea
2 Methods and Materials
2.1 Participants
2.2 Experimental Design and Protocols
3 Results and Discussion
4 Conclusions
References
Work-Related Musculoskeletal Disorders Among the Metal Craft Workers in Jaipur, India
1 Introduction
2 Materials and Methods
2.1 Sample
2.2 Questionnaire Study
2.3 Evaluation of Working Posture
2.4 Statistical Analysis
3 Result
3.1 General Information of Sample
3.2 Prevalence of WMSDs
3.3 Association of Risk Factors
3.4 RULA Scores
4 Discussion
5 Conclusions
References
Ergonomic Intervention for Drudgery Reduction in Paddy Seed selection—A Post-harvest Activity in Assam
1 Introduction
2 Methodology
2.1 Selection of Subjects
2.2 Physical Characteristics and Body Composition
2.3 Pinch Grip Strength
2.4 Identification on the Incidence of Musculoskeletal Problems
2.5 Identification of Different Body Parts Discomfort
3 Results and Discussion
4 Physical Characteristics and Body Composition
5 An Ergonomic Intervention for Drudgery Reduction of Farm Women in Paddy Seed Selection Activity
6 Ergonomic Evaluation of the Seed Selection Activity with Developed Stripper
7 Pinch Grip Strength of the Farm Women
8 Prevalence of Work-Related Musculoskeletal Disorders (WMSDs) of the Farm Women
9 Body Parts Discomfort (BPD) of Farm Women
10 Significant Benefits to Farm Women
11 Conclusions
References
Classification of Mobile Interactions Based on Human Emotion
1 Introduction
2 Literature Review
2.1 Overview
3 Methodology
3.1 Participants, Sampling, and Procedure
3.2 Questionnaire Design
4 Result
4.1 Result of Phase 1 Study
4.2 Result of Phase 2 Study
5 Discussion
6 Limitations and Future Scope
References
Evaluation of Vibration and Physiological Parameters of Indian Female Workers for Operating a Mini-Combine Harvester
1 Introduction
2 Material and Methods
2.1 Selection of Subjects
2.2 Measurement of Vibration of Mini-Combine Harvester
2.3 Total Vibration
3 Results and Discussion
3.1 Vibration Measurement of Mini-Combine
3.2 Ergonomic Analysis of Mini-Combine Harvester
4 Conclusion
References
Workplace Design Factors, Well-Being and Ergonomics Training—A Case for Indian Millennial Employee
1 Introduction
1.1 Research Problem
1.2 Research Objectives
2 Literature Review
2.1 Well-Being
2.2 Workplace Design Factors
2.3 Ergonomic Training
3 Research Methodology
3.1 Findings and Discussions
3.2 Implications
4 Limitations
References
Leadership Decisions on Workplace Ergonomics: Roadmap to Success
1 Introduction
2 Review of the Literature
3 Purpose of the Study
4 Methodology
5 Results
6 Discussion and Conclusions
7 Recommendations
References
Analysing the Prevalence of Occupational Risk Among Workers Involved in Traditional Clay Brick Manufacturing Tasks
1 Introduction
2 Methodology
3 Observations and Results
4 Posture Analysis
4.1 REBA Score
5 Hand Grip Strength
6 Conclusion and Discussion
References
Ergonomics in the Workplace for a Better Quality of Work Life
1 Introduction
2 Serving Our People: An Employee Centric Approach
3 Changing Workforce Office Design: Blue Work Strategy at American Express
4 Working Smarter with Ergonomics
5 Ergonomics Program at American Express Financial Advisors (AEFA)
6 American Express India
7 Conclusion
References
Ergonomic Evaluation of a CNC Machine Panel Keyboard
1 Introduction
2 Literature Review
3 Discomfort Associated with CNC
4 Problem Formulation
4.1 Process Parameters
4.2 Response Parameters
5 Design of Experiment
6 Result
7 Discussion and Conclusion
8 Future Scope for the Study
Appendix
References
Design and Development of an Automated Hand Shovel
1 Introduction
2 Methodology
2.1 Experimentation
2.2 Results and Analysis
3 Design of an Automated Hand Shovel
3.1 Design of Shovelling Mechanism
3.2 Design of Support Structure
4 Prototype
5 Conclusion
References
Microstructure Evolution in Dissimilar Friction Stir Weld Joints of Precipitation and Solution Hardening Aluminum Alloys
1 Introduction
2 Experimental Details
3 Microstructure
4 Conclusions
References
Design and Evaluation of Wheelchair-Mounted Self-Transfer Assistive Device for Elderly and Patients
1 Introduction
2 Material and Methods
2.1 Design Method Using TRIZ
2.2 Requirements of the Proposed Wheelchair-Based Assistive Device
3 Results and Discussions
4 Conclusions
References
Evaluation of Crew Protection Performance and Ergonomic Design Aspects of a Light Combat Vehicle During Its Conceptualization Stage
1 Introduction
2 Method
3 Result and Discussion
4 Conclusion
References
User-Oriented Subjective Ergonomic Evaluation for Work-Related Disorders: A Review
1 Introduction
2 Method
3 Results and Discussion
3.1 Working Posture and Repeated Activity
3.2 Work Environment
3.3 Demography, Habits, Socioeconomic Status, and Work-life Balance
3.4 Musculoskeletal Disorders (MSDs)
4 Conclusions
References
Effect of Nozzle Tip Distance in Minimum Quantity Coolant-Assisted Turning of Ti-6Al-4V Alloy
1 Introduction
2 Experimental Work
3 Results and Discussion
4 Conclusion
References
Assessment of Bus Driver Performance Based on Reaction Time on Simulator and On-Road Driving
1 Introduction
2 Materials and Methods
2.1 Subject Details
2.2 Driving Simulator
2.3 On-Road Driving
2.4 Statistical Analysis
2.5 Reaction Time Instrument
3 Result
4 Discussions
5 Conclusion
References
Comparative Assessment of Mini-Mental State Examination in Bus Drivers for On-Road and Simulator Study Conditions
1 Introduction
2 Materials and Methods
2.1 Participants
2.2 Experimental Design
3 Results
4 Discussions and Conclusions
References
Reverse Engineering in Customization of Products: Review and Case Study
1 Introduction
2 Review on Reverse Engineering
2.1 Reverse Engineering in Biomedical Application
3 Case Study: Design of Customized Orthopedic Plate
3.1 3D Scan and Post-Processing
3.2 Designing of Custom Implant
3.3 FE Modeling
4 Results and Discussion
5 Conclusion
References
Comparison of Fatigue Trend Among Different Aged Driver on Simulator and On-Road Driving
1 Introduction
2 Materials and Methods
2.1 Subject Details
2.2 Driving Simulator
2.3 Seat Pressure Analysis
3 Result
4 Discussion
5 Conclusion
References
Subjective Evaluation of Musculoskeletal Disorders Among Fatal and Nonfatal Bus Drivers in Different Scenarios
1 Introduction
2 Methods
2.1 Participants
2.2 RBGPS
2.3 Experimental Design
3 Results
4 Discussions and Conclusions
References
A Low-Cost Reaction Time Estimator-Based Hand and Foot Exercises for Stroke Rehabilitation
1 Introduction
2 System Design and Development
2.1 The Arduino Platform
2.2 System Integration
2.3 Reaction Time Calculation
2.4 Procedure
3 Conclusion
References
Real-Time Driver Fatigue Detection from ECG Using Deep Learning Algorithm
1 Introduction
2 Methods and Materials
2.1 Block Diagram
2.2 Heart Rate Variability Features
2.3 Deep Learning to Classify HRV Features
3 Experimental Results
4 Conclusion
References
Training System for Autistic Children Based on Virtual Reality
1 Introduction
2 Literature Review
2.1 Current Rehabilitation Methods
2.2 Rehabilitation Game Design Using Virtual Reality Platform
3 Experiment Set-Up
3.1 Interactive VR Technology Platform
4 Result and Discussion
5 Conclusion
References
Cognitive Assessment of Driver Fatigue Based on Machine Learning Using EEG Signals
1 Introduction
2 Literature Review
2.1 Overview on Existing Fatigue Estimation Methods
2.2 Benefits of EEG-based Fatigue Estimation
3 Experiment Set-up
3.1 Subject Selection
4 Result and Discussion
5 Conclusion
References
Comparative Study of ANN Algorithms for EMG Signals
1 Introduction
2 EMG Signal Acquisition and Processing
3 Artificial Neural Networking
3.1 Feed Forward Backpropagation Network
4 Results and Discussion
5 Conclusion
References
EEG-Based Exoskeleton for Rehabilitation Therapy
1 Introduction
2 Mechatronic Design
2.1 Elbow Support
2.2 Hand Support
2.3 Finger Support
2.4 Fabrication
3 EEG
3.1 Data Acquisition
4 Channel Selection
4.1 Feature Extraction
5 Results and Discussion
6 Conclusion
References
Barriers to Promote Occupational Health and Safety (OHS) Among Different Construction Types in India
1 Introduction
2 Materials and Methods
2.1 Survey on Barriers to Promote OHS Among Different Construction Groups
2.2 Statistical Analysis
3 Analysis of Results
3.1 Respondents Profile
3.2 Barriers to Promote OHS Among Organizations
4 Suggestions/Recommendations
5 Conclusion
References
An Optimized Algorithm for Automatic Seizure Detection in Time Frequency Domain
1 Introduction
2 Database
3 Methodology
3.1 Multi-resolution Analysis Using Dual-Tree Complex Wavelet Transform
3.2 Feature Extraction and Feature Selection Using Mahalanobis Distance and Correlation Coefficient
3.3 K-Fold Cross-Validation and Classification
4 Results and Discussion
5 Conclusion
References
Designing Baffles of Fuel Tanker Truck to Prevent Rollovers
1 Introduction
2 Validation
3 Assumptions in the Analysis
4 Methodology
4.1 Governing Equations
5 Results
6 Conclusions
References
Cockpit Design of a Formula Student Race Car: An Ergonomics Study
1 Introduction
2 Literature Review
2.1 Competition Rules
2.2 Overview of Past Research Study
3 Methodology
3.1 Design of Apparatus
3.2 Data Obtained
4 Results and Discussion
5 Conclusions
References
Design and Development of Semi-Automatic Handloom Incorporating Human Factors
1 Introduction
2 Literature Review
3 Product Review
4 Methodology
5 Conceptual Design
6 Development
7 Conclusion
References
Footwear: Purchase and Impact on Health
1 Introduction
2 Methodology
3 Results and Discussion
4 Discussion
5 Conclusion
References
Ergonomics Study on the Handle Orientation of Shovel
1 Introduction
2 Field Survey
2.1 Participants
2.2 Survey Assessment
2.3 Post-survey Analysis/Results
3 Shovel Design Modification
3.1 Shovel Handle Orientations
3.2 HCAD Modeling
4 Results and Discussions
5 Conclusions
References
Subjective Evaluation of Driver Distraction Caused During Use of Mobile Phone for Navigation Purpose
1 Introduction
2 Methodology
3 Description of the Questionnaire
4 Result
5 Discussion
6 Limitation of the Present Research
References
A Scrutiny of On-Job Stress and Occupational Well-Being of Indian Policewomen Compared to Chinese Policewomen
1 Introduction
2 Methodology
3 Observations and Discussion
3.1 Exposure to Environmental and Occupational Stress and Perceived Well-Being of Policewomen at the Existing Workplace at AWPS Pan Bazar, Guwahati, and Policewomen at Hangzhou, China
3.2 Observations of Survey on-Job Burnout Across Various Police Stations
3.3 Observations Related to on-Job Satisfaction Survey Results Across Police Stations
3.4 Comparative Notes Regarding Satisfaction Index of Policewomen Across the Various Police Stations
4 Conclusion
5 Significance of the Research
References
Knee Arthritis-Related Issues Among Aging Population in Indian Households
1 Introduction
2 Method and Participants
3 Findings
3.1 Arthritis-Related Symptoms Experienced
3.2 Difficult Activities
4 Discussion
5 Conclusion
References
WMSDs Among Workers Engaged in Press Work at Small-Scale Lock Industries: A Case Study
1 Introduction
2 Materials and Methods
2.1 Job Selection
2.2 Survey Technique
3 Results and Discussion
3.1 Worker Statistics
3.2 Perceived Discomfort
4 Conclusions
References
Carpal Tunnel Syndrome Estimation in Shock Absorber Assembly Workforce in Indian Automobile Industry: A Study
1 Introduction
2 Materials and Methods
2.1 Shocker Manufacturing Plant
2.2 Data Collection
3 Result and Discussions
3.1 Indian Automobile Sector
3.2 Shocker Assembly Description
4 Conclusions
References
The Use of Worksheets and Checklists in Imparting Ergonomics Education to Students
1 Introduction
2 Worksheets and Checklists
3 Ergonomics Education
3.1 Rapid Entire Body Assessment (REBA) Worksheet
3.2 Computer Workstation E-Tool
3.3 Checklist for Selecting Non-powered Hand Tools
4 Results
5 Summary
References
Effect of Housing Dimensions and Materials on Human Thermal Comfort in Air-Conditioned Beds
1 Introduction
1.1 Calculations
1.2 Considering Case 1—for Cuboidal Housing Bed
1.3 Considering Case 2—for Cylindrical Housing Bed
2 Results
3 Conclusions
References
Can Dynamic Widgets Improve Data Entry Efficiency?
1 Introduction
2 Literature Study
3 Methodology
3.1 User Study
4 Results and Discussion
5 Conclusion
References
Correlation Between Anthropometry Dimensions and EMG Features During Endurance Task
1 Introduction
2 Method
2.1 Surface EMG Recordings and Analysis
2.2 Participants
2.3 Experimental Protocol
3 Results
3.1 MVC Grip Strength and Endurance Time
3.2 Effect of Anthropometric Variables on EMG Features
4 Discussion
5 Conclusion
References
Industrial Defects Reduction Using Quality Control Tools
1 Introduction
2 Company Background
3 Methodology
4 Results and Discussion
5 Conclusions
References
Design and Analysis of Partial Right Foot Chopart Socket Prosthesis
1 Introduction
2 Manufacturing of Foot Chopart Socket Prosthesis
2.1 Polypropylene Socket Prosthesis
2.2 Carbon Fiber Socket Prosthesis
3 FEA of Foot Chopart Socket Prosthesis
4 Conclusion
References
Implementation of Kansei Engineering to Develop a Framework to Retain Ethnicity of Indian Handloom Products
1 Introduction
2 Kansei Engineering (KE) Approach
3 Application of Kansei Engineering on Handloom Saree
4 Discussion
5 Conclusion
References
Multichannel Feature Extraction for Pattern Recognition of EMG Signals in Time and Frequency Domain
1 Introduction
2 Methods
2.1 Surface EMG Recording
2.2 Participants
2.3 Experimental Protocol
2.4 Feature Extraction
2.5 Feature Classification
3 Results
4 Discussion
5 Conclusion
References
Psychophysical Approach in Manual Material Handling: Review
1 Introduction
2 Method
3 Psychophysical Approach
4 Studies Related to Psychophysical Lifting
5 Conclusion
References
Musculoskeletal Disorders and Visual Symptoms Among Virtual Reality Headset Users
1 Introduction
2 Methodology
2.1 Apparatus Used
2.2 Procedure
3 Results
4 Discussion and Conclusions
5 Future Work
References
Influence of Indian Classical Dancing on the Postural Stability of Adult Bengalee Females
1 Introduction
2 Methodology
3 Results
4 Discussions
5 Conclusion
References
Individualized Helmet: An Approach for Reducing Road Traffic Injury Casualties
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion
References
Linkage Between Select Anthropometric Measures and Pulmonary Function Indicator: A Study on Bengalee Male Automobile Workers
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion
References
Study on Auditory Status and Annoyance Level of Male Adolescents Residing in the Vicinity of an Airport
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion
References
A Study on Flexibility and Fitness Status of Adult Bengalee Males Undergoing Training in Football
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion
References
Safety Begins at Kitchen: HFE Perspective
1 Introduction
2 Methodology
3 Results
4 Discussions
5 Conclusions
References
Investigation of Work-Related Musculoskeletal Disorders in the Carpentry Task
1 Introduction
2 Methodology.
2.1 Ergonomics Risk Assessment
2.2 REBA Validation
3 Objective
3.1 Participants
3.2 Procedure
4 Results
5 Discussion and Conclusion
References
Re-Hospitalization Due to Secondary Complications Post Spinal Cord Injury
1 Introduction
2 Methods
3 Results
3.1 Flow of SCI Patients in the System
3.2 Demographic Details of Participants
3.3 Reasons for the Re-Hospitalizations
4 Discussions
5 Conclusions
References
Relation Between Occupational Sitting Duration and Central Obesity? A Study in Bengalee Female Human Resources Engaged in Sedentary Occupation
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion
References
Impact of Bharatnatyam Dancing on Obesity and Diabetes Risk Status: A Study in Bengalee Female Human Resources Engaged in Sedentary Occupations
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
Assessment of Physiological Strain in Male Food Crop Cultivators Engaged in Manual Reaping Task
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion
References
Analysis of Posture and Workplace of Female Students Using Laptop in Hostel
1 Introduction
2 Methodology
3 Results
3.1 General Information and Laptop Usage Pattern by Hostel Students
3.2 Laptop Workstation and Posture Adopted by Students in Hostel
3.3 Furniture-Related and Posture-Related Problems Faced by Laptop Users
4 Discussions
5 Conclusion
References
Assessment of Prevalence of Musculoskeletal Disorders Among Packing Workers in Pharmaceutical Industry
1 Introduction
2 Methods
2.1 Data Collection Procedure
2.2 Job Description
2.3 Owas
2.4 Musculoskeletal Problems
3 Results
3.1 Demographic Data
3.2 Musculoskeletal Disorder Data
3.3 Posture Assessment
4 Discussions
5 Conclusion
References
A Preliminary Report on Musculoskeletal Pains and Discomfort Among Indian School Children Due to Mismatch Between Anthropometric Measurements and Classroom Furniture
1 Introduction
2 Methods
3 Statistical Analysis and Results
4 Discussion
5 Conclusion
References
Ergonomic Assessment Among Workers Engaged in Pashmina Embroidery Work in Kashmir, India
1 Introduction
2 Material and Methods
2.1 Participants
2.2 Survey Technique
2.3 Posture Analysis
2.4 Aari Design Modification
3 Results and Discussion
4 Conclusions
References
Ergonomic Study of Manual Work of a Workplace: A Case Study
1 Introduction
2 Methodology
3 Problem Identification
3.1 Mold Development Division
3.2 Molded Component Division
3.3 Finishing Division
4 Results
4.1 Anthropometry
4.2 Rapid Upper Limb Assessment [RULA]
5 Conclusion
References
Assessing Relationship Between Drivers Behavior and Cognitive Failure: Categorizing Sub-groups of Drivers
1 Introduction
2 Method
2.1 Participant
2.2 Instruments and Procedure
2.3 Statistical Analysis
3 Results
4 Discussion
References
Role of Ergonomics in English Language Teaching: An Overview
1 Introduction
1.1 Ergonomics
2 Ergonomics and English Language Teaching
2.1 Role of Interactive Language Laboratories
2.2 Role of Self-Access Room (SAR) in Language Teaching and Learning
2.3 Ergonomics and Varieties of International English (IE)
2.4 Scope of Ergonomics in Language Teaching and Learning
3 Conclusions
References
Inhaled Particles Deposition in Human Respiratory Tract During Friction Stir Processing (FSP)
1 Introduction
2 Human Respiratory System
3 Particle Deposition Mechanism
4 Effect of Friction Stir Process Parameters and Strategy on Human Health
5 Effect of Different FSP Powdered Materials on Human
5.1 Aluminum Oxide
5.2 Silicon Carbide
5.3 Titanium Carbide (TiC)
6 Precautionary Recommendation During FSP
7 Conclusion
References
Friction Stir Welding Process Vis-a-Vis Human Health
1 Introduction
2 Health Hazards Associated with Fusion Welding
2.1 Inhalation Hazards
2.2 Exposure to Radiation
2.3 Effect of Noise
2.4 Effect of Heat
3 Friction Stir Welding
3.1 Process and Benefits
3.2 Ergonomics in FSW
4 Conclusion
References
Overview of Garbage Monitoring System
1 Introduction
2 Literature Survey
3 Contextual Inquiry
4 Work Models
4.1 Flow Model
4.2 Sequence Model
4.3 Artifact Model
5 Conclusion and Future Work
References
Pulmonary Function Analysis of a Simple Crossed Legs Sitting Posture
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusion
References
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Design Science and Innovation
Mohammad Muzammil Abid Ali Khan Faisal Hasan Editors
Ergonomics for Improved Productivity Proceedings of HWWE 2017
Design Science and Innovation Series Editor Amaresh Chakrabarti, Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore, India
The book series is intended to provide a platform for disseminating knowledge in all areas of design science and innovation, and is intended for all stakeholders in design and innovation, e.g. educators, researchers, practitioners, policy makers and students of design and innovation. With leading international experts as members of its editorial board, the series aims to disseminate knowledge that combines academic rigour and practical relevance in this area of crucial importance to the society.
More information about this series at http://www.springer.com/series/15399
Mohammad Muzammil · Abid Ali Khan · Faisal Hasan Editors
Ergonomics for Improved Productivity Proceedings of HWWE 2017
Editors Mohammad Muzammil Department of Mechanical Engineering Aligarh Muslim University Aligarh, Uttar Pradesh, India
Abid Ali Khan Department of Mechanical Engineering Aligarh Muslim University Aligarh, Uttar Pradesh, India
Faisal Hasan Department of Mechanical Engineering Aligarh Muslim University Aligarh, Uttar Pradesh, India
ISSN 2509-5986 ISSN 2509-5994 (electronic) Design Science and Innovation ISBN 978-981-15-9053-5 ISBN 978-981-15-9054-2 (eBook) https://doi.org/10.1007/978-981-15-9054-2 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 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 Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Contents
Satyan Steering Gear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sathyanesan T. Narayanan Enhancing Walking Stability of Foot Deformities Patients by 3D-Printed Ankle Foot Orthosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Harish Kumar Banga, R. M. Belokar, Parveen Kalra, and Rajesh Kumar Analyzing the Important Factors Causing Fatigue in Industrial Workers Using Fuzzy MCDM Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . Noor Zaman Khan, Reshma Yasmin Siddiquie, Suha K. Shihab, Arshad Noor Siddiquee, and Zahid A. Khan Prioritizing the TQM Enablers in HCEs for Improved Performance: An AHP Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Faisal Talib and Zillur Rahman Development of Bottom-Wear Size Chart for Indian Male Youth . . . . . . Manoj Tiwari and Noopur Anand
1
13
25
33 43
Occupational Health Hazard of Workers Engaged in Food Processing Unit of Assam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lahkar Koushika and Bhattacharyya Nandita
57
Ergonomic Evaluation of a Car Interior: A Case Example on Shelby Cobra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anirban Chowdhury and Chaitanya Kachare
65
Ergonomic Risk Assessment and Postural Analysis of Indian Agricultural Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arunesh Chandra, Sachin Rathore, and Z. Mallick
73
Ergonomics in the Kitchen of Working Women of MIG Families (A Study of Aligarh City) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rashmi Singh and Saba Khan
83
v
vi
Contents
Physical Effects on an Assembly of Modeled Teeth and Mandible Using Finite Element Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sheeraz Athar, Ahmad Raza Usmani, Abid Ali Khan, Prabhat Kumar Chaudhari, and Mohd. Tariq A Case for Re-Examining Office Furniture Norms in India . . . . . . . . . . . Vinod Gupta
91
97
Advergames Are More Persuasive Among Different Online Advertisements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tara Thomas, Kanika Tuteja, and Anirban Chowdhury
105
Analysis of the Critical Factors for Integration of Sustainability with Lean Practices for Indian Manufacturing Enterprises . . . . . . . . . . . Sonal Khurana, Bisma Mannan, and Abid Haleem
119
Enhancing Human Productivity in Stress-Oriented Jobs: A Proposed Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Asif Khan, Shantanu Saraswat, Ashutosh Yadav, and Faisal Talib
127
Effect of Noise-Induced Stress on Bus Drivers of Faridabad (India) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gajender, Zulquernain Mallick, and Mohammad Asjad
135
Ergonomic Study on Foundry Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Debasis Haldar, Rauf Iqbal, Asif Mahammadsayed Qureshi, and Vivek Khanzode
145
Modernizing Ergonomics Through Additive Manufacturing Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohd Imran Khan, Shahbaz Khan, and Abid Haleem
157
Factors Affecting Work-Related Musculoskeletal Disorders in Caregiving Staff at Hospitals and Medical Organization . . . . . . . . . . . Deevesh Sharma, Awadhesh Bhardwaj, and Monica Sharma
165
Redesigning Agricultural Tools Using Anthropometry of Male Agricultural Workers of Dayalbagh Region, Agra, India . . . . . . . . . . . . . P. Singh, S. Srivastava, and N. S. Thakur
173
Effect of Environmental Parameters on Performance and Fatigue of a Worker Performing a Metal Pouring Operation . . . . . . Saman Ahmad, A. Varshney, S. Singhal, V. Agrawal, and A. Saleem
181
Design of Land Leveller Height Measuring Physiological and Psychophysical Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . P. Singh, S. Srivastava, and N. S. Thakur
189
Integrated Supply Chain Problems and Organizational Ergonomics: An Insight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rishav Khanal and J. Sanjog
199
Contents
vii
Ergonomic Interventions for Manual Material Handling Tasks in a Warehouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vibha Bhatia, Parveen Kalra, and Jagjit Singh Randhawa
205
Ergonomics in Product Design—Past, Present, and Future: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Saed Enam Mustafa, Mohammad Asghar Khan, and Hasan Faraz
213
A Comparative Analysis of a Mouse and Touchpad Based on Throughput and Locations for a Laptop Computer . . . . . . . . . . . . . . . Mohd Shah Faizan, Tauheed Mian, and Mohammed Muzammil
219
Ergonomic Assessment of Chaff Cutting Task . . . . . . . . . . . . . . . . . . . . . . . Md Samiullah Ansari, Faisal Hasan, Siddharth Bhardawaj, and Saiful Wali Khan Experimental Study of Rate of Heat Release of Sprays in Supercritical Direct Injection Combustion System Using Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sanaur Rehman Analysis of Health Issue and Musculoskeletal Problem for Workers in Manufacturing Sectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Adalarasu, T. Aravind Krishna, S. Sashank, and S. Kathirvel Analysis of Working Postures Leading to Musculoskeletal Disorders Among Employees in Garment Manufacturing Units—A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. N. Subramanya, K. V. S. Rajeswara Rao, and N. S. Shobha
227
233
243
251
Suppressed Articulatory Rehearsal Mechanism, Gaze Behavior, and Direction Following in Distracted Driving . . . . . . . . . . . . . . . . . . . . . . . Sajad Ahmad Najar and Premjit Khanganba Sanjram
263
Experimental Study of Ignition and Combustion Characteristics of Dieseline Spray in Supercritical State . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sanaur Rehman, Ankur Mahavar, and Arees Qamareen
271
Electromyographic Analysis of Low Back Muscles of Occupational Workers: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ashish Yadav, Greesh Kumar Singh, and Sanjay Srivastava
281
Isometric Push/Pull Strength of Indian Male Participants at Three Handle Heights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rahul Jain, M. L. Meena, and G. S. Dangayach
287
viii
Contents
Postural Analysis, Occupational Health, and Ergonomic Intervention of Welding Workers in Different Small-Scale Welding Units: A Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Das Suman, Pal Pabitra Kumar, Banerjee Debamalya, and Mukherjee Shankarashis
295
Strength Index of Axle Housing of Pre-ROPS Agricultural Tractors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. K. Shrivastava and V. K. Tewari
309
Ergonomic Hazard Identification and Assessment of a Garment Factory in KSA—An Exploratory Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . Banan Masoud, Nada Al-Saiari, Noor Al-Shareef, Yara Munshi, and Farheen Bano Impact of Exposure to the High Noise Level on Occupational Health of the Weavers Engaged in Handloom Sectors in India: A Case Study from Bargarh District . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Surendra Kumar, Abhirup Chatterjee, and Sougata Karmakar Evaluation of Agricultural Waste Natural Fiber as an Acoustic Absorber for Reduction of Industrial Noise . . . . . . . . . . . . . . . . . . . . . . . . . Tafzeelul Kamal, Issam Wajih, Vikas Sharma, Yasser Rafat, and M. A. Siddiqui Impact of Heat Stress and Its Impression on Cardiac Jeopardy Among Construction Laborers: A Consequence for a Climate Change Imminent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arijit Chatterjee and Subhashis Sahu
321
327
335
343
User-Centered System Design for Indian Small-Scale Industries: Case Study on Pottery Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Devyani Shirole, Wricha Mishra, and Debayan Dhar
353
Space Ergonomics: Analysis of Artificial Gravity Model and an Improved Proposed Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Md Ragib Hussain, Abdurrahman, and Asif Khan
365
Assessment of Checkout Operator’s Workload in Organized Retail Stores of India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nabila Rehman and Namrata Arora Charpe
373
Ergonomic Evaluation and Work Table Design for Wood Furniture Manufacturing Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ashish Kumar Singh, Rahul Jain, Bharat Singh, and Makkhan Lal Meena
383
Technical Intervention for Assessment of Physiological Characteristics as Function of Operating Force in Traditional Agricultural Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Smrutilipi Hota, V. K. Tewari, Gajendra Singh, and Sweeti Kumari
391
Contents
Effect of Vibration Intervention on Forearm Muscles to Improve Grip Strength: A Systematic Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Azhar Eqbal, Mohd Mukhtar Alam, Israr Ahmad, Abid Ali Khan, and Mohd Farooq Relationship Between Grip Strength and Anthropometric Variations—A Systematic Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Israr Ahmad, Mohd Mukhtar Alam, Nadeemul Haque, Abid Ali Khan, and Mohd Farooq
ix
401
409
Ergonomic Assessment of Work-Related Musculoskeletal Disorders and Comfort of Students in Mechanical Workshop . . . . . . . . . P. Saraswat, M. K. Sain, and M. L. Meena
417
A Comparative Study of Thermal Environment Between Two Varieties of Pantry Car Available in Indian Railway . . . . . . . . . . . . . . . . . Md. Sarfaraz Alam, Arunachalam Muthiah, and Urmi Salve
425
Gender Differences in Sleep Apnea—A Questionnaire Study . . . . . . . . . J. Rajeswari, M. Jagannath, and K. Adalarasu
435
Work-Related Musculoskeletal Disorders Among the Metal Craft Workers in Jaipur, India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dipayan Das, Awadhesh Bhardwaj, and Monica Sharma
443
Ergonomic Intervention for Drudgery Reduction in Paddy Seed selection—A Post-harvest Activity in Assam . . . . . . . . . . . . . . . . . . . . . . . . M. Kalita, R. Borah, and P. Saikia
451
Classification of Mobile Interactions Based on Human Emotion . . . . . . . Anindya Sundar Mukhopadhyay, Ketan Shimpi, Vinayak Bhandare, and Tanmoy Goswami
459
Evaluation of Vibration and Physiological Parameters of Indian Female Workers for Operating a Mini-Combine Harvester . . . . . . . . . . . Gajendra Singh, V. K. Tewari, Smrutilipi Hota, and Naveen Kumar
469
Workplace Design Factors, Well-Being and Ergonomics Training—A Case for Indian Millennial Employee . . . . . . . . . . . . . . . . . . . Shalini Singh and Ayesha Farooq
477
Leadership Decisions on Workplace Ergonomics: Roadmap to Success . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ayesha Rehman, Faiz Rehman Abbasi, and Ayesha Farooq
487
Analysing the Prevalence of Occupational Risk Among Workers Involved in Traditional Clay Brick Manufacturing Tasks . . . . . . . . . . . . . M. K. Sain and M. L. Meena
497
Ergonomics in the Workplace for a Better Quality of Work Life . . . . . . Saman Afroz and Mohammad Israrul Haque
503
x
Contents
Ergonomic Evaluation of a CNC Machine Panel Keyboard . . . . . . . . . . . Mohamad Masud Faridi, Imtiaz Ali Khan, and Umair Arif
513
Design and Development of an Automated Hand Shovel . . . . . . . . . . . . . . Mohammed Rajik Khan and Aditya Rahul Gupta
525
Microstructure Evolution in Dissimilar Friction Stir Weld Joints of Precipitation and Solution Hardening Aluminum Alloys . . . . . . . . . . . Vishwdeep Sharma, Chaitanya Sharma, and Vikas Upadhyay
533
Design and Evaluation of Wheelchair-Mounted Self-Transfer Assistive Device for Elderly and Patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kelifa Seid and Amarendra Kumar Das
539
Evaluation of Crew Protection Performance and Ergonomic Design Aspects of a Light Combat Vehicle During Its Conceptualization Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amare Wibneh and Sougata Karmakar User-Oriented Subjective Ergonomic Evaluation for Work-Related Disorders: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kiran Mohan, V. Madhusudanan Pillai, S. Abhinav, Amal Sunny, Vishnu V. Kumar, O. R. Rohith Raj, S. Abishek, and Vahid Mohammad Effect of Nozzle Tip Distance in Minimum Quantity Coolant-Assisted Turning of Ti-6Al-4V Alloy . . . . . . . . . . . . . . . . . . . . . . . . Vikas Upadhyay Assessment of Bus Driver Performance Based on Reaction Time on Simulator and On-Road Driving . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rahul Bhardwaj, Sathish Kumar Sivasankaran, and Venkatesh Balasubramanian Comparative Assessment of Mini-Mental State Examination in Bus Drivers for On-Road and Simulator Study Conditions . . . . . . . . . Sathish Kumar Sivasankaran, Rahul Bharadwaj, and Venkatesh Balasubramanian Reverse Engineering in Customization of Products: Review and Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohammad Faisal Noor, Faisal Hasan, Siddharth Bhardwaj, and Saim Hasan Comparison of Fatigue Trend Among Different Aged Driver on Simulator and On-Road Driving . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rahul Bhardwaj, Sathish Kumar Sivasankaran, and Venkatesh Balasubramanian
547
555
567
573
581
587
593
Contents
Subjective Evaluation of Musculoskeletal Disorders Among Fatal and Nonfatal Bus Drivers in Different Scenarios . . . . . . . . . . . . . . . Sathish Kumar Sivasankaran, Rahul Bharadwaj, and Venkatesh Balasubramanian
xi
601
A Low-Cost Reaction Time Estimator-Based Hand and Foot Exercises for Stroke Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rahul Bhardwaj and Venkatesh Balasubramanian
609
Real-Time Driver Fatigue Detection from ECG Using Deep Learning Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Anjaly Cherian, Rahul Bhardwaj, and Venkatesh Balasubramanian
615
Training System for Autistic Children Based on Virtual Reality . . . . . . . Ceethal Piyus, Rahul Bhardwaj, and Venkatesh Balasubramanian Cognitive Assessment of Driver Fatigue Based on Machine Learning Using EEG Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rahul Bhardwaj, Ceethal Piyus, and Venkatesh Balasubramanian
623
631
Comparative Study of ANN Algorithms for EMG Signals . . . . . . . . . . . . Salman Mohd Khan, Mohd Parvez, Siddharth Bhardwaj, and Abid Ali Khan
637
EEG-Based Exoskeleton for Rehabilitation Therapy . . . . . . . . . . . . . . . . . Bilal Alam Khan, Ahmad Raza Usmani, Sheeraz Athar, Anam Hashmi, Omar Farooq, and M. Muzammil
645
Barriers to Promote Occupational Health and Safety (OHS) Among Different Construction Types in India . . . . . . . . . . . . . . . . . . . . . . . C. Vigneshkumar and K. Saravanamuthu
655
An Optimized Algorithm for Automatic Seizure Detection in Time Frequency Domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ayesha Tooba Khan and Yusuf Uzzaman Khan
663
Designing Baffles of Fuel Tanker Truck to Prevent Rollovers . . . . . . . . . Nafees Ahmad, Mehul Varshney, M. Haani Farooqi, and Umair Khan
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Cockpit Design of a Formula Student Race Car: An Ergonomics Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arshil Ahmad, Syed Ali Zaheen, Israr Ahmad, and Faisal Talib
679
Design and Development of Semi-Automatic Handloom Incorporating Human Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Manohar Mahato and Amarendra Kumar Das
691
Footwear: Purchase and Impact on Health . . . . . . . . . . . . . . . . . . . . . . . . . . Devika Vipin Vaidya, Rauf Iqbal, and Archana Bhatnagar
699
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Ergonomics Study on the Handle Orientation of Shovel . . . . . . . . . . . . . . Ayush Saxena, Siddharth Bhardwaj, and Vishal Saxena
705
Subjective Evaluation of Driver Distraction Caused During Use of Mobile Phone for Navigation Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . Indresh Verma and Sougata Karmakar
713
A Scrutiny of On-Job Stress and Occupational Well-Being of Indian Policewomen Compared to Chinese Policewomen . . . . . . . . . . . Shilpi Bora, Abhirup Chatterjee, and Debkumar Chakrabarti
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Knee Arthritis-Related Issues Among Aging Population in Indian Households . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prakash Kumar, Sarthak Mittal, and Siddharth Jhawar
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WMSDs Among Workers Engaged in Press Work at Small-Scale Lock Industries: A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohd Asif Khan, Mahtab Ali, Irfan Ahmad, and Siddharth Bhardwaj
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Carpal Tunnel Syndrome Estimation in Shock Absorber Assembly Workforce in Indian Automobile Industry: A Study . . . . . . . . Santosh Kumar and M. Muralidhar
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The Use of Worksheets and Checklists in Imparting Ergonomics Education to Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Darius Gnanaraj
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Effect of Housing Dimensions and Materials on Human Thermal Comfort in Air-Conditioned Beds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohd Mansoor, Sana Fatema, Nafees Ahmad, and Taliv Hussain
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Can Dynamic Widgets Improve Data Entry Efficiency? . . . . . . . . . . . . . . Shrikant Salve, Ganesh Bhutkar, and Pradeep Yammiyavar Correlation Between Anthropometry Dimensions and EMG Features During Endurance Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohd Mukhtar Alam, Abid Ali Khan, and Mohd Farooq Industrial Defects Reduction Using Quality Control Tools . . . . . . . . . . . . Jafar Husain, Samar Khan, Obaidullah Khawar, Arunesh Chandra, and Abid Ali Khan Design and Analysis of Partial Right Foot Chopart Socket Prosthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Falah Hasan Abdulsadah, Qasim Murtaza, Faisal Hasan, Siddharth Bhardwaj, Mehul Varshney, and Marwan Shaiban Implementation of Kansei Engineering to Develop a Framework to Retain Ethnicity of Indian Handloom Products . . . . . . . . . . . . . . . . . . . Chirapriya Mondal and Sougata Karmakar
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779 787
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Multichannel Feature Extraction for Pattern Recognition of EMG Signals in Time and Frequency Domain . . . . . . . . . . . . . . . . . . . . Mohd Mukhtar Alam, Abid Ali Khan, and Mohd Farooq Psychophysical Approach in Manual Material Handling: Review . . . . . A. Saleem, A. Raza, and S. Ahmad Musculoskeletal Disorders and Visual Symptoms Among Virtual Reality Headset Users . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Umair Arif, Roohul Huda Khan, and Abid Ali Khan Influence of Indian Classical Dancing on the Postural Stability of Adult Bengalee Females . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Surjani Chatterjee, Neepa Banerjee, Satabdi Bhattacharjee, Sandipan Chatterjee, Debamalya Banerjee, and Shankarashis Mukherjee Individualized Helmet: An Approach for Reducing Road Traffic Injury Casualties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Barnini Bhattacharya, Neepa Banerjee, Surjani Chatterjee, Raja Bhattacharya, Kuntal Ghosh, and Shankarashis Mukherjee Linkage Between Select Anthropometric Measures and Pulmonary Function Indicator: A Study on Bengalee Male Automobile Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tanaya Santra, Neepa Banerjee, Sandipan Chatterjee, Ayan Chatterjee, Kuntal Ghosh, and Shankarashis Mukherjee Study on Auditory Status and Annoyance Level of Male Adolescents Residing in the Vicinity of an Airport . . . . . . . . . . . . . . . . . . . Sandipan Chatterjee, Ayan Chatterjee, Surjani Chatterjee, Neepa Banerjee, Santanu De, and Shankarashis Mukherjee A Study on Flexibility and Fitness Status of Adult Bengalee Males Undergoing Training in Football . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Satabdi Bhattacharjee, Tanaya Santra, Surjani Chatterjee, Priyanka Biswas, Neepa Banerjee, and Shankarashis Mukherjee Safety Begins at Kitchen: HFE Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . Neepa Banerjee, Surjani Chatterjee, Satabdi Bhattacharjee, Sandipan Chatterjee, and Shankarashis Mukherjee
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841
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Investigation of Work-Related Musculoskeletal Disorders in the Carpentry Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Umair Arif and Afsar Husain
895
Re-Hospitalization Due to Secondary Complications Post Spinal Cord Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Priyanka Rawal and Gaur G. Ray
905
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Relation Between Occupational Sitting Duration and Central Obesity? A Study in Bengalee Female Human Resources Engaged in Sedentary Occupation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neepa Banerjee, Surjani Chatterjee, Sandipan Chaterjee, Satabdi Bhattacherjee, Santanu De, and Shankarashis Mukherjee
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Impact of Bharatnatyam Dancing on Obesity and Diabetes Risk Status: A Study in Bengalee Female Human Resources Engaged in Sedentary Occupations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neepa Banerjee, Priyanka Biswas, Surjani Chatterjee, Tanaya Santra, Sandipan Chatterjee, and Shankarashis Mukherjee
921
Assessment of Physiological Strain in Male Food Crop Cultivators Engaged in Manual Reaping Task . . . . . . . . . . . . . . . . . . . . . . . Ayan Chatterjee, Sandipan Chatterjee, Surjani Chatterjee, Tanaya Santra, Neepa Banerjee, and Shankarashis Mukherjee
931
Analysis of Posture and Workplace of Female Students Using Laptop in Hostel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chauhan Manjit Kaur, Singh Pooja, and Patel Prachi
939
Assessment of Prevalence of Musculoskeletal Disorders Among Packing Workers in Pharmaceutical Industry . . . . . . . . . . . . . . . . . . . . . . . Murarka Pallavi and Chauhan Manjit Kaur
949
A Preliminary Report on Musculoskeletal Pains and Discomfort Among Indian School Children Due to Mismatch Between Anthropometric Measurements and Classroom Furniture . . . . . . . . . . . . Vandana Esht and Ajita D. Singh Ergonomic Assessment Among Workers Engaged in Pashmina Embroidery Work in Kashmir, India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Uzma Iqbal, Siddharth Bhardwaj, and Asma Iqbal Ergonomic Study of Manual Work of a Workplace: A Case Study . . . . . V. Suresh, Ankit Sharad Ranka, Deep Matkar, and Arun Tom Mathew Assessing Relationship Between Drivers Behavior and Cognitive Failure: Categorizing Sub-groups of Drivers . . . . . . . . . . . . . . . . . . . . . . . . Nikita Sharma and Azizuddin Khan Role of Ergonomics in English Language Teaching: An Overview . . . . . Syyada Faheem Inhaled Particles Deposition in Human Respiratory Tract During Friction Stir Processing (FSP) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nidhi Sharma
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963 971
981 989
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Friction Stir Welding Process Vis-a-Vis Human Health . . . . . . . . . . . . . . . 1003 Mohd Atif Wahid, Suha K. Shihab, Rohit Shandley, Ashish Jacob, and Tanveer Majeed Overview of Garbage Monitoring System . . . . . . . . . . . . . . . . . . . . . . . . . . . 1011 Vinod Shinde, Ganesh Bhutkar, and Virendra Pawar Pulmonary Function Analysis of a Simple Crossed Legs Sitting Posture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1019 Manish Yadav, Greesh Kumar Singh, Ashish Yadav, Sanjay Srivastava, and Gopichand Gupta
Editors and Contributors
About the Editors Dr. Mohammad Muzammil is a Professor in the Department of Mechanical Engineering and also in-charge of the Ergonomics Research Division. He has B.Sc. Engineering (Mechanical) and M.Sc. Engineering (Industrial and Production Engineering) from AMU, Aligarh. He has self-supplicated his Ph.D. in Ergonomics. He has more than thirty years of teaching and research experience to his credit in the area of Industrial Engineering, Operations Management, Economics & Management and Ergonomics. His research interest is hand tool design, human response to vibration and noise, noise control engineering, human–computer interaction and human cognitive performance. He has published around papers in journals of international and national repute and presented papers at several conferences. Dr. Abid Ali Khan is a Professor in the Department of Mechanical Engineering and is also associated with the Centre for Interdisciplinary Biomedical and Human Factors Engineering in the Faculty of Engineering & Technology. He has B.Sc. Engineering (Mechanical) and M.Sc. Engineering (Industrial and Production Engineering) from AMU, Aligarh. He received his Ph.D. from the University of Limerick, Ireland. He teaches Ergonomics, Experimental Methods & Analysis, Design of Experiments and Research Methodology. His research interest is occupational ergonomics, human response to vibration, work-related musculoskeletal disorder and EMG. He has published more than 90 papers in various international and national journals and conferences. He is involved in the R&D activities related to the various areas, viz. whole body and hand-arm vibration exposure, ergonomic evaluation of new designs and EMG-based prosthetics. Dr. Faisal Hasan obtained his Ph.D. in the area of Reconfigurable Manufacturing System from Indian Institute of Technology Roorkee. He joined as a faculty member in the Department of Mechanical Engineering, AMU, in 2003. His teaching and research interests include manufacturing systems, human factors and operations
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Editors and Contributors
management. He has published more than 75 papers in journals of national and international repute. He has also attended and presented papers at various international and national conferences.
Contributors Faiz Rehman Abbasi Jamia Millia Islamia, New Delhi, India Falah Hasan Abdulsadah Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Abdurrahman Zakir Husain College of Engineering & Technology, Aligarh Muslim University, Aligarh, UP, India S. Abhinav Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode, India S. Abishek Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode, India K. Adalarasu Department of Electronics and Instrumentation Engineering, SASTRA Deemed to be University, Thanjavur, India; School of Electrical and Electronics Engineering, SASTRA Deemed To Be University, Thanjavur, Tamil Nadu, India Saman Afroz Aligarh Muslim University, Aligarh, India V. Agrawal ZHCET Aligarh Muslim University, Aligarh, India Arshil Ahmad Department of Mechanical Engineering, Zakir Husain College of Engineering & Technology, Faculty of Engineering & Technology, Aligarh Muslim University, Aligarh, UP, India Irfan Ahmad Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Israr Ahmad Department of Mechanical Engineering, Zakir Husain College of Engineering & Technology, Faculty of Engineering & Technology, Aligarh Muslim University, Aligarh, UP, India Nafees Ahmad Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India S. Ahmad Z. H. C. E. T, Aligarh Muslim University, Aligarh, India Saman Ahmad ZHCET Aligarh Muslim University, Aligarh, India Nada Al-Saiari Department of Industrial Engineering, King Abdulaziz University, Jeddah, Saudi Arabia
Editors and Contributors
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Noor Al-Shareef Department of Industrial Engineering, King Abdulaziz University, Jeddah, Saudi Arabia Md. Sarfaraz Alam Department of Design, Indian Institute of Technology Guwahati, Guwahati, India Mohd Mukhtar Alam Ergonomics Research Division, Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Mahtab Ali Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Noopur Anand National Institute of Fashion Technology, New Delhi, India Md Samiullah Ansari Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India T. Aravind Krishna Centre for Business Research in Data Logic and Analysis, Coimbatore, India Umair Arif Aligarh Muslim University, Aligarh, India Mohammad Asjad Mechanical Department, Jamia Millia Islamia University, New Delhi, India Sheeraz Athar Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, U.P, India Venkatesh Balasubramanian RBG Lab, Department of Engineering Design, IIT Madras, Chennai, India Debamalya Banerjee Department of Production Engineering, Jadavpur University, Kolkata, India Neepa Banerjee Human Performance Analytics and Facilitation Unit, Department of Physiology, University Colleges of Science and Technology, University of Calcutta, Kolkata, India Harish Kumar Banga Production & Industrial Engineering Department, PEC University of Technology, Chandigarh, India Farheen Bano Department of Industrial Engineering, King Abdulaziz University, Jeddah, Saudi Arabia R. M. Belokar Production & Industrial Engineering Department, PEC University of Technology, Chandigarh, India Vinayak Bhandare MAEER’s MIT Institute of Design, Pune, India Rahul Bharadwaj RBG Lab, Department of Engineering Design, IIT Madras, Chennai, India Siddharth Bhardawaj Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India
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Editors and Contributors
Awadhesh Bhardwaj Department of Mechanical Engineering, Malviya National Institute of Technology Jaipur, Jaipur, Rajasthan, India Rahul Bhardwaj Indian Institute of Technology Madras, Chennai, India Siddharth Bhardwaj Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Vibha Bhatia PEC University of Technology, Chandigarh, India Archana Bhatnagar S.N.D.T Women’s University, Mumbai, India Satabdi Bhattacharjee Human Performance Analytics and Facilitation Unit, Department of Physiology, University Colleges of Science and Technology, University of Calcutta, Kolkata, India Barnini Bhattacharya Human Performance Analytics and Facilitation Unit, University of Calcutta, Rashbehari Shiksha Prangan, Kolkata, India; Indian Statistical Institute, Kolkata, India Raja Bhattacharya Human Performance Analytics and Facilitation Unit, University of Calcutta, Rashbehari Shiksha Prangan, Kolkata, India Satabdi Bhattacherjee HPAFU, University of Calcutta, Kolkata, India Ganesh Bhutkar Vishwakarma Institute of Technology (VIT), Pune, India; Indian Institute of Technology Bombay, Mumbai, India Priyanka Biswas RKMSP, Kolkata, India Shilpi Bora Ergonomics Laboratory, Department of Design, IIT Guwahati, Guwahati, Assam, India R. Borah Department of Family Resource Management and Consumer Science, College of Community Science, Assam Agricultural University, AAU, Jorhat, India Debkumar Chakrabarti Ergonomics Laboratory, Department of Design, IIT Guwahati, Guwahati, Assam, India Arunesh Chandra Department of Mechanical Engineering, KIET Group of Institutions, Dehi-NCR, Ghaziabad, Uttar Pradesh, India Namrata Arora Charpe Department of Home Science, Banasthali Vidyapith, Banasthali, Rajasthan, India Sandipan Chaterjee HPAFU, University of Calcutta, Kolkata, India Abhirup Chatterjee Central Institute of Technology Kokrajhar, Assam, India; Ergonomics Laboratory, Department of Design, IIT Guwahati, Guwahati, Assam, India Arijit Chatterjee Ergonomics and Occupational Physiology Laboratory, Department of Physiology, University of Kalyani, Nadia, Kalyani, West Bengal, India
Editors and Contributors
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Ayan Chatterjee Human Performance Analytics and Facilitation Unit, University Colleges of Science and Technology, University of Calcutta, Kolkata, India Sandipan Chatterjee Human Performance Analytics and Facilitation Unit, Department of Physiology, University Colleges of Science and Technology, University of Calcutta, Kolkata, India Surjani Chatterjee Human Performance Analytics and Facilitation Unit, Department of Physiology, University Colleges of Science and Technology, University of Calcutta, Kolkata, India Prabhat Kumar Chaudhari Division of Orthodontics and Dentofacial Orthopedics, Centre for Dental Education and Research, All India Institute of Medical Sciences, New Delhi, India V. Anjaly Cherian VIT University, Vellore, India Anirban Chowdhury School of Design, University of Petroleum and Energy Studies, Dehradun, India G. S. Dangayach Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur, Jaipur, India S. Darius Gnanaraj Vellore Institute of Technology (VIT), Vellore, India Amarendra Kumar Das Department of Design, Indian Institute of Technology Guwahati, Guwahati, India Dipayan Das Malaviya National Institute of Technology, Jaipur, Rajasthan, India Santanu De Human Performance Analytics and Facilitation Unit, University Colleges of Science and Technology, University of Calcutta, Kolkata, India; NRS Medical College and Hospital, Kolkata, India Banerjee Debamalya Department of Production Engineering, Jadavpur University, Kolkata, West Bengal, India Debayan Dhar User Experience Design Department, MIT Institute of Design, Pune, India Azhar Eqbal Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Vandana Esht Maharishi Markandeshwar Institute of Physiotherapy and Rehabilitation, Maharishi Markandeshwar (Deemed To Be) University, Mullana, Haryana, India Syyada Faheem Aligarh Muslim University, Aligarh, India Mohd Shah Faizan Mechanical Engineering Department, Aligarh Muslim University, Aligarh, India
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Editors and Contributors
Hasan Faraz Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Mohamad Masud Faridi Aligarh Muslim University, Aligarh, India Ayesha Farooq Department of Business Administration, FMSR, Aligarh Muslim University, Aligarh, India Mohd Farooq Ergonomics Research Division, Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Omar Farooq Department of Electronics Engineering, Aligarh Muslim University, Aligarh, U.P, India Sana Fatema Department of Computer Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Gajender Jamia Milia Islamia University, New Delhi, India Kuntal Ghosh Indian Statistical Institute, Kolkata, India Tanmoy Goswami MAEER’s MIT Institute of Design, Pune, India Aditya Rahul Gupta Industrial Design Department, National Institute of Technology Rourkela, Rourkela, Odisha, India Gopichand Gupta Consultanting Physician (Pulmonary Medicine), Saran Ashram Hospital, Dayalbagh, Agra, India Vinod Gupta School of Planning and Architecture, New Delhi, India; Opus Indigo Designs Pvt. Ltd, New Delhi, India M. Haani Farooqi Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Debasis Haldar National Institute of Industrial Engineering, Mumbai, India Abid Haleem Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India Mohammad Israrul Haque Aligarh Muslim University, Aligarh, India Nadeemul Haque Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Faisal Hasan Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Saim Hasan SHKM Government Medical College and Hospital, Nuh, India Anam Hashmi Department of Electronics Engineering, Aligarh Muslim University, Aligarh, U.P, India Smrutilipi Hota Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, India
Editors and Contributors
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Afsar Husain Aligarh Muslim University, Aligarh, India Jafar Husain Department of Mechanical Engineering, Z.H.C.E.T., A.M.U., Aligarh, India Md Ragib Hussain Zakir Husain College of Engineering & Technology, Aligarh Muslim University, Aligarh, UP, India Taliv Hussain Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Asma Iqbal Department of Chemical Engineering, Aligarh Muslim University, Aligarh, UP, India Rauf Iqbal National Institute of Industrial Engineering (NITIE), Mumbai, India Uzma Iqbal Division of Agricultural Engineering, SKUAST-K, Shalimar (J&K), India Ashish Jacob Division of MPAE, Netaji Subhas Institute of Technology, New Delhi, India M. Jagannath School of Electronics Engineering, Vellore Institute of Technology (VIT), Chennai, Tamil Nadu, India Rahul Jain Department of Mechanical Engineering, University Departments, Rajasthan Technical University Kota, Kota, India; Malaviya National Institute of Technology, Jaipur, Rajasthan, India Siddharth Jhawar Shiv Nadar University, Uttar Pradesh, India Chaitanya Kachare Institute of Design, MIT Art, Design and Technology University, Pune, India M. Kalita Department of Family Resource Management and Consumer Science, College of Community Science, Assam Agricultural University, AAU, Jorhat, India Parveen Kalra Production & Industrial Engineering Department, PEC University of Technology, Chandigarh, India Tafzeelul Kamal Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Sougata Karmakar Ergonomics Laboratory, Department of Design, Indian Institute of Technology Guwahati, Guwahati, Assam, India S. Kathirvel Department of Electronics and Communication Engineering, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, India Chauhan Manjit Kaur Department of Family Resource Management, SNDTWU, Juhu, Mumbai, India Abid Ali Khan Ergonomics Research Division, Department of Mechanical Engineering, Z.H.C.E.T., Aligarh Muslim University, Aligarh, UP, India
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Editors and Contributors
Asif Khan Department of Mechanical Engineering, Zakir Husain College of Engineering and Technology, Faculty of Engineering & Technology, Aligarh Muslim University, Aligarh, UP, India Ayesha Tooba Khan Department of Electrical Engineering, Aligarh Muslim University, Aligarh, India Azizuddin Khan Psychophysiology Laboratory, Department of Humanities and Social Sciences, Indian Institute of Technology, Bombay, Powai, India Bilal Alam Khan Department of Electronics Engineering, Aligarh Muslim University, Aligarh, U.P, India Imtiaz Ali Khan Aligarh Muslim University, Aligarh, India Mohammad Asghar Khan Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Mohammed Rajik Khan Industrial Design Department, National Institute of Technology Rourkela, Rourkela, Odisha, India Mohd Asif Khan Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Mohd Imran Khan Mittal School of Business, Lovely Professional University, Phagwara, Punjab, India Noor Zaman Khan Department of Mechanical Engineering, National Institute of Technology, Srinagar, Jammu and Kashmir, India Roohul Huda Khan Aligarh Muslim University, Aligarh, India Saba Khan Department of Home Science, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Saiful Wali Khan Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India Salman Mohd Khan Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Samar Khan Department of Mechanical Engineering, Z.H.C.E.T., A.M.U., Aligarh, India Shahbaz Khan GLA University, Mathura, India Umair Khan Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Yusuf Uzzaman Khan Department of Electrical Engineering, Aligarh Muslim University, Aligarh, India Zahid A. Khan Department of Mechanical Engineering, Jamia Millia Islamia (A Central University), New Delhi, India
Editors and Contributors
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Rishav Khanal Department of Mechanical Engineering, Shepherd Institute of Engineering and Technology (SIET), Sam Higginbottom University of Agriculture, Technology and Sciences (SHUATS), Allahabad, Uttar Pradesh, India Vivek Khanzode National Institute of Industrial Engineering, Mumbai, India Obaidullah Khawar Department of Mechanical Engineering, Z.H.C.E.T., A.M.U., Aligarh, India Sonal Khurana Jamia Millia Islamia, New Delhi, India Lahkar Koushika Department of Family Resource Management and Consumer Science, College of Community Science, Assam Agricultural University, Jorhat, India Naveen Kumar Agricultural and Food Engineering Department, IIT Kharagpur, Kharagpur, India Pal Pabitra Kumar Department of Production Engineering, Jadavpur University, Kolkata, West Bengal, India Prakash Kumar Shiv Nadar University, Uttar Pradesh, India Rajesh Kumar Mechanical Engineering Department, UIET, Panjab University Chandigarh, Chandigarh, India Santosh Kumar Department of Mechanical Engineering, North Eastern Regional Institute of Science and Technology, Itanagar, Arunachal Pradesh, India Surendra Kumar Indian Institute of Handloom Technology, Bargarh, Orissa, India Vishnu V. Kumar Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode, India Sweeti Kumari Central Institute of Agricultural Engineering, Bhopal, India Manohar Mahato Department of Design, Indian Institute of Technology Guwahati, Guwahati, India Ankur Mahavar Combustion and Pollution Control Laboratory, Department of Mechanical Engineering, ZHCET, AMU, Aligarh, India Tanveer Majeed Department of Mechanical Engineering, Jamia Millia Islamia (A Central University), New Delhi, India Z. Mallick Faculty of Engineering and Technology, Jamia Millia University, New Delhi, India Zulquernain Mallick Mechanical Department, Jamia Millia Islamia University, New Delhi, India Bisma Mannan Jamia Millia Islamia, New Delhi, India
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Editors and Contributors
Mohd Mansoor Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Banan Masoud Department of Industrial Engineering, King Abdulaziz University, Jeddah, Saudi Arabia Arun Tom Mathew Department of Design and Automation, School of Mechanical Engineering, VIT University, Vellore, Tamil Nadu, India Deep Matkar Department of Design and Automation, School of Mechanical Engineering, VIT University, Vellore, Tamil Nadu, India M. L. Meena Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur, Jaipur, India Makkhan Lal Meena Malaviya National Institute of Technology, Jaipur Rajasthan, India Tauheed Mian Mechanical Engineering Department, Aligarh Muslim University, Aligarh, India Wricha Mishra User Experience Design Department, MIT Institute of Design, Pune, India Sarthak Mittal Shiv Nadar University, Uttar Pradesh, India Vahid Mohammad Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode, India Kiran Mohan Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode, India Chirapriya Mondal Indian Institute of Technology Guwahati, Guwahati, India Shankarashis Mukherjee Public Health Analytics Unit, Department of Food and Nutrition, West Bengal State University, Kolkata, India Anindya Sundar Mukhopadhyay MAEER’s MIT Institute of Design, Pune, India Yara Munshi Department of Industrial Engineering, King Abdulaziz University, Jeddah, Saudi Arabia M. Muralidhar Department of Mechanical Engineering, North Eastern Regional Institute of Science and Technology, Itanagar, Arunachal Pradesh, India Qasim Murtaza Department of Mechanical Engineering, Delhi Technological University, Delhi, India Saed Enam Mustafa Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Arunachalam Muthiah Department of Design, Indian Institute of Technology Guwahati, Guwahati, India
Editors and Contributors
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M. Muzammil Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, U.P, India Mohammed Muzammil Mechanical Engineering Department, Aligarh Muslim University, Aligarh, India Sajad Ahmad Najar Department of Psychology, Central University of Punjab, Bathinda, India Bhattacharyya Nandita Department of Family Resource Management and Consumer Science, College of Community Science, Assam Agricultural University, Jorhat, India Sathyanesan T. Narayanan Mechanical Engineering, Govt. Engineering College, Thrissur, Kerala, India Mohammad Faisal Noor Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jamshedpur, India Murarka Pallavi Department of Family Resource Management, SNDTWU, Mumbai, India Mohd Parvez Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Virendra Pawar Vishwakarma Institute of Technology (VIT), Pune, India V. Madhusudanan Pillai Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode, India Ceethal Piyus Vellore Institute of Technology, Vellore, India Singh Pooja Department of Resource Management, SNDTWU, Juhu, Mumbai, India Patel Prachi Department of Resource Management, SNDTWU, Juhu, Mumbai, India Arees Qamareen Combustion and Pollution Control Laboratory, Department of Mechanical Engineering, ZHCET, AMU, Aligarh, India Asif Mahammadsayed Qureshi K.I. Ts College of Engineering, Kolhapur, India Yasser Rafat Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Zillur Rahman Department of Management Studies, Indian Institute of Technology, Roorkee, Uttarakhand, India O. R. Rohith Raj Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode, India K. V. S. Rajeswara Rao Department of Industrial Engineering & Management, Rashtreeya Vidyalaya College of Engineering, Bengaluru, India
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Editors and Contributors
J. Rajeswari School of Electronics Engineering, Vellore Institute of Technology (VIT), Chennai, Tamil Nadu, India Jagjit Singh Randhawa PEC University of Technology, Chandigarh, India Ankit Sharad Ranka Department of Design and Automation, School of Mechanical Engineering, VIT University, Vellore, Tamil Nadu, India Sachin Rathore Department of Mechanical Engineering, KIET Group of Institutions, Dehi-NCR, Ghaziabad, Uttar Pradesh, India Priyanka Rawal IDC, School of Design, Indian Institute of Technology Bombay, Mumbai, India Gaur G. Ray IDC, School of Design, Indian Institute of Technology Bombay, Mumbai, India A. Raza Z. H. C. E. T, Aligarh Muslim University, Aligarh, India Ayesha Rehman Aligarh Muslim University, Aligarh, India Nabila Rehman Department of Home Science, Banasthali Vidyapith, Banasthali, Rajasthan, India Sanaur Rehman Combustion and Pollution Control Laboratory, Department of Mechanical Engineering, ZHCET, AMU, Aligarh, India Subhashis Sahu Ergonomics and Occupational Physiology Laboratory, Department of Physiology, University of Kalyani, Nadia, Kalyani, West Bengal, India P. Saikia Department of Family Resource Management and Consumer Science, College of Community Science, Assam Agricultural University, AAU, Jorhat, India M. K. Sain Department of Mechanical Engineering, Swami Keshvanand Institute of Technology, Management and Gramothan, Jaipur, India A. Saleem ZHCET Aligarh Muslim University, Aligarh, India Shrikant Salve MIT Academy of Engineering, Pune, India; Indian Institute of Technology Guwahati, Guwahati, India Urmi Salve Department of Design, Indian Institute of Technology Guwahati, Guwahati, India J. Sanjog Department of Mechanical Engineering, Shepherd Institute of Engineering and Technology (SIET), Sam Higginbottom University of Agriculture, Technology and Sciences (SHUATS), Allahabad, Uttar Pradesh, India Premjit Khanganba Sanjram Human Factors & Applied Cognition Lab, Indian Institute of Technology Indore, Indore, India Tanaya Santra Human Performance Analytics and Facilitation Unit, University Colleges of Science and Technology, University of Calcutta, Kolkata, India
Editors and Contributors
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P. Saraswat Department of Mechanical Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, India Shantanu Saraswat Department of Mechanical Engineering, Zakir Husain College of Engineering and Technology, Faculty of Engineering & Technology, Aligarh Muslim University, Aligarh, UP, India K. Saravanamuthu Concord Stars Contracting LLC LTD, Dubai, UAE S. Sashank Department of Mechanical Engineering, SASTRA Deemed to be University, Thanjavur, India Ayush Saxena Department of Mechanical Engineering, SET, IFTM University, Moradabad, UP, India Vishal Saxena Department of Mechanical Engineering, SET, IFTM University, Moradabad, UP, India Kelifa Seid Department of Design, Indian Institute of Technology Guwahati, Guwahati, India Marwan Shaiban Department of Biomedical Engineering, Osmania University, Hyderabad, India Rohit Shandley Division of MPAE, Netaji Subhas Institute of Technology, New Delhi, India Mukherjee Shankarashis Department of Physiology, University College of Science and Technology, Kolkata, West Bengal, India Chaitanya Sharma Rustamji Institute of Technology, BSF Academy Tekanpur, Gwalior, India Deevesh Sharma Department of Mechanical Engineering, Malviya National Institute of Technology Jaipur, Jaipur, Rajasthan, India Monica Sharma Department of Management Studies, Malviya National Institute of Technology Jaipur, Jaipur, Rajasthan, India Nidhi Sharma Department of Mechanical Engineering, Greater Noida Institute of Technology, Greater Noida, India Nikita Sharma Psychophysiology Laboratory, Department of Humanities and Social Sciences, Indian Institute of Technology, Bombay, Powai, India Vikas Sharma Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Vishwdeep Sharma Rustamji Institute of Technology, BSF Academy Tekanpur, Gwalior, India Suha K. Shihab Department of Materials Engineering, College of Engineering, University of Diyala, Diyala, Iraq
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Editors and Contributors
Ketan Shimpi MAEER’s MIT Institute of Design, Pune, India Vinod Shinde Vishwakarma Institute of Technology (VIT), Pune, India Devyani Shirole User Experience Design Department, MIT Institute of Design, Pune, India N. S. Shobha Department of Industrial Engineering & Management, Rashtreeya Vidyalaya College of Engineering, Bengaluru, India A. K. Shrivastava Indira Gandhi Krishi Vishwavidyalaya, SG College of Agriculture and Research Station, Jagdalpur, Chhattisgarh, India Arshad Noor Siddiquee Department of Mechanical Engineering, Jamia Millia Islamia (A Central University), New Delhi, India M. A. Siddiqui Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Reshma Yasmin Siddiquie Mechanical Engineering Department, IIT Bombay, Mumbai, India Ajita D. Singh Professor, Department of Sports Sciences, Punjabi University, Patiala, Punjab, India Ashish Kumar Singh Malaviya National Institute of Technology, Jaipur Rajasthan, India Bharat Singh Malaviya National Institute of Technology, Jaipur Rajasthan, India Gajendra Singh Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, India Greesh Kumar Singh Institute of Engineering and Technology, Dr. B. R. Ambedkar University, Agra, India P. Singh Department of Mechanical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, (Deemed University) Dayalbagh, Agra, India Rashmi Singh Department of Home Science, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Shalini Singh AIMA-AMU, New Delhi, India S. Singhal ZHCET Aligarh Muslim University, Aligarh, India Sathish Kumar Sivasankaran RBG Lab, Department of Engineering Design, IIT Madras, Chennai, India S. Srivastava Department of Mechanical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, (Deemed University) Dayalbagh, Agra, India
Editors and Contributors
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Sanjay Srivastava Industrial Kinesiology Lab, Department of Mechanical Engineering, Dayalbagh Educational Institute (Deemed University), Dayalbagh, Agra, India K. N. Subramanya Department of Industrial Engineering & Management, Rashtreeya Vidyalaya College of Engineering, Bengaluru, India Das Suman Department of Production Engineering, Jadavpur University, Kolkata, West Bengal, India Amal Sunny Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode, India V. Suresh Department of Design and Automation, School of Mechanical Engineering, VIT University, Vellore, Tamil Nadu, India Faisal Talib Department of Mechanical Engineering, Zakir Husain College of Engineering and Technology, Faculty of Engineering & Technology, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Mohd. Tariq Department of Orthodontics and Dentofacial Orthopedics, Aligarh Muslim University, Aligarh, U.P, India V. K. Tewari Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India N. S. Thakur Department of Mechanical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, (Deemed University) Dayalbagh, Agra, India Tara Thomas Department of User Experience Design, MAEER’s MIT Institute of Design, Pune, Maharashtra, India Manoj Tiwari National Institute of Fashion Technology, Jodhpur, India Kanika Tuteja Department of User Experience Design, MAEER’s MIT Institute of Design, Pune, Maharashtra, India Vikas Upadhyay Department of Mechanical Engineering, National Institute of Technology Patna, Patna, India Ahmad Raza Usmani Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, U.P, India Devika Vipin Vaidya S.N.D.T Women’s University, Mumbai, India A. Varshney ZHCET Aligarh Muslim University, Aligarh, India Mehul Varshney Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India Indresh Verma Ergonomics Laboratory, Department of Design, Indian Institute of Technology Guwahati, Guwahati, Assam, India C. Vigneshkumar Indian Institute of Technology Guwahati, Assam, India
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Editors and Contributors
Mohd Atif Wahid Department of Mechanical Engineering, Jamia Millia Islamia (A Central University), New Delhi, India Issam Wajih Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India Amare Wibneh Department of Design, Indian Institute of Technology Guwahati, Guwahati, India Ashish Yadav Industrial Kinesiology Lab, Department of Mechanical Engineering, Dayalbagh Educational Institute (Deemed University), Dayalbagh, Agra, India Ashutosh Yadav Department of Mechanical Engineering, Zakir Husain College of Engineering and Technology, Faculty of Engineering & Technology, Aligarh Muslim University, Aligarh, UP, India Manish Yadav Industrial Kinesiology Lab, Department of Mechanical Engineering, Dayalbagh Educational Institute (Deemed University), Dayalbagh, Agra, India Pradeep Yammiyavar Indian Institute of Technology Guwahati, Guwahati, India Syed Ali Zaheen Department of Mechanical Engineering, Zakir Husain College of Engineering & Technology, Faculty of Engineering & Technology, Aligarh Muslim University, Aligarh, UP, India
Satyan Steering Gear Sathyanesan T. Narayanan
Abstract This paper deals with the working, analysis, comparison of output with ideal case and application of Satyan Steering Gear devised by the author. Satyan Steering Gear (SSG) eliminates the drawbacks of Ackermann mechanism and Davis mechanism. SSG is a new and totally different simple mechanism satisfying the Fundamental Equation of Correct Gearing (FECG).
1 Introduction Steering gear is a mechanism that enables the driver to guide vehicle along a road efficiently. It is a combination of components or links. Slip between wheel–tire and road results in increased wear and loss of energy and control. When a vehicle moves on straight road, slip between tire and road can be taken as absent. To make sure that all the four wheels of an ordinary vehicle roll without slipping on the road when the vehicle takes a curve, they should have a common instantaneous center which depends on the curve the vehicle takes and may change from instant to instant. The inner wheels have to travel less distance compared to the outer wheels. FECG is formulated based on this principle and is the ideal case, as there is no slip. (Figures show arrangements only and are drawn not to scale.) When a vehicle takes a left turn as shown in Fig. 1, FECG gives cotφ − cotθ =
w b
(1)
Here, w = track width, b = wheel base, φ = angle turned by right wheel or stub axle, and θ = the angle turned by left wheel or stub axle. The equation is equally valid for right turn also when modified to cot θ − cot φ = wb . In Fig. 1, A and B are king-pins and I is the instantaneous center. Then, steering gear is a mechanism to S. T. Narayanan (B) Mechanical Engineering, Govt. Engineering College, Aswathy, Metro Street, Govt. Engg. College P.O, Thrissur, Kerala 680 009, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_1
1
2
S. T. Narayanan
Fig. 1 Ideal steering gear of automobile
Table 1 Fundamental equation of correct gearing—Eq. (1) F
1
θ
1.01 2.04 3.1
4.17 5.27 6.40 7.55 8.72 9.92 11.1
θ –F
0.01 0.04 0.1
0.17 0.27 0.39 0.55 0.72 0.92
1.14
1.24
1.67
1.98
2.31
(θ – 0.01 0.02 0.03 0.04 0.05 0.07 0.08 0.09 0.10 F)/F
0.11
0.11
0.14
0.15
0.16
θ/F
1.11
1.11
1.14
1.52
1.16
2
3
4
5
6
7
8
9
1.01 1.02 1.03 1.04 1.05 1.07 1.08 1.09 1.10
10
11
12
13
14
12.4
13.67 14.98 16.3
produce wheel-tilt angles φ and θ such that Eq. (1) is satisfied. The instant steering wheel is turned, instantaneous center changes, φ takes the value φ i and θ takes the value θ i . Practically, there is a wide variation in the values of wheel base b. For example, compare the wheel bases of ‘Nano’ car and a passenger bus. In the typical example considered here, w = 1450 mm and b = 2440 mm. These values give w/b = 1450/2440 = 0.594. For a left turn, FECG becomes cot φ − cot θ = 0.594. For this left turn, let φ = 12°, the corresponding value of θ = 13.67°. Values of θ corresponding to the values of φ from 1 to 14 are given in Table 1. Referring to Table 1 (for left turn) and examining the values of (θ/φ), it is clear that when vehicle takes a curve θ = φ and (θ/φ) > 1. Also, as φ increases, (θ/φ) and (θ – φ) increase.
2 Basic Mechanical Steering Gear in Use at Present The basic mechanical steering gear employed at present is either Ackerman mechanism or Davis mechanism.
Satyan Steering Gear
3
Ackerman steering gear does not fulfill FECG in all curves on the road. Mechanism is in the back of front wheels. It consists of turning pairs, so produces less friction and wear. It gives position of correct gearing (a) when vehicle moves straight, and (b) when vehicle moves a correct angle to the right and left. At other angles, slip between wheel-tire and road occurs [1]. Davis steering gear fulfills FECG at all positions, but the mechanism comes in front of front wheels. It consists of sliding pairs which may be subjected to wear and so faulty operation in due course [3].
3 Application of FECG on Roads Straight and Curved Let a vehicle moves on a straight road. Now consider the gear train shown in Fig. 2a. Let the ‘controlling pinion’ (spur type with diameter, d) be at the center of track width w. L and R are two spur gear sectors meshing with controlling pinion on diametrically opposite points, and their extensions firmly connected to stub axles as shown in Fig. 2a, b. Let φ be the angle turned by right wheel and θ the angle turned by the left wheel. When the vehicle moves on a straight road, φ = θ = 0. The radii of the two gear sectors measured from the respective king-pin are same, i.e., Lr0 = Rr0 = (w–d)/2. When the controlling pinion turns clockwise, sense of right and left wheel-tilts as shown in Fig. 2b is for left turn. For right turn, the controlling pinion turns counter-clockwise, and sense of right and left wheel-tilts is reversed (not shown). Now consider vehicle has to take a left turn as shown in Fig. 2b. The driver turns the steering wheel to the left (counter-clockwise). This rotation of steering wheel is transferred to the controlling pinion using steering-column-pinion and rack so as to turn the controlling pinion clockwise. Right and left wheel-tilts, φi and θi , are no more zeros. The tangential velocity (t.v) at the two meshing points on the controlling pinion is equal and opposite. That is, φi × Rri = θi × Lri . (b) Requirement (b) given above necessitates (θi /φi ) = (Rri /Lri ). (c)
Fig. 2 a Vehicle moves on straight road, Lr0 = Rr0 . b Vehicle takes a left turn. Lri < Rri
4
S. T. Narayanan
In Table 1, it may be seen that (θi /φi ) > 1 and as (i) increases, ratio (θi /φi ) increases. (d) But track width w = Rri + Lri + d. (e) where d = fixed diameter of the controlling pinion. As (i) increases, Rri is to be increased and Lri to be decreased for satisfying conditions (c), (d) and (e) when taking a left turn. For this left turn, controlling pinion is to be moved left, Lri decreasing and Rri increasing, magnitude depending on the amount of left turn. Similarly for a right turn, Rri is to be decreased and Lri to be increased and for these, controlling pinion is moved right, the magnitude depending on the amount of right turn.
4 Satyan Steering Gear Now the search is for a mechanism to satisfy the requirements (1), (c), (d) and (e). Satyan Steering Gear (SSG) devised by the author is a totally different simple mechanism, when compared to Ackermann or Davis mechanism. Details of ‘controlling pinion console’ used in SSG are shown in Fig. 3. A rack driven by steering-column-pinion motivates pinion G1 connected to the controlling pinion through a compound gear-shaft H1 . Console frame is free to move parallel to the line joining king-pins on anti-friction bearing. Controlling pinion meshes with racks R and S. These are firmly connected to stub axles as shown in Fig. 5 which represents the configuration of steering gear when it takes a left turn. SSG is an all-gear mechanism with turning and rolling pairs only. It satisfies the Fundamental Equation of Correct Gearing (FECG) in all curves on the road. It does not come in
Fig. 3 Mechanism of Satyan Steering Gear
Satyan Steering Gear
5
Fig. 4 Configuration of Satyan Steering Gear when vehicle moves on a straight road
Fig. 5 Configuration of Satyan Steering Gear when vehicle takes a left turn
front of the front wheels. Design of SSG satisfies requirements (1), (c), (d) and (e) (Fig. 4).
5 Theoretical Analysis of the Mechanism Theoretical treatment is given in the Appendix. As the controlling pinion turns, the number (n) of the tooth in mesh with the racks varies. Table 2 gives the values φ from Eq. (6a) and values θ from Eq. (10a). φ=
n.π.m cos β [r + (d/2). tan β × sin β] + 0.5.n.π.m. sin β
(6a)
θ=
n.π.m. cos β [r + (d/2). tan β × sin β] − 0.5.n.π.m. sin β
(10a)
6
S. T. Narayanan
Table 2 Performance of Satyan Steering Gear—Eqs. (6a) and (10a) n
0.5
F
1.004 1.999 3.964 5.894 7.791
1
2
3
4
θ
1.013 2.036 4.109 6.22
θ –F
0.009 0.036 0.145 0.326 0.58
5
6 9.655 11.49
8.371 10.56
8
9
10
15.06
16.80
18.52
15.07
17.39
19.75
22.16
0.907
1.307
1.781
2.329
2.95
3.65
(θ – 0.009 0.018 0.036 0.055 0.074 F)/F
0.094
0.114
0.134
0.155
0.176
0.197
θ/F
1.094
1.114
1.134
1.155
1.176
1.197
1.009 1.018 1.036 1.055 1.074
12.79
7 13.29
Fig. 6 Performance curves of SSG and FECG compared
6 Performance of Satyan Steering Gear Parameters: w/b = 0.594, β = 27°, m = 8 mm and d = 200 mm. The values of θ are plotted against values of φ to give the performance curve of Satyan Steering Gear—curve identified by ◯-◯-◯. This curve agrees very well with the plot of the Fundamental Equation of Correct Gearing—curve identified by -- as shown in Fig. 6.
7 Discussion 1. Performance of Satyan steering gear Performance characteristics of Satyan Steering Gear are understood from Table 2 and is identified by ◯-◯-◯ in Fig. 6. Fundamental Equation of Correct Gearing
Satyan Steering Gear
7
is understood from Table 1 and is identified by --. Values of θ from Tables 1 and 2 for different values of φ are compared which show very good agreement. That is, the performance exhibited by Satyan Steering Gear is very close to the required ideal one given by the Fundamental Equation of Correct Gearing. 2. Effect of wheel base b on angle θ for constant angle φ The track width w of a vehicle has to comply with the width of the road. Generally, wheel base b is selected liberally to some extent. The effect resulting from equation for correct gearing, when wheel base is increased and the vehicle takes the same curve (Fig. 7), is understood from Table 3. Values of (θi ) are computed using Eq. (1) keeping φ = 15°. (θi ) are plotted against wheel base b for constant φ. The variation of θ is seen asymptotic to φ = 15°. The corresponding changes in the values of angle β computed from Eq. (12) also are shown in Table 3. 3. Rack angle β of steering gear for a given wheel base b. Fundamental Equation of Correct Gearing, Eq. (1), cotφ – cotθ = w/b, is used to compute the values of θ corresponding to the values of φ in the required range. Average of (θ/φ) for the required range can be computed from Table 1. This may be used in Eq. 12 given below to compute β. Ratio of angles, (θ/φ) =
[r + (d/2). tan β × sin β] + 0.5n.π.m. sin β [r + (d/2). tan β × sin β] − 0.5n.π.m. sin β
(12)
Fig. 7 Variation of θ when wheel base is increased and vehicle takes the same curve, keeping F = 15°
Table 3 Values of θ & β when wheel base b changes keeping F = 15° Track width w
F
bi
w/bi
θi (°)
θi /F
β (°)
1450 mm
15°
1 × 2440 = 2440 mm
0.594
17.675
1.178
27
“
“
2 × 2440 = 4880 mm
0.297
16.231
1.082
14.4
“
“
3 × 2440 = 7320 mm
0.198
15.8394
1.0559
10.1
“
“
4 × 2440 = 9760 mm
0.1485
15.592
1.0395
6.9
“
“
5 × 2440 = 12 2400 mm
0.1188
15.47
1.0313
5.5
8
S. T. Narayanan
4. ‘Controlling pinion console’ Fig. 3 The console can move parallel to the track width AB to accommodate the movement CC1 as given by Eq. (7). When the controlling pinion turns, the radial distance from king-pin to the point of engagement of controlling pinion with rack (AP6 or BO6 ) increases on one side and decreases on the other side. This is how values of φ and θ become different. 5. Ergonomics Theory of Satyan Steering Gear is in the establishing stage. Basically, it is an all-gear mechanism, and gear trains can be manufactured with high efficiency. Number of elements is less compared to other mechanisms. The number of parameters enables to design for comfort, efficiency, safety and productivity.
8 Conclusion 1. Tables 1 and 2 for different values of φ are compared in Fig. 6. This shows very good agreement indicating that Satyan Steering Gear provides the correct gearing relations. 2. Different arrangements are possible with the elements of Satyan Steering Gear. 3. It may be noted that when controlling pinion turns clockwise, the vehicle takes a left turn (i.e., moves counter-clockwise) 4. The angle ψ for the shown configuration taken as example is 4.245°. 5. 5.The approximations adopted in Eqs. 6a and 10a simplify computation and induce an error which increases with wheel turn angles and is approximately + 3.6% for φ and +3.53% for θ corresponding to n = 9. 6. Parameters used in the example require 6.56° rotation of controlling pinion to produce 1° turning of wheel (6.56: 1). 7. Steering ratio = Turn of steering wheel in degrees/Turn of wheel in degrees and is usually between 12:1 and 35:1[2]. In modern cars, steering ratio is 12:1 to 20:1. 8. Required steering ratio may be obtained by suitably designing pinion G1 and/or pinion G0 on steering column. Tabulation for determination of angles turned by Racks. LEFT TURN (Fig. 3). Pinion or rack
Pinion G0 on steering column
Pinion G1 on compound shaft
Controlling pinion G
Rack R
Rack S
No. of teeth
T0
T1
T
–
–
Module
m0
m1
m
m
m
Angle turned
γ0 −ve
γ1 + ve
γ = γ1 + ve
φ
θ
γ1 = γ0 × T0 /T1 . Since G1 meshes with the rack on its other side, G1 can have a module other than m0 . Here assume m1 = m0 . Angle turned by controlling pinion
Satyan Steering Gear
9
G, γ = γ1 + ve. = n × pc /(d/2) = 2.π.m.n/d = γ0 × T0 /T1 , where n = number of teeth turned and pc = circular pitch = π × m (Fig. 3). Then, (π.m.n) = γ0 × d/2 × T0 /T1 . Now substituting for (π.m.n) in the numerator of Eq. 6a, γ0 (T0 /T1 )
d
× cos β 2 d φ= r + 2 tan β × sin β + 0.5.nπ m. sin β
(13)
Steering ratio = Turn of steering wheel in degrees/Turn of wheel in degrees = γ0 /φ, and this can be computed using Eq. 13. Steering ratio r + d2 tan β. sin β + 0.5.n.π.m sin β γ0 = d T0 φ . cos β 2
(14)
T1
9.
Movement of controlling pinion console parallel to the track AB is CC1 (or h). Corresponding to a turn angle of 19.754°, it is 102.69 mm. 10. For practical applications, the arrangements of links shown require modifications to limit the size of steering gear mechanism. 11. Steering gear mechanism together with the driver constitutes a feedback system, and as the driver continuously monitors the vehicle, the error introduced by simplification of equation may become compensated. Acknowledgements Certified that the above manuscript titled ‘Satyan Steering Gear’ is my own genuine work that there are no co-workers, that the matter contained under the title is not published till date and that this work did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.
Appendix Theoretical analysis (Satyan Steering Gear) Considering the triangles CO2 O and CO3 O, created by pinion and rack S in Fig. 4. ∠O2 CO = ∠CO3 O = β. Then CO = d/(2.cosβ) and the length B O = r = BC−C O = w/2 − d/(2.cosβ)
(1a)
where w = AB = track width. O2 represents the point where the controlling pinion and rack S make contact. Also OO2 = (d/ 2).tanβ. OO4 is an arc with radius r and center B. It is taken as straight line as ∠O B O4 = ψ is small and the radius BO is large. As angle ∠O2 OO4 is very closely equal to β,
10
S. T. Narayanan
O4 O2 = O O2 × sinβ = (d/2) × tanβ × sinβ
(2)
O O4 = (d/2).tanβ × cosβ andB O2 = r + (d/2).tanβ × sinβ
(2a)
When the vehicle moves on a straight road, the pinion meshes with the right rack S at a point O2 and the left rack R at a point P2 and the stub axles make zero angle with AB and this is the initial position, Fig. 4. From triangles, OO2 O4 and BOO4 , (d/2).tanβ × cosβ = r × ψ giving, ψ=
(d/2) × tan β × cos β r
(3)
When the controlling pinion turns through n teeth clockwise, arc length turned by it is equal to n × pc where pc = circular pitch = π × m. Angle turned through by pinion, γ = n × pc /(d/2). Angle turned through by right rack S is φ. Let a distance O2 O6 , on the rack S is equal to arc length traversed by pinion, n × pc . This distance can be resolved into (n × pc × cosβ) = v, component perpendicular to AB and (n × pc × sinβ) = h, component parallel to AB, Fig. 4. The component of O2 O6 perpendicular to BO2 is very closely equal to n × pc × cosβ × cosψ. The arc O2 O7 cuts the radii BO2 and BO6 . O2 O7 is taken a straight line. Then, ∠O6 O2 O7 = β + ψ and O7 O6 = n × pc × sin(β + ψ). Radius BO6 = BO2 + O7 O6 = r +(d/ 2).tanβ × sinβ + n × pc × sin(β + ψ). Let the average of radii, BO2 and BO6 be BO8 . Then BO8 = r + (d/2).tanβ × sinβ + 0.5 × n × pc × sin(β + ψ).
(4)
Rack S together with its stub axle can turn about king-pin B. Angle turned by rack S, φ = [n × pc × cosβ × cos(ψ + φ/2)]/[r + (d/2).tanβ × sinβ + 0.5 × n × pc × sin(β + ψ)].
(5)
In terms of module, m angle φ=
n.π.m. cos β × cos(ψ + φ/2) [r + (d/2) tan β × sin β] + 0.5n.π.m. sin(β + ψ)
(6)
Angles ψ and φ/ 2 are small, so sin(β + ψ) may be approximated to sinβ and cos(ψ + φ/2) to 1. Then, angle through which right wheel turns, φ=
n.π.m. cos β [r + (d/2) tan β × sin β] + 0.5n.π.m. sin β
(6a)
Satyan Steering Gear
11
As shown in Fig. 5, movement of the controlling pinion console parallel to track AB, CC1 = π.n.m.sinβ = h.
(7)
Referring to the left rack R of the steering gear, AP = r = (w/2) – d/ (2.cosβ). (Similar to Eq. 1a) AP2 = r + (d/2).tanβ ×sinβ. (Similar to Eq. 2a) P2 represents the point where controlling pinion and rack R make contact. When the controlling pinion turns through n teeth clockwise, arc length turned is equal to n × pc . Angle turned through by pinion, γ = n × pc /(d/2). Angle turned through by the left rack R about A is θ. Let P2 P6 be the distance traversed by left rack. Then, P2 P6 = n × pc . P2 P7 is an arc with radius AP2 and is taken a straight line. In the triangle P6 P2 P7 , ∠ P6 P2 P7 = β + ψ. Then, AP6 = AP7 − P7 P6 = AP2 − n × pc × sin(β + ψ) = r + (d/2).tanβ × sinβ − n × pc × sin(β + ψ).
(8)
Rack R together with its stub axle can turn about king-pin A. Let the average of radius of AP2 and AP6 be AP8 . Then, A P8 = [r + (d/2). tan β × sin β − 0.5 × n × pc × sin(β + ψ)].
(8a)
Angle turned by left rack R, θ = [n × pc × cos β × cos(ψ + θ/2)]/[r + (d/2). tan β × sin β −0.5 × n × pc × sin(β + ψ)].
(9)
That is, angle through which left wheel turns, θ=
n.π.m. cos β × cos(ψ + θ/2) [r + (d/2) tan β × sin β] − 0.5n.π.m. sin(β + ψ)
(10)
∠ψ and ∠θ/2 are small, so sin(β + ψ) may be approximated to sinβ and cos(ψ + θ/2) to 1. Then θ=
n.π.m. cos β [r + (d/2) tan β × sin β] − 0.5n.π.m. sin β
(10a)
Difference in tilt angles, (θ − φ) =
0.5.n 2 , π 2 .m 2 . sin 2β [r + (d/2). tan β × sin β]2 − [0.5n.π.m. sin β]2
(11)
12
S. T. Narayanan
Also the ratio of angle, (θ/φ) =
[r + (d/2. tan β × sin β] + 0.5n.π.m. sin β [r + (d/2). tan β × sin β] − 0.5n.π.m. sin β
(12)
References 1. Rattan, S.S.: Theory of Machine, Third Edition, 13th reprint 2012 Tata McGraw Hill Education Private Limited, New Delhi (2009). pp. 195–198 2. Singh, K.: Automobile Engineering, Vol. 1. 14th Edition, Standard Publishers Distributers, 1705-B, Nai Sarak, Delhi-110006 (2017). pp. 247 3. https://scribd.com/doc/100487707/Davis-Steering-Gear-Mechanism-uploaded by Vidhu Kampurath P on Jul 19, 2012
Enhancing Walking Stability of Foot Deformities Patients by 3D-Printed Ankle Foot Orthosis Harish Kumar Banga, R. M. Belokar, Parveen Kalra, and Rajesh Kumar
Abstract This research found that to get mechanical properties of lower leg foot orthoses, a system is developed through three-dimensional (3D) advances. A handheld versatile 3D laser scanner is utilized for producing 3D work geometry immediately from patient’s lower appendage. Therefore, 3D-printable orthotic configuration is delivered by the rough enter rendition. Custom fitting is outfitted in PC helped 3D environment. Particular laser sintering (SLS) technique in additive manufacturing (AM) innovation is utilized to create the 3D-printable Ankle Foot Orthosis (AFO) model. Polymer characterization checks are finished on additive manufactured take a look at specimens consistent with the recognized standards. The take a look at outcomes are then loaded in Material Library of Finite Element Analysis (FEA) software. Simulations for specific specimens in FEA environment are finished for evaluating the consequences obtained from stable and additive synthetic AFO fashions. It is proposed in this paper that if the mechanical houses of additive synthetic items acquired from bodily exams are defined in material library of FEA software program, numerous simulations for exceptional sorts of specimens may be finished in laptop surroundings with higher. Keywords Ankle Foot Orthosis (AFO) · Clinical gait analysis · Finite Element Analysis (FEA) · Foot drop
1 Introduction An AFO might be utilized for foot drop when medical procedure is not justified or amid careful or neurologic recuperation. The particular motivation behind an AFO is to give toe dorsiflexion amid the swing stage, average or sidelong dependability H. K. Banga (B) · R. M. Belokar · P. Kalra Production & Industrial Engineering Department, PEC University of Technology, Chandigarh, India e-mail: [email protected] R. Kumar Mechanical Engineering Department, UIET, Panjab University Chandigarh, Chandigarh, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_2
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Fig. 1 Causes of foot drop (Web source www.epaina ssist.com)
at the lower leg amid position, and, if fundamental, pushoff incitement amid the late position stage. An AFO is useful just if the foot can accomplish plantigrade position when the patient is standing. Any equinus contracture blocks its fruitful use. The most ordinarily utilized AFO in foot drop is built of polypropylene and supplements into a shoe. On the off chance that it is cut to fit foremost to the malleoli, it gives unbending immobilization. This gadget is utilized when lower leg precariousness or spasticity is risky, just like the case in patients with upper engine neuron maladies or stroke. On the off chance that the AFO fits back to the malleoli (back leaf spring type), plantarflexion at impact point strike is permitted, and pushoff restores the foot to impartial for the swing stage. This gives dorsiflexion help with occurrences of flabby or mellow spastic equinovarus disfigurement. A shoe-fasten orthosis that connects specifically to the heel counter of the shoe additionally might be utilized. An examination by Menotti et al. proposed that front AFOs are associated with lower vitality expenses of strolling and more elevated amounts of apparent solace than back AFOs are and in this way may enable individuals with foot drop to walk longer separations while using less physical exertion as appeared in Fig. 1.
1.1 The Right AFO for Every Patient The impact of AFOs on walk has been extensively thought about, regardless, there is no indisputable verification with reference to their ampleness. Diverse examinations have evaluated the consequences of wearing an AFO at the kinematics and vitality of step, strolling pace, security, and the power advantage of walking. An impressive part of the above-referred to ponders has referenced on the supportive consequences of wearing an AFO; however, others referenced no focal points of the AFO. Ace gatherings of the ISPO and the outcomes generally reviews affirm the nonattendance of unambiguous verification with reference to the suitability and working frameworks of AFOs [1, 2]. Ankle and foot motion.
Enhancing Walking Stability of Foot Deformities Patients …
15
Fig. 2 Ankle movements. a Dorsiflexion and b plantarflexion
1. Flexion and development happen in the sagittal air ship. At the decline leg joint, these upgrades are known as dorsiflexion and plantarflexion, autonomously (see Fig. 2); 2. Snatching and adduction happen inside the frontal plane; three. Inside and outside turns, besides called regular and parallel pivot, occur inside the transverse plane plantarflexion [3]. The lower leg joint is a basic weight bearing flip joint interfacing the foot to the leg and normally liable for dorsiflexion (feet up, impact point down) (see Fig. 2a) and plantarflexion (feet down, impact point up) (see Fig. 2b). Regardless, it moreover permits a moderate advancement inside the transverse air ship amid plantarflexion, understanding feebleness in the meantime as in this capacity. The lower leg joint is fundamental to the regular development, and the base volume of enhancement basic for a dull walk cycle is from 10° of dorsiflexion to 20° of plantarflexion [4–8]
1.2 Gait Data Reference System Walk is a cyclic advancement for which certain discrete occasions have been characterized as fundamental. As a rule, the walk cycle is depicted as a period range from the explanation behind starting contact (likewise suggested as foot contact) of the patient’s foot with the ground to the going with inspiration driving starting contact for that proportional furthest point. Partitioning the walk cycle into position and swing stages is the point in the cycle where the position part leaves the ground, dropped toe or foot off. Step factors that change after some time, for example, the patient’s joint
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correct removals are ordinarily appeared clinical examination as a part of the person’s walk cycle. This is done to empower the association of various strolling primers and the utilization of a reference database from a sorted out, normal populace [9–11] (Fig. 3; Table 1).
Fig. 3 Clinical gait analysis laboratory
Table 1 Typical gait data collection protocol Test component
Approximate time (min)
Pretest tasks: test explanation to the adult patient or the pediatric patient and parent, system calibration
10
Videotaping: brace, barefoot, close-up, standing
5–10
Clinical examination: range of motion, muscle strength, etc.
15–30
Motion marker placement
15–20
Motion data collection: subject calibration and multiple walks, per test condition (barefoot and orthosis)
10–60
EMG (surface electrodes and fine wire electrodes)
20–60
Data reduction of all trials
15–90
Data interpretation
20–30
Report dictation, generation, and distribution
120–180
Enhancing Walking Stability of Foot Deformities Patients …
17
1.3 Additive/Rapid Prototype Technology There are two basic sorts of rapid prototyping (RP) accessible, included substance and subtractive. Included substance demonstrating takes in the wake of building a figure from mud, including material until the final shape is passed on. Subtractive showing begins with a touch of material, and a cutting device expels material until the final shape is made. This is a kind of CNC machining. Roland DGA utilizes the term SRP™ (subtractive quick prototyping) to portray its CNC machines and PC helped making (CAM) structures that are advanced for prototyping [12], as opposed to introduce day CNC for period machining. Another articulation for smart prototyping is the more expansive term robotized creation. ‘Mechanized creation is an impelled assembling of advancements that convey three-dimensional, strong contradictions under PC control’ [13–15].
2 Methodology 2.1 Manufacturing Techniques of AFO The process will be used to create orthotic devices in additive manufacturing. Computer-assisted design (CAD) systems have also being used to assist in creating the positive improving consistency and repeatability of this process, but the process remains slow and complex and it requires considerable input from experienced craftsmen. Furthermore, in these traditional processes the possibilities for innovation or product development are limited. With CAD systems, it will be observe that orthoses rejection ratio has been reduced combined with time reduction up to 50% and cost saving up to 2–50% [16–19] as shown in Figs. 4, 5 and 6.
2.2 Gait Analysis of Foot Drop Patients Cadence is the rate at which a person walk, expressed in steps per minute. The average cadence is 100–115 steps/min. Thus, if you let your character take 10 steps in 156–180 frames (using 30 frames/s), the character’s cadence is within a normal range as shown in Fig. 7 Right Foot of Deformity Patients Old and New AFO. The result in Fig. 8a shows that during period of one month improvement in cadence Right Foot of foot drop patient with new AFO as compared to old AFO. Stride length is the distance between the successive heel contact points of the same foot. Normally, stride length = 2 × step length as shown in Fig. 7 Right Foot of Deformity Patients Old and New AFO. The rseult in Fig. 8b shows that during period of one month improvement in stride Right Foot of foot drop patient with new AFO as compared to old AFO.
18
Fig. 4 a Traditional process, b possible AM process
Fig. 5 Measurement of dimensions of foot drop patients leg
H. K. Banga et al.
Enhancing Walking Stability of Foot Deformities Patients …
19
Fig. 6 Foot size of foot drop patients leg model
Fig. 7 GAIT analysis with old and new ankle foot orthosis
Stance phase—the portion of the gait cycle when the foot is in contact with the ground (weight bearing) as shown in Fig. 7 Right Foot of Deformity Patients Old and New AFO. The result in Fig. 8c shows that during period of one month improvement in stance time right Foot of foot drop patient with new AFO as compared to old AFO Swing phase—the portion of the gait cycle when the foot is in the air (non-weight bearing) as shown in Fig. 7 Right Foot of Deformity Patients Old and New AFO. Stride period or Cycle time: The period of time from initial contact of one foot to the following initial contact of the same foot, expressed in seconds (s). The result in Fig. 8d shows that during period of one month improvement in swing Right Foot of foot drop patient with new AFO as compared to old AFO. Step length is the distance between the heel contact point of one foot and that of the other foot. As shown in Fig. 8e Right Foot of Deformity Patients Old and New AFO.
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Fig. 8 a Cadence difference of Right Foot of Deformity Patients Old and New AFO, b stride time difference of Right Foot of Deformity Patients Old and New AFO, c stance time difference of Right Foot of Deformity Patients Old and New AFO, d swing time difference of Right Foot of Deformity Patients Old and New AFO, e step length difference of Right Foot of Deformity Patients Old and New AFO
The histogram in Fig. 8e show that during period of one month improvement in step length in Right Foot of foot drop patient with new AFO as compared to old AFO.
Enhancing Walking Stability of Foot Deformities Patients …
21
Fig. 8 (continued)
3 Results and Discussion: It was concluded that using a 3D laser scanner can provide a high quality of image of scanning for the AFO making purposes comparing to those that used in previous studies. The CAD design tools were suitable to reduce the size of the original, large scan, mesh making and offsetting the mesh in order to make 5 mm thickness for the final AFO design. In exhibit AFO design patients stands up to blood course stream to foot and can’t walk genuinely are being gone up against in the midst of whole deal
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Fig. 8 (continued)
utilize. In the wake of analyzing with patients and orthotist (which supported AFO to father patients). Another strategy of AFO for Foot Drop patients has been made to overcome this issue and constrained part showing up and extend examination has in like manner been performed. Utilization of 3D human accommodating scanner (Artec Eva) to get right estimations of Foot drop Patients. New plan of AFO is made by 3D printing technology (SLS) which is extra time and cost. It examinations the shape and lead of material of current usable AFO and 3D-printed AFO.
References 1. Abboud, R.J.: Relevant foot biomechanics. Curr. Orthoped. 16, 165–179 (2002) 2. Alexander, M.A., Xing, S.Y., Bhagia, S.M.: Lower Limb Orthotics. Webmd Llc. http://Emedic ine.Medscape.Com/Article/314838-Overview#Aw2aab6b5. Accessed 22 Sept 2011 (2011) 3. American Orthotic and Prosthetic Association Inc.: Evidence Note—The Use of Ankle-Foot Orthoses in the Management of Stroke (2008) 4. Boehler, W., Marbs, A.: 3D scanning and photogrammetry for heritage recording: a comparison. In: Proceedings of the 12th International Conference on Geoinformatics, pp. 291–298 (2004) 5. Böhler, W., Marbs, A.: 3D scanning instruments. In: Proceedings of the CIPA WG 6 International workshop on scanning for cultural heritage recording, Ziti, Thessaloniki, pp. 9–1 (2002) 6. Banga, H.K, Belokar, R.M., Madan, R., Dhole, S.: Three dimensional Gait assessments during walking of healthy people and drop foot patients. Defence Life Sci. J. (2017) 7. Banga, H.K., Belokar, R.M., Kalra, P., Madan, R.: Fabrication and stress analysis of ankle foot orthosis with additive manufacturing. Rapid Prototyping J. Emerald Publishing 24(1), 301–312 (2018) 8. Banga, H.K., Belokar, R.M., Kumar, R., A novel approach for ankle foot orthosis developed by three dimensional technologies. In: 3rd International Conference on Mechanical Engineering and Automation Science (ICMEAS 2017), vol. 8, no. 10, pp. 141–145. University of Birmingham, UK (2017) 9. Brackx, B., Van Damme, M., Matthys, A., Vanderborght, B., Lefeber, D.: Passive ankle-foot prosthesis prototype with extended push-off. Int. J. Adv. Robot. Syst. (2012)
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10. Bennett, B.C., Russell, S.D., Abel, M.F.: The effects of ankle foot orthoses on energy recovery and work during gait in children with cerebral palsy. Clin. Biomech. (Bristol, Avon). 27(3), 287–291(2012) 11. Bregman, D.J.J., Rozumalski, A., Koops, D., De Groot, V., Schwartz, M., Harlaar, J.: A new method for evaluating ankle-foot orthosis characteristics: bruce. Gait Posture 30, 144–149 (2009) 12. Bregman, D.J.J., Van Der Krogt, M.M., De Groot, V., Harlaar, J., Wisse, M., Collins, S.H.: The effect of ankle foot orthosis stiffness on the energy cost of walking: a simulation study. Clin. Biomech. (Bristol, Avon) 26, 955–961 (2011) 13. Brehm, M.A., Harlaar, J., Schwartz, M.: Effect of ankle-foot orthoses on walking efficiency and gait in children with cerebral palsy. J. Rehabil. Med. 40, 529–534 (2008) 14. Bowker, P.: Biomechanical Basis of Orthotic Management. Butterworth-Heinemann, Oxford, England, Boston (1993) 15. Chen, C.L., Yeung, K.T., Wang, C.H., Chu, H.T., Yeh, C.Y.: Anterior ankle-foot orthosis effects on postural stability in hemiplegic patients. Arch. Phys. Med. Rehabil. 80, 1587–1592 (1999) 16. Chu, T.M.: Determination of peak stress on Pp Afo’s due to weight change using strain gage technology. Exp. Tech. 24, 28–30 (2001). Chu, T.M.: Biomechanics of ankle-foot orthoses: past, present, and future. Top. Stroke Rehabil. 7, 19–28 (2000) 17. Chu, T.M., Feng, R.: Determination of stress distribution in various ankle- foot orthoses: experimental stress analysis. JPO: J. Prosth. Ortho. 10, 11–16 (1998) 18. Chu, T.M., Reddy, N.P.: Stress distribution in the ankle-foot orthosis used to correct pathological gait. J. Rehabil. Res. Dev. 32, 349–360 (1995) 19. Chu, T.M., Reddy, N.P., Padovan, J.: Three-dimensional finite element stress analysis of the polypropylene, ankle-foot orthosis: static analysis. Med. Eng. Phys. 17, 372–379 (1995)
Analyzing the Important Factors Causing Fatigue in Industrial Workers Using Fuzzy MCDM Technique Noor Zaman Khan, Reshma Yasmin Siddiquie, Suha K. Shihab, Arshad Noor Siddiquee, and Zahid A. Khan
Abstract There are several factors that cause fatigue in industrial workers due to which they feel inhibited and their activities are impaired. Fatigued workers have no willingness to perform either physical or mental tasks because they feel heavy, lethargic and exhausted. Identifying the important fatigue-causing factors as well as the direction of cause–effect relation between them can help in managing and controlling the factors leading to fatigue in industrial workers. The impact of the factors can be evaluated on the basis of the expert opinion with the application of fuzzy multistage grading scale. In this paper, an attempt has been made to use fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to analyze the relationship between factors causing fatigue in industrial workers. Keywords Fatigue · Workers · Fuzzy · DEMATEL
1 Introduction Fatigue refers to the conditions which lead to lessening in the efficiency and desire of the workers to perform the assigned task [1]. In general, fatigue is classified as general fatigue and muscular fatigue. Muscular fatigue occurs due to overstressing of the muscles while working, and it is restricted to the local overstressed muscles causing a lot of pain. General fatigue refers to a situation in which the fatigued person N. Z. Khan (B) Department of Mechanical Engineering, National Institute of Technology, Srinagar, Jammu and Kashmir 190006, India e-mail: [email protected] R. Y. Siddiquie Mechanical Engineering Department, IIT Bombay, Mumbai, India S. K. Shihab Department of Materials Engineering, College of Engineering, University of Diyala, Diyala, Iraq A. N. Siddiquee · Z. A. Khan Department of Mechanical Engineering, Jamia Millia Islamia (A Central University), New Delhi 110025, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_3
25
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N. Z. Khan et al.
feels lazy and exhibits unwillingness to execute the given task [1]. Several factors such as working at night, loss of sleep, heavy work, monotonous nature of work, etc. may cause fatigue among industrial workers. From the literature available on the causes of fatigue and its effects, it is observed that fatigue leads to impaired performance, and safety [2, 3] which in turn adversely affects human productivity. There are several factors that may result in fatigue [1]. Studies related to the workplace fatigue have been carried out focusing on shift or a typical work [4], particular workplace settings [5], and fatigue risk management approaches [6]. The causes of fatigue in the workplace and approaches for its countermeasure have been discussed by Williamson and Friswell [7]. Although our understanding of causes of fatigue is improving, a lot more is required to understand cause–effect relationship between various fatigue causing factors for effective countermeasures and management of their effects. Keeping this in view, an attempt has been made in this paper to develop cause–effect relationship between various fatigue causing factors and also to identify hierarchy of the factors using fuzzy DEMATEL method. Expert assessments are typically used to evaluate the nature of such relationships. To include problems associated with subjective assessment, the fuzzy grading scale is applied, according to which the degree of uncertainty related to the single expert opinion is quantified by the adequate membership function. Models and methods using fuzzy set theory are often applied to support decision process [8–10].
2 Fuzzy DEMATEL Method The DEMATEL is a multicriteria decision-making (MCDM) method used to develop a structural model using the cause–effect relationships among the factors of the system under study. This method involves an efficient process which identifies the hierarchy and relationships among the factors of the considered system. The conventional DEMATEL method assumes that the values and conditions of the factors are certain which is far away from reality. The fuzzy DEMATEL method can overcome this problem as it is an appropriate technique for decision making under uncertainty. This method uses fuzzy linguistic terms to define the variables which in turn simplify the decision making under uncertainty. Fuzzy DEMATEL method is being extensively used by researchers for analyzing the problems pertaining to different fields. In this study, fuzzy DEMATEL method is used to find cause–effect relationship between factors causing fatigue. Six fatigue causing factors: (i) intensity and duration of physical and mental effort (F1), (ii) environments such as heat, humidity, radiation, indoor air quality, light, noise and vibration (F2), (iii) physical problems such as responsibilities, worries or conflicts (F3), (iv) pains and illness (F4), (v) nutrition (F5) and (vi) circadian rhythm (F6) are considered [1]. A typical four-gradual fuzzy grading scale is applied in analyzing the relation between these factors. The form of such grading scale is shown in Fig. 1, where the symbol N means no influence
Analyzing the Important Factors Causing Fatigue in Industrial …
27
Fig. 1 A typical four-gradual fuzzy grading scale adopted in the analysis
(none), L- weak influence (low), H- high influence, and S- extremely strong influence (strong). The steps involved in this method are given below: Step 1: Formulate the fuzzy matrix Z using Eq. (1) ⎡
0 z 12 ⎢ z 21 0 ⎢ Z =⎢ . ⎣ .. : z n1 z n2
... ··· .. .
⎤ z 1n z 2n ⎥ ⎥ .. ⎥ . ⎦
(1)
··· 0
where zij = (l ij , mij , uij ) is a triangular fuzzy number. Step 2: Obtain the normalized fuzzy decision matrix using Eq. (2) ⎡
0 x12 ⎢ x21 0 ⎢ X =⎢ . ⎣ .. : xn1 xn2
... ··· .. .
⎤ x1n x2n ⎥ ⎥ .. ⎥ . ⎦
(2)
··· 0
where x ij = zij ⊗(r ij )−1 and
n rij = max (1≤i≤n) zi j, s j=1
Step 3: Develop the total-relation fuzzy matrix using Eq. (3) T = lim (X + X2 + X3 + · · · + Xn ) = X(1 − X)−1 n→∞
(3)
where T matrix is represented by Eq. (4) ⎡
0 t12 ⎢ t21 0 ⎢ T=⎢ . ⎣ .. : tn1 tn2
... ··· .. .
⎤ t1n t2n ⎥ ⎥ .. ⎥ . ⎦
(4)
··· 0
where t ij = (t ijl, t ijm , t iju ) overall influence rating of decision maker for each criterion i against criterion j.
28
N. Z. Khan et al.
Step 4: Obtain the fuzzy numbers Di , Ri by summing the rows and columns of the sub-matrices t l , t m , t m using Eqs. (5) and (6), respectively. Di =
n
ti j
(5)
ti j
(6)
i=1
Ri =
n j=1
Step 5: Defuzzify the Di and Ri using suitable defuzzification method to produce def def two sets of numbers: Di + Ri which indicate importance of strategic objectives. def def Di and Ri represent strategic cause-and-effect objective. Defuzzification of a triangular number t ij (l,m,u) is done by using Eq. (7). de f ti j
= tmi j
tui2 j + 2.tmi j × tli j − tui j − tli2 j
+ 3 × tui j − tli j
(7)
Step 6: Compute weights of the criteria/factors using Eq. (8). wi =
de f Di
+
de f Ri
2
+
de f Di
−
de f Ri
2 0.5 (8)
Step 7: Determine overall weight of each criterion using Eq. (9). wi Wi = n i=1
(9)
wi
3 Results and Discussion The method explained in Sect. 2 is applied to the response obtained by one expert. The fuzzy decision matrix is given below: ⎡ ⎢ ⎢ ⎢ ⎢ Z=⎢ ⎢ ⎢ ⎣
λ = (1,2,3.25)−1 = (0.31,0.5,1)
0 S H S S L
N 0 N N N N
N L 0 H L H
S H H 0 S L
N L L L 0 L
L L H L L 0
⎤ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎦
Analyzing the Important Factors Causing Fatigue in Industrial … (0,0,0)
(0,0,0.25)
(0.5,0.75,1.0) (0.25,0.5,0.75)
29
(0,0,0.25)
(0.5,0.75,1.0)
(0,0,0.25)
(0,0.25,0.5)
(0,0,0)
(0,0.25,0.5)
(0.25,0.5,0.75)
(0,0.25,0.5)
(0,0.25,0.5)
(0,0,0.25)
(0,0,0)
(0.25,0.5,0.75)
(0,0.25,0.5)
(0.25,0.5,0.75)
(0.5,0.75,1.0)
(0,0,0.25)
(0.25,0.5,0.75)
(0,0,0)
(0,0.25,0.5)
(0,0.25,0.5)
(0.5,0.75,1.0)
(0,0,0.25)
(0,0.25,0.5)
(0.5,0.75,1.0)
(0,0,0)
(0,0.25,0.5)
(0,0.25,0.5)
(0,0,0.25)
(0.25,0.5,0.75)
(0,0.25,0.5)
(0,0.25,0.5)
(0,0,0)
X= (0,0,0)
(0,0,0.25) (0,0,0.25)
(0.155,0.375,1.0) (0,0,0)
(0,0.125,0.5)
(0.078,0.25,0.75) (0,0,0.25) (0,0,0)
(0.155,0.375,1.0) (0,0,0.25)
(0.078,0.25,0.75) (0,0.125,0.5) (0.078,0.25,0.75)
(0.155,0.375,1.0) (0,0,0.25) (0.078,0.25,0.75) (0,0,0) (0.155,0.375,1.0) (0,0,0.25) (0,0.125,0.5) (0,0.125,0.5)
(0,0.125,0.5)
(0.078,0.25,0.75) (0,0.125,0.5) (0,0.125,0.5) (0,0.125,0.5) (0,0.125,0.5)
(0.155,0.375,1.0) (0,0,0)
(0,0,0.25) (0.078,0.25,0.75) (0,0.125,0.5)
(0,0.125,0.5)
(0,0.125,0.5) (0,0,0)
The total-relation fuzzy matrix T is divided in lower, middle, and upper components of triangular fuzzy number and is given by Tl = 0.0257
0
0.0125
0.1599
0
0.0009
0.1719
0
0.0083
0.1053
0
0.0006
0.0935
0
0.0135
0.0935
0
0.0790
0.1663
0
0.0030
0.0321
0
0.0063
0.1847
0
0.0145
0.1848
0
0.0010
0.0073
0
0.0010
0.0073
0
0.0061
Tm = 0.422
0
0.236
0.695
0.159
0.343
1.078
0
0.488
0.987
0.378
0.552
0.860
0
0.332
0.860
0.348
0.591
0.948
0
0.523
0.676
0.337
0.501
1.064
0
0.492
1.063
0.262
0.546
0.644
0
0.489
0.644
0.307
0.321
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N. Z. Khan et al.
Fig. 2 Cause-and-effect diagram
Relation
Position
Tu = 0.777
0.127
0.37
0.262
0.252
0.215
0.257
0.335
0.652
0.329
0.19
0.275
0.337
0.117
1.087
0.317
0.142
0.122
0.229
0.112
0.507
0.700
0.154
0.214
0.252
0.132
0.63
0.227
0.512
0.262
0.36
0.092
0.072
0.339
0.095
0.495
Now using steps (4), (5), and (6), we obtain Factors s+i
s− i
s+i (def) s− i (def) wi
Wi
Rank
F1
(0.848, 6.875, 4.215) (0.451, 3.159, 0.209) 3.979
1.273 4.178 0.204 2
F2
(0.286, 3.483, 2.955) (−0.286, −3.483, − 2.241 1.123)
−1.631 2.772 0.135 6
F3
(0.458, 3.248, 5.722) (−0.354, −0.433, 0.916)
3.143
0.043 3.143 0.153 4
F4
(0.788, 7.912, 4.095) (0.374, 1.940, 0.259) 4.265
0.858 4.350 0.212 1
F5
(0.386, 5.222,3.363)
(−0.386, −2.083, − 2.990 0.669)
−1.046 3.168 0.155 3
F6
(0.115, 5.264, 3.038) (0.073, 0.452, 0.128) 2.806
0.218 2.814 0.137 5
A cause-and-effect diagram is shown in Fig. 2. The position expresses the importance of each factor among all factors being considered, while the relation indicates the nature of particular cross-references (causative or consecutive). From Fig. 2, it is evident that factors F1, F3, F4, and F6 are the causes not the consequences of fatigue, whereas other two factors, i.e., F2 and F5, are influenced by these factors.
4 Conclusions DEMATEL method coupled with the fuzzy grading is an effective tool for describing the nature of the influence between fatigue risk factors. This method reliably estimates the values of the position and of the relation between factors, thus helps in quantifying both the intensity and the direction of the examined cause–effect interaction.
Analyzing the Important Factors Causing Fatigue in Industrial …
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References 1. Kroemer, K.H.E., Grandjean, E.: Fitting the task to the Human, 5th edn. Taylor & Francis Ltd., London (2000) 2. Williamson, A., Lombardi, D.A., Folkard, S., Stutts, J., Courtney, T.K., Connor, J.L.: The link between fatigue and safety. Accid. Anal. Prev. 43(2), 498–515 (2011) 3. Spencer, M.B., Robertson, K.A., Folkard, S.: The development of a fatigue/risk index for shift workers. Research Report 446. London: Health & Safety Executive (2006) 4. Folkcard, S., Tucker, P.: Shift work, safety and productivity. Occup. Med. 53(2), 95–101 (2003) 5. Cladwell, J.A.: Fatigue in the aviation environment: an overview of the causes and effects as well as recommended countermeasures. Aviat. Space Environ. Med. 68(10), 932–938 (1997) 6. Lerman, S.E., Eskin, E., Flower, D.J., George, E., Gerson, B., Hartenbaum, N.: Fatigue risk management in the workplace. J. Occup. Environ. Med. 54(2), 231–258 (2012) 7. Williamson, A., Friswell, R.: Fatigue in the workplace: causes and countermeasures. Fatigue: Biomedicine, Health & Behaviour 1(1-2), 81–98 (2013) 8. Samantra, C., Datta, S., Mahapatra, S.S.: Application of Fuzzy based VIKOR approach for multi-attribute group decision making (MAGDM): A case study in supplier selection. Decis. Making Manuf. Serv. 6(1), 25–39 (2012) 9. Karande, P., Chakarborty, S.: A Fuzzy-MOORA approach for ERP system selection. Decis. Sci. Lett. 1, 11–22 (2012) 10. Vinodh, S., Varadharajan, A.R., Subramanian, A.: Application of fuzzy VIKOR for concept selection in an agile environment. Int. J. Adv. Manuf. Technol. 65, 825–832 (2013)
Prioritizing the TQM Enablers in HCEs for Improved Performance: An AHP Approach Faisal Talib
and Zillur Rahman
Abstract The purpose of this paper is to investigate and categorize the TQM enablers and examine the relative importance of these enablers for implementation by ranking them in HCEs. A literature review, discussion with experts, and the analytical hierarchy process (AHP) approach were employed in the study. About 20 TQM enablers were identified and divided into five broad enabler categories. The identified enablers were prioritized using AHP approach and results showed that ‘leadership-based enablers’ ranked at first place followed by ‘resources and competency developmentbased enablers,’ ‘teamwork and participation-based enablers,’ ‘process managementbased enablers,’ and ‘continuous improvement-based enablers.’ This study further identified the relative importance of the 20 TQM enablers within the broad-based enablers categories, which will allow HCEs practitioners and decision-makers to operate their available resources for the improvement and strengthening of current TQM enablers and hence, performance of HCEs. The priority criteria enablers that ranked on the top of the TQM enablers list were: ‘quality leadership and role of physicians,’ ‘resource management,’ and ‘leadership style and change in organizational culture.’ The managerial implications and scope for future study were presented in the end. Keywords Total quality management (TQM) · TQM enablers · Analytical hierarchy process (AHP) · Healthcare establishments (HCEs) · Prioritization
F. Talib (B) Department of Mechanical Engineering, Zakir Husain College of Engineering and Technology, Faculty of Engineering & Technology, Aligarh Muslim University, Aligarh 202002, Uttar Pradesh, India e-mail: [email protected] Z. Rahman Department of Management Studies, Indian Institute of Technology, Roorkee 247667, Uttarakhand, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_4
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F. Talib and Z. Rahman
1 Introduction In the present globalized and liberalized world, the standards of quality products and services as well as changing behavior of customers have remarkably increased due to which there is a concern about the improvement in delivery of quality products and services in every sector [1]. In this response, many organizations start to develop and adopted quality improvement approaches like Six Sigma, balance score card (BCS), Taguchi method, quality function deployment, multicriteria decisionmaking processes (MCDM) techniques, and many others. One of the notable and recommended approach is the philosophy of total quality management (TQM). It is an approach that focuses on continuously improving and sustaining quality of products and services by involving ‘all,’ i.e., management, employees, suppliers, internal and external customers and stakeholders to meet and exceed customer satisfaction [2–6]. Furthermore, the review of literature on TQM shows that several researches have been undertaken to establish the enablers of TQM in service sector [1, 2, 7], but study on establishment and ranking of TQM enablers in HCEs is at beginning stage and attention has to be paid in this area. There is extreme need to establish the relative importance of these TQM enablers, implementing them, and achieve maximum benefits and desired goals. Therefore, it is essential to prioritize resource allocation to each individual enablers during implementation of TQM in HCEs. Based on the critical analysis of above information and to bridge this gap, the present study uses an analytical hierarchy process (AHP) approach that can be used for ascertaining the relative importance of enablers of TQM in HCEs. Hence, the purpose of this study is twofold: • to investigate and categorize the enablers of TQM in HCEs; and • to prioritize the relative importance of these enablers for implementation. The remainder of this paper is organized as follows. The next section presents the literature review and discusses the identification and categorization of TQM enablers in HCEs which is followed by research methodology used in the study. Finally, discussion and conclusions, along with the implications of the research findings and scope for further research, are presented.
2 Literature Review 2.1 TQM in HCEs Sabella et al. [8] assessed QM practices and their implementation in Palestinian hospitals by utilizing Malcolm Baldrige National Quality Award (MBNQA) criteria. They observed that performance of non-governmental organizations and private hospitals was superior than all other administrative types of hospitals. Marinkovic et al.
Prioritizing the TQM Enablers in HCEs …
35
[2] explored the good practice (GxP) and standardized management system integration within TQM paradigm in pharmaceutical sector of Serbia by conducting a cross-sectional study among manufacturers, distributors, big pharma representative officers, and national regulatory authority. In another study by Mosadeghard [9] developed a TQM model for healthcare organizations and validated it using a sample of Iranian healthcare organizations. The proposed TQM model was measured and found that in some healthcare organizations, the level of TQM success was medium, whereas in others, it was having high level in the dimensions such as customer management, leadership, and employee management. Talib et al. [10] presented a TQM implementation framework for healthcare industry consisting of five different stages or enablers which are integrated systematically to achieve positive outcomes. Similarly, other studies like [11, 12] are of interest too. The above literature reveals that to some extent, no proper framework of TQM implementation for HCEs has been established though few researchers have proposed but either they are not implemented or failed. Therefore, there is a strong need to develop a framework that should categorize the enablers into different sub-categories or enablers and examine the relative importance of these identified enables for implementation in HCEs as per their priority so that the HCEs practitioners and decisionmakers may take appropriate decisions for their effective implementation and achieve desired outcomes.
2.2 Identification of Enablers Categories and TQM Enablers in HCEs The study utilizes 20 TQM enablers of Talib et al. [10] research to carry out further analyses. They divided these TQM enablers (sub-categories) into five broad enabler categories based on review of TQM enablers literature and discussion with experts from academia and HCEs. After in-depth analysis and understanding the behaviors of these 20 TQM enablers, five categories were formed, namely leadership-based enablers, resources and competency development-based enablers, process management-based enablers, teamwork and participation-based enablers, and continuous improvement-based enablers [10]. The details of these enabler categories and sub-categories can be found in the work of Talib et al. [10].
3 Research Methodology This study investigates and categorizes the TQM enablers associated with HCEs and then prioritize them using the AHP methodology.
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F. Talib and Z. Rahman
3.1 AHP Background AHP approach was pioneered by Saaty [13] which aims to allow decision-makers to model complex problem based on mathematics and human psychology [13]. It uses a multilevel hierarchical structure of goal, criteria, and sub-criteria. Thus, a complex hierarchal structure is obtained consisting of three levels. Level 1 focuses on goal of the research, Level 2 contains criteria or enablers categories, and Level 3 includes sub-criteria or TQM enablers to be implemented. To carry out this process, AHP utilizes Expert Choice software, but this study adopted simple computational approach that uses a standard procedure to conduct AHP study. The detail of which can be seen in the work of Khanam et al. [14], Talib and Rahman [15].
3.2 Prioritization of TQM Enablers in HCEs After developing the AHP model using Steps 1 to 3, data was obtained involving a team of four experts who performs pairwise comparison of enablers’ categories and sub-categories used in the AHP approach. Experts were chosen from different areas such as academia, healthcare and practitioners. Next task was to perform the pairwise comparisons among the criteria and sub-criteria using a nine-point scale proposed by Saaty in 2000 [14, 15]. Further, consistency index (CI) was calculated to verify consistency of the pairwise matrix as defined by Saaty [13]. CI =
λmax − n n−1
(1)
where λmax is the maximum eigenvalue of the matrix of the importance ratio and ‘n’ is the number of categories or sub-categories of each level. Then, the consistency ratio (CR) was calculated to assess whether a matrix was consistence or not. This is determined by the following relation: CR =
CI RI
(2)
The values of random index (RI) are also proposed by Saaty in 2000 and can be obtained [14, 15]. According to Saaty [13], if the value of CR ≤ 0.10, the consistency is acceptable, otherwise pairwise comparison is inconsistence and therefore, undesirable, and the assessment is repeated again under such circumstances. For example, the pairwise comparisons of categories or enabler categories in the second level (Level-2) were performed, and the degree of consistency was found to be less than 0.10, i.e., CR is 0.072. Similarly, the pairwise comparison for sub-categories or TQM enablers in the other level (Level-3) was carried out, and their degree of consistency was measured and examined. The results of pairwise comparisons of sub-categories (TQM enablers) are presented in Table 1. The priority weights obtained are split into
Prioritizing the TQM Enablers in HCEs …
37
Table 1 Local and global weights of the five enabler categories or criteria and 20 TQM enablers or sub-criteria Hierarchy level
Enablers categories/criteria and TQM enablers
Level 2
With respect to implementation priorities of TQM enablers
Level 3
Local Wts.
Ranking
Global Wts.
Ranking
Leadership enablers
0.467
1
0.467
1
Resources and competency development enablers
0.277
2
0.277
2
Process management enablers
0.075
4
0.075
4
Teamwork and participation enablers
0.139
3
0.139
3
Continuous improvement enablers
0.042
5
0.042
5
Sum
1.00
1.00
With respect to leadership enablers Building management commitment
0.117
3
0.054
6
Leadership style and 0.262 change in organizational culture
2
0.122
3
Setting the management 0.055 principles and quality policies
4
0.025
10
Quality leadership and role of physicians
0.566
1
0.264
1
Sum
1.00
With respect to resources and competency development enablers Resource management
0.565
1
0.156
2
Personnel management
0.261
2
0.072
5
Policy and strategy
0.054
4
0.014
14
Training resources
0.116
3
0.032
9
Sum
1.00
With respect to process management enablers Delivering the concepts of quality to employees
0.252
2
0.018
12
Conduct TQM 0.568 educational and training program
1
0.042
7
(continued)
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F. Talib and Z. Rahman
Table 1 (continued) Hierarchy level
Enablers categories/criteria and TQM enablers
Local Wts.
Ranking
Global Wts.
Ranking
Standardizing the processes and management
0.120
3
0.009
16
Management by fact
0.059
4
0.004
19
Sum
1.00
1.00
With respect to teamwork and participation enablers Teamwork development 0.260
2
0.036
8
People-based management
0.115
3
0.015
13
Employee relations
0.564
1
0.078
4
Supplier participation
0.053
4
0.007
17
Sum
1.00
1.00
With respect to continuous improvement enablers Customer focus
0.529
1
0.022
11
Performing regular survey of customer satisfaction and quality audit
0.068
4
0.002
20
Customer feedback
0.1342
3
0.005
18
Performance measurement
0.268
2
0.011
15
Sum
1.00
1.00
local weights and global weights for each category and sub-category. Local weights represent the priority weights with respect to the preceding hierarchical level, and global weights are priority weights with respect to the highest hierarchical level. Finally, overall ranking of categories and sub-categories was performed utilizing the equation [15]: Global weights =
(Local weight for category i × local weight for sub − category j with respect to category i)
(3)
The final rankings of enablers (categories) and TQM enablers (sub-categories) are presented in Table 1. From Table 1, one can prioritize and consider the enabler categories and TQM enablers (sub-categories) for effective implementation of TQM in HCEs and health practitioners and managers can have better knowledge of them for best utilization.
Prioritizing the TQM Enablers in HCEs …
39
4 Discussion The present study investigated various enabler categories and TQM enablers (subcategories) of TQM implementation for improved performance in HCEs. The study also prioritized the relative importance of these TQM enablers and ranked them based on priority weights and with the help of experts opinion. Finally, a hierarchical model based on AHP approach is developed and introduced as depicted in Fig. 1 that divides the hierarchy into three levels: Level-1: goal, Level-2: five enabler categories and Level-3: TQM enablers (20 sub-categories). Table 1 shows both the weights local as well as global of five enabler categories and 20 TQM enablers (sub-categories). In Level 2 of the model (w.r.t. local weights), the evaluators considered that leadership enablers (0.467) were the most important enabler category followed by resource and competency development-based enablers (0.277), teamwork and participationbased enablers (0.139), process management-based enablers (0.075), and continuous improvement-based enablers (0.042) based on the priority weights as shown in parentheses. From Level-3 of the model (Fig. 1), the evaluators considered ‘quality leadership and role of physicians (0.566)’ and ‘leadership style and change in organizational culture (0.262)’ most important with respect to leadership-based enablers. Similarly, w.r.t. resource and competency development-based enablers, ‘resource management (0.565) and ‘personnel management (0.261)’ were considered critical and other remaining three enablers’ categories ranking can be seen from Table 1. The global weight results indicate that quality leadership and role of physicians (0.264) is the most important enabler among 20 TQM enablers and is ranked at the top of the list. It concludes that HCEs should emphasize on the development of quality leadership and active participation of top leaders of the management for improved performance. Active role of physicians promotes the quality performance of the organization and increased satisfaction to patient. This is followed by resource management (0.156) and leadership style and change in organizational culture (0.122). The other TQM enablers ranked on the basis of their global weights are also critical enablers of TQM. They are: employee relations (0.078), personal management (0.072), building management commitment (0.054), conduct TQM educational and training program (0.042), and teamwork development (0.036). These TQM enablers are critical for successful implementation of TQM program and if implemented properly will improve performance of HCEs. The lowest ranked TQM enablers, viz. standardizing the processes and management (0.009), supplier participation (0.007), customer feedback (0.005), management by fact (0.004), and performing regular survey (0.002) are also important and cannot be neglected. The priority levels of all these TQM enablers of HCEs are graphically portrayed and presented in Fig. 2.
Fig. 1 A hierarchy model of TQM implementation in HCE
40 F. Talib and Z. Rahman
Prioritizing the TQM Enablers in HCEs …
41
Fig. 2 Priority level of TQM enablers in HCEs
5 Conclusion This study tried to prioritize the identified enablers of TQM and put forward hierarchical model, i.e., AHP methodology, to rank the identified enablers connected to HCEs. The robustness of this study is the evolution of a hierarchy model for investigation and prioritization of enablers of TQM that HCEs observes. By using AHP, the relative importance of all these enablers and their importance in HCEs were analyzed, and the most and least significant enablers were identified. It is concluded that the role of top management including physicians and employees as well as availability of resources and development of competency in the organization are tremendously important for improved performance. Therefore, top management should pay special attention on these enablers and to the highest ranked enablers. Continuous efforts should be made for quality leadership and role of physicians in HCEs. This study can be further extended by validating the proposed AHP model using structural equation modeling (SEM) and can be implemented in various other organizations like micro, small, medium enterprises (MSMEs), agro industries, etc. for improved performance.
References 1. van Schoten, S., de Blok, C., Spreeuwenberg, P., Groenewegen, P., Wagner, C.: The EFQM Model as a framework for total quality management in healthcare: Results of a longitudinal quantitative study. Int. J. Oper. Prod. Manag. 36(8), 901–922 (2016) 2. Marinkovic, V., Bekcic, S., Pejovic, G., Sibalija, T., Majstorovic, V., Tasic, L.: An approach to TQM evaluation in pharma business. TQM J. 28(5), 745–759 (2016) 3. Cua, K.O., McKone, K.E., Schroeder, R.G.: Relationships between implementation of TQM, JIT, and TPM and manufacturing performance. J. Oper. Manag. 19, 675–694 (2001) 4. Valmohammadi, C., Roshanzamir, S.: The guidelines of improvement: relations among organizational culture, TQM and performance. Int. J. Prod. Econ. 164, 167–178 (2015) 5. Mehralian, G., Nazari, J.A., Zarei, L., Rasekh, H.R.: The effects of corporate social responsibility on organizational performance in the Iranian pharmaceutical industry: the meditative role of TQM. J. Clean. Prod. 135, 689–698 (2016) 6. Ahmad et al.: Relationship of TQM and business performance with mediators of SPC, lean production and TPM. Procedia-Social and Behavior. Sci. 65, 186–191 (2012)
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7. Talib, F., Rahman, Z., Azam, M.: Best practices of total quality management implementation in healthcare setting. Health Market. Q. 28(3), 232–252 (2011) 8. Sabella, A.R., Kashou, R., Omran, Q.: Assessing quality of management practices in Palestinian hospitals. Int. J. Organ. Anal. 23(2), 213–232 (2015) 9. Mosadeghrad, A.M.: Developing and validating a total quality management model for healthcare organisations. TQM J. 27(5), 544–564 (2015) 10. Talib, F., Rahman, Z., Azam, M.: Total quality management implementation in the healthcare industry: a proposed framework. Proceedings of Second International Conference on Production and Industrial Engineering (CPIE-2010) organized by Department of Industrial and Production Engineering, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar (NITJ), Punjab, India, pp. 1361–1368 (2010) 11. Chiarini, A., Vagnoni, E.: TQM implementation for the healthcare sector: The relevance of leadership and possible causes of lack of leadership. Leadersh. Health Serv. 30(3), 210–216 (2017) 12. Beuran, M., Negoi, I., Paun, S., Vartic, M., Stoica, B., T˘anase, I., Negoi, R.I., Hostiuc, S.: Quality management in general surgery: a review of the literature. J. Acute Dis. 3(4), 253–257 (2014). https://doi.org/10.1016/S2221-6189(14)60057-3 13. Saaty, T.L.: Fundamental of Decision Making and Priority Theory with the Analytic Hierarchy Process. RWS Publication, Pittsburgh, PA (2000) 14. Khanam, S., Siddiqui, J., Talib, F.: A DEMATEL approach for prioritizing the TQM enablers and IT resources in the Indian ICT industry. Int. J. Appl. Manag. Sci. Eng. 3(1), 11–29 (2016) 15. Talib, F., Rahman, Z., Qureshi, M.N.: Prioritising the practices of total quality management: an analytic hierarchy process (AHP) analysis for the service industries. Total Quality Manag. Bus. Excell. 22(12), 1331–1351 (2011)
Development of Bottom-Wear Size Chart for Indian Male Youth Manoj Tiwari and Noopur Anand
Abstract The objective of the paper is to develop a standardized bottom-wear body size chart for Indian male youth through a pan-India anthropometric survey. The research involved a pan-India anthropometric survey of 14 crucial body dimensions (required for bottom-wear) of 2401 Indian male youth aged between 18 and 29 years. Statistical analysis of the anthropometric data was done through multivariate analysis using principal component analysis (PCA) and two-step cluster analysis as data mining techniques using SPSS 16. The developed size charts were validated statistically by calculating aggregate loss based on Euclidean distance. The research resulted in the selection of six body size charts based on standard deviation as well as cluster analysis. The aggregate loss values were observed between 1.81 cm and 2.42 cm. The percentage coverage of the population ranged between 76.22% and 97.21% with a number of size categories ranged from 32 to 40. The research has significant practical implications in the scenario, where there is no Indian size chart, and this research provides one for bottom-wear for Indian male youth. The developed size chart may be used to manufacture well-fitting bottom-wear by Indian apparel industry. The research will result in increased consumer satisfaction and reduction in loss of sales because of fit issues of bottom-wear. Keywords Anthropometry · Indian youth · Bottom-wear · Size charts · Statistical analysis · Euclidean distance
1 Introduction Each and every element of the surrounding environment (personal space as well as workspace) must be able to provide satisfaction to the user in all aspects including utility or functionality, safety, user-friendliness, psychological satisfaction with M. Tiwari (B) National Institute of Fashion Technology, Jodhpur, India e-mail: [email protected] N. Anand National Institute of Fashion Technology, New Delhi, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_5
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aesthetics. The same is true with clothing also and its fit to the wearer’s body is an important criterion for evaluation of a garment by the consumer. The approach should be to consider human variability while designing [1]. Wearing clothes of right size according to body measurements in imperative to get comfort and fit [2]. Sizing is one of the basic requirements for industrial clothing production, where garments are manufactured considering the body dimensions of the consumers [1]. Considering the anthropometric measurements for clothing production; sizing systems have been developed based on the body measurements taken across the section of the population [3]. Various countries, including the US and UK, have developed their sizing systems using traditional manual techniques as well as modern technology [4]. India with the largest youth population is one of the biggest consumer markets with the presence of national and international apparel brands. Unfortunately, India does not have its anthropometric database; hence, the Indian apparel sector is bound to use size charts of western countries [5, 6]. There has been a little-reported research work done in India as far as anthropometric applications in apparel sizing are concerned [7]. Moreover, the sample size used in such apparel-related research was not good enough or statistically justified to represent the entire nation. However, few brands have come up with their measurement charts and tried to take the commercial advantage, but they are still unable to cater the mass with a perfect fit as per Indian consumer requirements. The youth consumers have to compromise with the fit of the garments. These fit-related issues may be addressed effectively by the development of standardized body size charts through a pan-India body size survey of Indian youth justifying the need for the research. This paper aims to develop standardized bottom-wear body size chart for Indian male youth through a pan-India anthropometric survey.
1.1 Subject A nation-wide anthropomorphic survey of Indian male youth (18–29 years) was conducted, where body measurements of the subjects were recorded from 6 geographical zones (as Eastern India, Western India, Northern India, Southern India, Central India and North-East India) covering all the states of India. A statistically justified sample size at 95% confidence level and 5% error level [8, 9] were covered by each zone making total sample size 2304 subjects from all six geographic zones. Total valid subjects measured while anthropometric survey was 2401 subjects. The subject categories involved primarily students and employed people from different organizations.
Development of Bottom-Wear Size Chart …
45
1.2 Body Dimensions In total, 14 body dimensions essentially required for bottom-wear were selected for measurements. Inside leg length, outside leg length, waist girth, seat girth (hip girth), thigh girth, knee girth, ankle girth and body rise are required for developing a fulllength trouser [10, 11]. According to Armstrong [12] measurements, from waist to ankle, crotch depth, front and back hip arc, front and back waist arc and ankle girth are required to develop a trouser [12].
1.3 Procedure and Equipment The definitions and landmarks of body dimensions followed were as per the ISO 8559 (1989) standard and ISO 7250-I (2008) standard. The body survey was conducted manually using anthropometer (sliding stadiometer of length 210 cm and least count 1.0 mm) and a certified flexible non-stretchable steel tape (length 200 cm and least count 1.0 mm) used for anthropometric studies. While taking, measurements subjects were kept bareheaded and without shoes. Skinny comfort fit knitted shorts were used while taking body measurements making sure that it was neither adding to the body dimension or compressing the body resulting in loss of measurement [13, 14].
2 Results and Discussion 2.1 Data Preparation and Initial Analysis The data was cleaned by filtering out outlier values which were abnormal and falling beyond ± three σ (standard deviation) limits [15, 16]. The initial analysis of the anthropometric data involved frequency distribution for age, profile and geographic distribution of the subjects, univariate analysis with basic statistics using mean, median, mode and range of minimum and maximum values of the anthropometric variables. The body measurement data were analyzed for the normal distribution. It was observed that the anthropometric data (body measurement data) was nearly normally distributed. Sample adequacy and sphericity of the body measurement data were tested using Kaiser Meyer Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity. KMO value observed was 0.810 which was very good in comparison with standard acceptable KMO value 0.60. Bartlett’s test of sphericity was also observed suitable. Internal consistency and uni-dimensionality of the data were tested using Cronbach’s alpha measure. The Cronbach’s alpha value observed was 0.910 which was very good to the standard acceptable Cronbach’s alpha value 0.60.
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2.2 Sizing Analysis The sizing analysis involved data mining applying multivariate analysis using principal component analysis (PCA) and two-step cluster analysis. Principal component analysis (PCA). The principal component analysis (PCA) with Varimax rotation was applied to identify the key or most important factors useful for developing the body size charts. In order to gain the parsimony, the number of factors extracted should be less. To achieve this objective, following the standard practice, the factors indicating eigenvalues more than 1.0 were selected. Figure 1 illustrates the scree plot of the graphical representation of eigenvalues of the factors extracted from PCA. Variance explained in the principal component analysis is mentioned in Table 1. It was observed that two components were having eigenvalue more than 1.0 and together explained 69% of the total variance (as shown in Table 1). These two components extracted were horizontal (girth) and vertical (height) dimension. Selection of key dimensions. Rotated component matrix with Varimax rotation for the body dimensions of the subjects measured during sizing survey is shown in Table 2. The body dimensions with factor loading ≥0.75 are highlighted with bold letters. Examination of the factor loading confirmed that the variables under a factor or component are highly correlated with each other. The girth-related (horizontal) dimensions are falling in one category having a strong positive correlation with the first component. While the other set of dimensions is length related (vertical) dimensions. As a result of this factor loading analysis with Varimax rotation (as
Fig. 1 Scree plot
Cumulative %
0.863
0.681
0.381
0.282
0.222
0.192
0.162
3
4
5
6
7
8
9
1.80
2.13
2.47
3.13
4.23
7.56
9.58
23.51
100.00
98.19
96.06
93.59
90.45
86.22
78.65
69.07
Extraction method: Principal component analysis.
2.11
2
45.55 2.11
4.10 23.51
45.55
% of variance 69.07
45.55
Cumulative %
Total
45.55
% of variance
Total
4.10
Extraction sums of squared loadings
Initial eigenvalues
1
Component
Total variance explained
Table 1 Principal component analysis
2.64
3.56
Total
29.43
39.64
% of variance
69.07
39.64
Cumulative %
Rotation sums of squared loadings
Development of Bottom-Wear Size Chart … 47
48 Table 2 Rotated component matrix—PCA
M. Tiwari and N. Anand Rotated component matrix Component 1 2 (Horizontal/girth) (Vertical/height) Height
0.199
0.890
True waist girth
0.875
0.043
Hip girth
0.855
0.183
Thigh girth
0.882
0.031
Knee girth
0.806
0.057
Crotch height
0.049
0.906
Waist height
0.124
0.926
Total crotch length front 0.388 to back as U
0.282
Ankle girth
0.246
0.651
a. Rotation converged in three iterations.
shown in Table 2), two components extracted were horizontal (girth) and vertical (length) dimensions. This eventually resulted in selection of key dimensions for the sizing system. Thigh girth and true waist girth showed the highest factor loading as 0.882 and 0.875, respectively, with the girth component, while waist height and crotch height witnessed the highest factor loading as 0.926 and 0.906, respectively, with the length component. It was noted that thigh girth has witnessed maximum factor loading in the girth component, though thigh girth is not common as a key dimension in the sizing systems developed, however, it showed marginally strong correlation than true waist girth in this research. True waist girth is the most acceptable key dimension for almost all the sizing systems used for the male population where thigh girth is not heard off as a key dimension for bottom-wear. Since the key dimensions must be easy to measure and the body dimensions should be familiar for everybody [17], and waist girth was chosen as one of the key dimensions. In the context of length-related key dimensions, waist height, crotch height and height showed a very strong correlation to the length factor. In common practice, all of these three are applied as a key dimension in different sizing systems. Some sizing systems follow waist height as a key dimension, while some other size systems follow waist height or height for body classification. In India, crotch height is popularly used as one of the key dimensions. ISO 3636 (1977) indicates waist girth and inside leg length as control dimensions for men’s lower body garments [18]. In BSI sizing, system uses waist height (outside leg length) as key dimension [19]. Similarly, Hsu [15] used outside leg length as one of the key dimension in sizing system development for Taiwanese female [15]. The Korean sizing systems use height as one of the key dimensions and size categories have been defined by height [20, 21]. Chung et al. [22] developed a sizing system for Taiwanese school students and used height as one
Development of Bottom-Wear Size Chart …
49
of the key dimensions [22]. Zakaria [17] used height as one of the key dimensions while developing size chart for school children in Malaysia [17]. Finally, an attempt was made to develop three separate sizing systems considering each of three vertical dimensions height, waist height and crotch height as a key dimension in a sizing system. Cluster Analysis. Cluster analysis was applied to classify the anthropometric data into significantly different clusters (classes) of control body dimensions for size chart development. Data classification was done through two-step cluster analysis method ensuring elimination of subjectivity on the number of some clusters. Following the results from PCA, three combinations were worked out as waist girth–height, waist girth–waist height and waist girth–crotch height. The cluster distribution with the percentage of subjects in the classes identified in each of the three combinations is shown in Table 3. It can be noticed that the waist girth–height, waist girth–waist height and waist girth–crotch height resulted in five, three and six classes of the subjects. To check and confirm the significantly distinguished segmentation, analysis of variance (ANOVA) was applied to the clusters created for each of the combinations. Table 3 Cluster combinations Cluster distribution Waist girth–height
Classes
% of total
14.2
14.2
2
671
27.9
27.9
3
451
18.8
18.8
4
259
10.8
10.8
679
28.3
28.3
2401
100.0
100.0
1
701
29.2
29.2
2
1013
42.2
42.2
3
687
28.6
28.6
2401
100.0
100.0
1
394
16.4
16.4
2
419
17.5
17.5
3
700
29.2
29.2
4
241
10.0
10.0
5
434
18.1
18.1
6
213
8.9
8.9
2401
100.0
100.0
Combined
Combined Waist girth–crotch height
% of combined
341
5 Waist girth–waist height
N
1
Combined
50
M. Tiwari and N. Anand
3 Development of Size Charts The development of the body size charts was done for three combinations of the control dimensions as waist girth–height, waist girth–waist height and waist girth– crotch height. The body size charts were developed by two methods as cluster analysis and standard deviation (see Fig. 2) using mentioned combinations of control dimensions resulted in total of six different body size charts. In each of the size chart two body dimensions, each for girth and height was taken as control dimensions following PCA and cluster analysis. The development of the sizing system involved selection size range, size interval, size scale and size roll. For cluster analysis-based size charts, the value of one control dimension mentioned in the size chart indicates the central value of that interval. An example of a size chart for class-1 (waist girth–waist height) is shown in Table 4. An interval of 5 cm has been kept for the control dimensions. For example, waist girth 57 cm as mentioned in the size charts covers waist girth more than or equal to 55 cm and less than 60 cm (55 cm ≤ waist girth < 60 cm). The same method is followed for the other control dimensions also. For standard deviation-based size charts, the value of one control dimension mentioned in the size chart indicates the central value of the standard deviation range. For example, height, 156 cm as mentioned in the size chart covers height more than or equal to 153 cm and less than 159 cm (153 cm ≤ height < 159 cm) provided the standard deviation of that control dimension is 6 cm. The value mentioned for the secondary dimension against each size category is the average value of the body dimensions of the subjects falling in the respective size category. It was observed from the size chart (refer Table 4) that there are 5 waist girth-wise categories and for each such category there are waist height-wise sub-categories. As indicated for the waist category of 62 cm., there are 3 waist height sub-categories 92 cm., 97 cm., and 102 cm. As a result, in this size chart for class 1, there are total of 9 size categories or size rolls. Table 5 shows the size distribution of size chart (clusterbased, waist girth–waist height) developed. The number of subjects and aggregate loss value of each category is indicated (refer to Table 5). It was observed that this
Standard deviation
Waist girth – Height Waist girth – Waist height Waist girth – Crotch height
Cluster analysis
Waist girth – Height Waist girth – Waist height Waist girth – Crotch height
Classification of Anthropometric data
Fig. 2 Body size chart combinations
62 (60–64.9)
67 (65–69.9)
72 (70–74.9)
77 (75–79.9)
70
34
36
71
29
Crotch height
Front rise
Back rise
Crotch length
Ankle girth
2.31
31
Knee girth
Aggregate loss (cm.)
41
Thigh girth
14
76
Hip girth
Number of subjects
68
67
High hip girth
1.36
29
31
72
37
35
60
34
45
75
65
2.07
25
30
72
37
35
66
33
43
79
71
67
64
63
Girth below 2 inch 63 of T/waist
161
159
1.3
56
30
73
38
36
70
33
43
80
72
67
65
166
1.7
30
31
72
37
35
66
34
46
81
74
70
68
161
1.09
129
31
73
38
36
70
34
46
82
74
71
68
166
2.12
21
31
74
38
35
67
34
46
86
79
76
74
160
1.29
110
31
74
38
36
71
34
48
86
79
76
73
167
3.07
15
32
72
38
34
69
35
49
91
83
81
79
167
102 92 97 102 97 102 97 102 97 (100–104.5) (90–94.9) (95–99.9) (100–104.5) (95–99.9) (100–104.5) (95–99.9) (100–104.5) (95–99.9)
Secondary Height 165 dimension (cm.) Girth below 1 inch 60 of T/waist
Waist height
57 (55–59.9)
Waist girth–waist height
Class-1
Control Waist girth dimension (cm.)
Bottom-wear (male—18–29 years)
Category
Table 4 Example of size chart for class-1 (waist girth–waist height)
Development of Bottom-Wear Size Chart … 51
52
M. Tiwari and N. Anand
Table 5 Size distribution for waist girth–waist height combination Size roll
1
Class
1
2
Control dimensions (cm.)
Aggregate loss value (cm.)
Average aggregate loss value (cm.) 1.81
Waist height
57
102
14
0.58
2.31
62
92
29
1.21
1.36
97
25
1.04
2.07
102
56
2.33
1.30
97
30
1.25
1.70
102
129
5.37
1.10
4 67
6 7
% accommodation
Waist girth
3 5
Number of subjects
72
97
21
0.87
2.12
102
110
4.58
1.30
77
97
15
0.62
3.07
62
107
43
1.79
1.46
112
58
2.42
1.20
107
104
4.33
1.21
13
112
110
4.58
1.21
14
117
26
1.08
1.90
107
159
6.62
1.26
16
112
187
7.79
1.18
17
117
54
2.25
1.31
77
112
101
4.21
1.12
117
71
2.96
2.33
77
102
42
1.75
1.61
107
110
4.58
1.45
8 9 10
2
11 12
67
15
72
18 19 20
3
21 22
97
14
0.58
3.56
23
102
46
1.92
1.48
24
107
91
3.79
1.57
25
112
79
3.29
2.01
26
117
16
0.67
2.54
102
25
1.04
2.36
28
107
37
1.54
1.87
29
112
29
1.21
1.72
30
117
18
0.75
2.17
107
18
0.75
2.69
112
19
0.79
2.53
1886
78.55
27
31
82
87
92
32 Total subjects covered
Development of Bottom-Wear Size Chart …
53
percentage coverage of this size chart was 78.55% spanning 32 size categories with average aggregate loss of 1.81 cm.
4 Validation of Size Charts McCulloch et al. [23] proposed the method for quantification of fit in a size chart. The level of fit will be poorer with an increase in the individual’s measurements differ from the prototype [23]. Ashdown [20] stated that an aggregate measure which is called aggregate loss represents the level of fit in the sizing system is calculated by averaging out all the individuals’ distances from respectively assigned size [20]. Aggregate loss based on Euclidean distance between two points X (X1 , X2 , etc.) and Y (Y1 , Y2 , etc.) is calculated as n Euclidean Distance (d) = (xi − yi)2 i=1
where x i and yi are the coordinates of points, where x is the actual size and y is the assigned size for the jth axis to represent the jth dimension. The system with an ability to provide the best fit should confirm the aggregate loss as low as possible [20]. The validation of size chart developed was done by determining the degree of fit following Euclidian distance as a measure of aggregate loss. Euclidean distance is one fundamental and the most popular way used to establish this distance or aggregate loss. In recent times, the aggregate loss is widely used by researchers worldwide for size chart validation and treated as a reliable tool for measuring the goodness of fit. Ideal aggregate loss value of fit may be a number given by the square root of the number of control dimensions or primary dimensions considered, allowing for ±1-inch deviation of the body dimension from the assigned value. Hence, the aggregate loss value √ (goodness of fit value) when considering two control body dimensions may be 2 or 1.414 inches. The same value in the metric system will be 3.59–3.6 cm. For fit validation of body size chart with two control dimensions, the aggregate loss value should be equal or lesser than 3.6 cm. In this research, each size category of every size chart was validated using aggregate loss based on Euclidean distance. All the six size charts developed were validated by calculating on an average aggregate loss. As mentioned in Table 6, the aggregate loss values observed from 1.81 cm. to 2.42 cm. in the size charts developed in this research. These values fall well within the standard limit value of ≤3.60 cm. The aggregate loss values observed in this research were found at par with the findings of other research works carried out in this field worldwide. Hsu [15] developed a data mining framework for industrial standards and observed aggregate loss values ranged between 2.5 cm. and 3.3 cm. [24]. Zakaria [25] validated the body size charts of the Malaysian school children using aggregate loss based on the Euclidean distance.
54
M. Tiwari and N. Anand
Table 6 Size charts comparison Sr. No.
Size chart control dimensions
Method used
Total size categories
1
WG–H
2.21
83.38
WG–WH
Cluster analysis
40
2
32
1.81
78.55
3
WG–CH
35
2.34
76.22
4
WG–H
40
2.41
92.13
5
WG–WH
40
2.42
95.50
6
WG–CH
39
2.29
97.21
Standard deviation
Aggregate loss value achieved
% coverage of population
The aggregate loss values observed were between 2.5 cm. and 2.6 cm. while using two control dimensions [25]. Doustaneh et al. [26] validated the size charts using aggregate loss and observed aggregate loss values between 2.27 cm. and 5.18 cm. [26]. It was noted that the aggregate loss observed in this research was, in fact, lesser than the aggregate loss observed by other researchers in recent times. It confirms the good level of fit and accuracy offered by the size charts developed in this research.
5 Comparative Analysis of the Size Charts Developed According to McCulloch et al. [23], an effective and economical sizing system must meet objectives of minimum aggregate loss, the minimum number of size categories and maximized percentage coverage of the population [23]. A comparative analysis was done for all the six size charts developed following the evaluation criteria followed suggested by McCulloch. The percentage coverage of population values was observed from 76.22% to 97.21% and considered as good accommodation in comparison with the international standards. A size chart with coverage of population ranging between 65% and 80% is treated as satisfactory [27, 28]. As shown in Table 6, it was noted that the size charts developed based on cluster analysis classification witnessed lesser aggregate loss values (confirmed better fit). While two of the size charts from this category had a lesser number of size categories as 32 and 35. However, these two size charts witnessed a comparatively lesser accommodation percentage (76–83%) though it was well within the acceptable limits. Standard deviation-based size charts showed an aggregate loss, number of size categories toward bit higher side, though it too was well within the acceptable limits. These size charts (standard deviation-based) showed excellent accommodation percentage (92–97%). The reason for this result may be the range considered for key dimensions that were mean ±3SD. As the anthropometric data of subjects was near normally distributed, and in a normal distribution, mean ±3 SD limits cover approximately 99% of the population.
Development of Bottom-Wear Size Chart …
55
6 Conclusion All the six size charts developed were validated by measuring aggregate loss based on Euclidean distance. The aggregate loss values observed from 1.81 cm. to 2.42 cm. These values fall well within the standard limit value of ≤3.60 cm. The percentage coverage of population values was observed from 76.22% to 97.21% with 32–40 size categories. It is considered as a good accommodation to the international standards. Size chart number 2 (WG–WH-cluster analysis) was observed best with minimum aggregate loss value and the number of size categories, while size chart number 6 (WG–CH-standard deviation) was observed best on the grounds of maximum percentage coverage of the population. This study applied data mining on the anthropometric data to develop the body size charts for bottom-wear. Proposed method ensured higher accommodation rate and lesser aggregate loss with lesser number of size categories in comparison with the standard values. The results of the study may help the mass manufacturers in predicting the proportional quantities in the respective sizes. It may also help the manufacturers and distributors in an effective process planning and control at different levels of the apparel supply chain. The garments developed using the proposed size charts may result in increased consumer satisfaction and reduction in loss of sales because of fit issues of bottom-wear.
References 1. Bridger, R.: Introduction to Ergonomics. Taylor & Francis, UK (2003) 2. Gupta, D., Zakaria, N. (eds.): Anthropometry, Apparel Sizing, and Design. Woodhead Publishing Limited in association with the Textile Institute, Cambridge (2014) 3. Kunick, P.: Modern Sizing and Pattern Making for Women’s and Children Garments. Kunick Publications, London, London (1984) 4. NTC: NTC Project: S01-CR01 (formerly S01-B01), 2003: Use of Body Scan Data to Design Sizing Systems Based on Target Markets. Annual Report, National Textile Center (2003) 5. Chakrabarty, D.: Indian Anthropometric Dimensions: For Ergonomic Design Practice. National Institute of Design, Ahmedabad (1997) 6. Anand, N.: Size does matter- Need for “SizeIndia”-National Body Sizing Survey of India. In: www.techexchange.com. Accessed 2011 7. Gupta, D.: Anthropometric study of young indian men for garment sizing. Res. J. Textile Apparel 14(1), 82–89 (2010) 8. Bartlett, J., Kotrlik, J., Higgins, C.: Organizational research: determining appropriate sample size in survey research. Inf. Technol. Learn. Perform. J. 19, 43–50 (2001) 9. Levin, L., Rubin, S.: Statistics for Management 2nd edn. Pearson Education (2004) 10. Cooklin, G.: Pattern Grading for Men’s Clothes. Blackwell Scientific, London, UK (1992) 11. Aldrich, W.: Metric Pattern Cutting for Menswear, 4th edn. Blackwell Publishing, Oxford, UK (2006) 12. Armstrong, H.J.: PatternmaKing for Fashion Design, 4th edn. Pearson Eduction Inc, New Jersey, USA (2006) 13. Beazley, A.: Size and fit: Procedures in undertaking a survey of body measurements. J. Fashion Market. Manag. Int. J. 2(1), 55–85 (1997)
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14. ISO-7250(I): Basic human body measurements for technological design - Body measurement definitions and landmarks (Part -1). Standards, International Organization for Standardization, Geneva (2008) 15. Hsu, C.-H.: Data mining to improve industrial standards and enhance production and marketing: An empirical study in apparel industry. Expert Syst. Appl. 36, 4185–4191 (2009) 16. Moon, J., Nam, Y.: A study the elderly women’s lower figure type classification and lower garment sizing systems. In: Proceedings of International Ergonomics Association, Korea (2003) 17. Zakaria, N.: Body shape analysis and identification of key dimensions for apparel sizing systems. In: Gupta, D., Zakaria, N. (eds.) Anthropometry, apparel sizing and design, p. 98. Woodhead Publishing Limited, Cambridge, UK (2014) 18. ISO:3636: ISO 3636:1977/Cor.1:1990 Size designation of clothes - Men’s and boys’ outerwear garments. ISO Standard, International Organization of Standardization, Geneva (1977) 19. Chun-Yoon, J., Jasper, C.: Garment-sizing systems: An international comparison. Int. J. Cloth. Sci. Technol. 5(5), 28–37 (1993) 20. Ashdown, S.: An investigation of the structure of sizing systems—A comparison of three multidimensional optimized sizing systems generated from anthropometric data with the ASTM Standard D5585-94. Int. J. Cloth. Sci. Technol. 10(5), 324–341 (1998) 21. Chun, J.: International apparel sizing systems and standardization of apparel sizes. In: Gupta, D., Zakaria, N. (eds.) Anthropometry, Apparel Sizing and Design, pp. 289–291. Woodhead Publishing ltd. in association with The Textile Institute, Cambridge, UK (2014) 22. Chung, M.-J., Lin, H.-F., Wang, M.-J.: The development of sizing systems for Taiwanese elementray and high-school students. Int. J. Ind. Ergon. 37, 707–716 (2007) 23. McCulloch, C., Paal, B., Ashdown, S.: An optimization approach to apparel sizing. J. Oper. Res. Soc. 49, 492–499 (1998) 24. Hsu, C.-H.: Developing accurate industrial standards to facilitate production in apparel manufacturing based on anthropometric data. Hum. Factors Ergon. Manuf. 19(3), 199–211 (2009) 25. Zakaria, N.: Sizing system for functional clothing- Uniforms for school children. Indian J. Fibre Text. Res. 36, 348–357 (2011) 26. Doustaneh, A.H., Gorji, M., Varsei, M.: Using SelfmOrganizing Mehtod (SOM) to establish a non-linear sizing system. World Appl. Sci. J. 9(12), 1359–1364 (2010) 27. Petrova, A.: Creating sizing systems. In Ashdown, S., ed.: Sizing in Clothing. Cambridge: Woodhead Publishing Limited, Cambridge, UK (2007), pp. 57–87 28. Gupta, D., Zakaria, N.: Apparel sizing:existing sizing systems and the development of new sizing systems. In: Gupta, D., Zakaria, N. (eds.) Anthropometry, Apparel Sizing and Design, pp. 3–33. Woodhead Publishing Limited in association with the Textile Institute, Cambridge (2014)
Occupational Health Hazard of Workers Engaged in Food Processing Unit of Assam Lahkar Koushika and Bhattacharyya Nandita
Abstract Occupational health hazards are quite prevalent among the workers engaged in food processing units. They may experience early fatigue and discomfort when performing highly repetitive tasks, working in repeated and sustained or awkward postures, performing heavy physical work and using forceful exertion. The study was conducted on 100 workers engaged in different activities of food processing units of Assam. It was revealed that respondents were found suffering from variety of work-related health hazards. While performing different activities, they used to assume unnatural postures, due to the mass productivity and arrangement of the workplace. Postural analyses of workers revealed that the majority of workers had musculoskeletal problems. Variety of joints movements were observed in maintaining different postures while the performing activities, as a result, workers were found suffering from joint paints. Cent percent of the respondent experienced very severe pains in low back, shoulder joint, knee joint and fingers. The use of age old work tools and poor workstations are reflected on the productivity of worker’s engaged in food processing units of Assam and their health status. Keywords Fatigue · Forceful exertion · Postural analysis
1 Introduction Occupational health is an important factor for sustainable socioeconomic development that enables workers to enjoy a healthy and productive life both throughout their active working years and beyond. It is always concerned with the promotion and maintenance of the highest degree of physical, mental and social well-being of workers in all occupations by preventing early departures from work, controlling risks and the adaptation of work to people, and people to their work. But in certain situations, occupational hazards are quite prevalent among the workers, aroused from work environment that is generated by job demands, environmental conditions, work L. Koushika · B. Nandita (B) Department of Family Resource Management and Consumer Science, College of Community Science, Assam Agricultural University, Jorhat, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_6
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organization, human relations, etc. Work-related musculoskeletal disorders mostly expressed through body pain, as a major indicating parameter of occupational health problems among the workers in industries, are the result of multiple exposures to a combination of risk factors. One of the most important work-related factors that contribute occupational health hazards is the ergonomic risk factor in the workplace [1]. A substantial body of credible epidemiologic research provides strong evidence of an association between work-related musculoskeletal disorders and certain workrelated physical factors; when there are high levels of exposure, and especially in combination with exposure to more than one physical factor (e.g., repetitiveness for more than two hours, carrying/lifting loads, awkward postures and duration) [2–4]. Controlling of these occupational problems depends on understanding the causation of the problems. Identification of risk for injury or illness or for musculoskeletal fatigue and quantifying the level of risk by using data on human capabilities is helpful to set priorities for which ergonomics issues should be addressed in work situation. Fruit processing industry is becoming as an emerging economic aspect of Assam and it needs special attention in order to develop the economic status of the state. Almost all the fruit processing industries, particularly, the small and medium are in the hands of private sector; mostly do not have access to latest technology because of the prohibitive cost of technology. Workers engaged in fruit- processing industries may experience fatigue and discomfort while performing highly repetitive tasks, working in repeated and sustained or awkward postures, performing heavy physical work, and using forceful exertion. Continued work under these conditions may result musculoskeletal disorders, injuries and illnesses. Thus, realizing the need to study the prevalence of work-related health problems among the workers engaged in food processing units ‘occupational health hazard of workers engaged in food processing unit of Assam’ was carried out. Under the present study, attempt was made to find out the factors causing work-related health problems among the workers. The scope for design development for selected activities was also explored.
2 Methodology The study was conducted in two phases. In the first phase, a preliminary on-site analysis of different activities was done to understand the risk factor exposures and effects, thereby by conducting a survey. In the second phase of the study, scope for peeling of ginger (a commonly performed activity in all the surveyed fruit processing units) explored and then suitable modifications were made.
2.1 Selection of Sample For the survey, purposive cum random sampling procedure was used to select the sample. To collect the relevant data, Jorhat, Nagaon, Goalpara and Kamrup districts
Occupational Health Hazard of Workers Engaged in Food …
59
of Assam were selected. From the each selected districts, two industries from Jorhat, four industries from Nagaon, two industries from Kamrup and two from Goalpara district were selected randomly. A total of 100 workers (include both male and female workers) from the selected fruit processing industries were selected purposively based on the criteria formulated for the study. The respondents having physical ailment or deformity were excluded from the study. In case of women workers, pregnant and lactating women were also excluded. The workers who are involved in the performance of different fruit processing activities daily for more than 4 h were selected. Interview cum observation method was used to collect the data.
2.2 Data Collection Ergonomic risk factors prevailed among women workers that associate productivity and relevant health issues were studied by using postural assessment. Postures assumed by the workers while performing different activities and joint movement during the activity were studied by the flexi curve, observation and still photography technique, from which the postures were analyzed.
3 Results and Discussion 3.1 Workers in Fruit Processing Industries Activities The ‘fruit processing’ industry plays an important role in employing the majority of the industrial workers classes. According to Sharma and Jain [5], the agro-food processing industry employs around 18 percent of the country’s industrial workforce and is ranked fifth in terms of production, consumption, export and expected growth. It is an unorganized sector, mostly run by private establishments. It provides employment for both men and women and workers perform multitask activities like cutting, peeling, weighing, drying, cooking, packaging, etc., throughout the day manually. In the present study, the extent of involvement was studied in terms of extent of rarely, sometimes and daily and was scored as 1, 2 and 3, respectively. Mostly, performed activities were ranked based on the calculated weighted scores and mean scores. From the analyses of data, it can be concluded that stirring was found to be highly involved activity (rank I), followed by boiling (rank II), cutting/slicing/dicing (rank III), bottling/packaging (rank IV), peeling (rank V), washing and cleaning (rank VI), sorting (rank VII) and batch preparation/weighing (rank VIII).
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3.2 Prevalence of Ergonomic Risk Factors Occupational health hazard is a wide-spread trend. The causative factors of occupational health problems are poor ergonomic risk factors prevalent in workplace, which may be work accessories, static work, poor working posture, repetitive work, frequent bending and twisting, lifting and forceful movements, vibration, etc. In the present study, the prevalence of ergonomic risk factors was studied in terms of postural analyses, types of muscular efforts, involvement of joint movement and perceived joint discomfort.
3.2.1
Posture Assumed by the Respondents in Performance of Various Activities in Fruit Processing Industries
Proper posture helps muscles function properly, decreases abnormal wear of joints, prevents backaches and muscular pain, reduces fatigue and contributes to a good appearance. In many unorganized industry, awkward work posture repetitiveness and frequent bending and twisting, lifting and forceful movements, vibration, etc., are the major problems. In the present study, workers were found assuming varieties of working posture in performing different activities (Table 1).
3.2.2
Angle of Deviation from Neutral Posture
Angle of deviation from neutral posture was studied with help of Flexi curve. Analyses of data revealed that highest angle of deviations from normal curve were observed at upper while performing cutting fruits and vegetables. In case of stirring activity, angle of deviation was found more in lower back (Fig. 1).
3.3 Work-Related Health Problem/Musculoskeletal Problem Faced The major occupational hazards concerning work motivation and quality productivity in India are the musculoskeletal injuries. Work-related health problems range from discomfort, minor aches and pains to more serious medical conditions requiring time off work and even medical treatment. Understanding the causes of health problems, especially those that are work-related is the key to primary prevention Work-related musculoskeletal problems were quite prevalent among the workers. Low back pain was found very common among the workers which was followed by hand pain, elbow pain and finger pain. As regards to severity of work-related musculoskeletal problems among the workers from the data, it was revealed that acute low back pain was found prevalent among the workers, which was followed by
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Table 1 Analysis of different posture assumed by the respondents in performing different activities in fruit processing industries Activities
Types of posture
Illustration
Description
1. Washing and cleaning
Standing and moving
The workers stand in forward bending at low back with both arms below the shoulder level, both the hands outstretched for washing and cleaning the fruits and vegetables for further processing
2. Sorting
Standing and bending
The worker stands in upright position (for sorting of fruits and vegetables according to size) with bending of neck. Twisting of back is involved intermittently
3. Peeling
Sitting and bending
The worker sits in slight bending position on a stool with right hand peeling the fruits and vegetables and the left hand stretching to hold the fruits or vegetables
4. Cutting/slicing/dicing
Sitting and bending and moving
The worker sits on a stool in slight bending position at neck and low back with the hands outstretched for cutting, slicing and dicing of the fruits and vegetables
5. Batch preparation/weighing
Standing and moving
The workers stand in upright with hand outstretched below the shoulder level to hold the fruits and vegetables for precisely weighed quantities
6. Boiling
Standing and bending
The workers stand in forward bending both arms below the shoulder level with hand outstretched to boil fruits and vegetables (continued)
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Table 1 (continued) Activities
Types of posture
7. Stirring
Standing, bending and moving
The workers stand in forward bending at neck and waist, both arms below the shoulder level with the right hand rotating the spatula in a pan and the left hand fixed in static position
8. Botling/Packaging
Standing, bending, moving and twisting
The workers stand in forward bending both arms below the shoulder level with hand outstretched for bottling and packaging the processed products
9 8 7 6 5 4 3 2 1 0
Illustration
Description
Upper back Lower back Degree of deviaon
Fig. 1 Angle of deviation from neutral posture while performing different activities in fruit processing units
finger pain, hand pain, elbow pain and leg pain. Lower back pain and finger cuts/pain were observed as most frequently occurred problems among the workers which were followed by neck pain and finger pains.
3.4 The Design Development Peeling of ginger was found very commonly performed activity in all the surveyed processing units of Assam. The design development attempt was focused on modifying the existing knife and developing a thimble-like device to assist peeling. While
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Fig. 2 Modified knives for final field trial
to modifying the existing knife, the handle and blade of the knife were redesigned keeping the ergonomic principles in mind for comfort and ease of the workers. Finally, two knives with modified blade sizes, shapes and along with finalized handle size were selected for final trial (Fig. 2). Based on productive performance and feeling of ease of comfort while using both the finally selected knives, the knife with crescent-shaped blade was selected as the best work tool for peeling of ginger.
4 Conclusion From the discussions of the present study, it was observed that injuries were being reported by the workers. Analysis of work area showed, i.e., awkward postures, force, repetitiveness, joint discomfort, work tools and workstations were found as work-related musculoskeletal problems risk factors. The workers were forced to assume unnatural postures because of the task demand and the work method. Workers reported discomfort, or excessive fatigue in body parts, especially low back, neck, shoulder and mostly in fingers. Body parts were being damaged, especially the fingers. This indicates that the fruit processing activities and working conditions were conducive for developing WMSDs. It was felt that ergonomic interventions were deemed necessary to improve working conditions and decrease the level of exposure to WMSD risks. This led to see the design development specifically for peeling of ginger.
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References 1. WHO 1996. WHO global strategy For occupational health for all (the Way to health at work) (1986) 2. Frymoyer, J.W., Mooney, V.: Current concepts review, occupational orthopaedics. J. Bone Joint Surgery 68A, 469 (1986) 3. Waters, T.R.: Workplace factors and trunk motion in grocery selector tasks. In: Proceedings of the Human Factors and Ergonomics society 37th Annual meeting, pp. 654–658 (1993) 4. Crawford, L., Gutierrez, G., Herber, P.: Work environment and occupational health of dental hygientists: aq qualitive assessment. J. Occup. Environ ed. 47(6), 623–632 (2008) 5. Sharma, V.P., Jain, D.: High-value agriculture in India: past trends and future prospect. A working paper series published by Indian Institute of Management, Ahmedabad (2011)
Ergonomic Evaluation of a Car Interior: A Case Example on Shelby Cobra Anirban Chowdhury and Chaitanya Kachare
Abstract Vehicle ergonomics is an important concern to provide comfort to car drivers and other car occupants (e.g. passengers). Improper dimensions and placements of controls on dashboard might cause dissatisfaction of car occupants. Therefore, it is better to evaluate the car interior experience of the driver when designing a car. Furthermore, the consideration of human body dimensions is important for accommodation all types of occupants in the car. Hence, a case study was conducted on Shelby Cobra car model to demonstrate the importance of ergonomic evaluation of car interior. A questionnaire was used to evaluate the drivers experience about different parts of the car interior. An observational study was also conducted along with the questionnaire study. Eventually, the overall experience of drivers, gender and anthropometry-wise experience differences about car interior of Shelby Cobra model was evaluated and presented in this paper. Derivers reported several problems (such as improper placement of driving wheel and lack of legroom) about Shelby Cobra interior as designers considered only certain percentile value (e.g. only 95th percentile value) for all required human body dimensions when designed the car interior. Similar problems were also observed during the observational study. Keywords Automotive · Design · Experience · Perception · Vehicle ergonomics
1 Introduction Ergonomics evaluation is very important for packaging of a car as it is very challenging for designers to arrange seats, controls, dashboards and other interior elements within a small space. It is advised that car interior space should be comfortable to the car users or drivers [1]. There are many aspects of car interior design. Few A. Chowdhury (B) School of Design, University of Petroleum and Energy Studies, Dehradun 248007, India e-mail: [email protected] C. Kachare Institute of Design, MIT Art, Design and Technology University, Pune 412201, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_7
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eminent authors have reported about role aesthetics of interior compartments and dashboard design [2, 3]; whereas, other authors have described about wind-shield design of a car using nanomaterials [4]. The comfort and adjustability of controls and seats [5] are also important aspects of automobile ergonomics. Human body dimensions and location of different controls; visibility and attentional aspects are most important aspects as reported in automotive design literature [6]. In spite of these facts, often designers are ignoring these aspects while designing car interior and space. Furthermore, all cars are not suitable for all kind of somatotypes as anthropometry differs from country to country [7] and also from gender to gender [8]. Even adaptation of postures in confined space (like car interior) depends on anthropometry of drivers [9, 10]. There is a misconception among Indian designers that design of automobile interior considering 95th percentile value of all required human body dimensions is good for accommodating people with dimensions near various percentile values. Therefore, an attempt has been made to disprove this fact by evaluating the overall experience of drivers, gender and anthropometry-wise experience differences about car interior of Shelby Cobra model (1:1 scale, a model created by Indian Designers at MIT Institute of Design) were evaluated.
2 Methods 2.1 Design of Car Interior of Shelby Cobra Working Model Shelby Cobra model (1:1 scale, please see Fig. 1) was created by Indian Designers at MIT Institute of Design, Pune, India. During the car interior design phase, designers considered only the 95th percentile values of human body dimensions of Indian adults. No adjustability features were implemented for different interactive parts of the car interiors (driving wheel, gear, dashboard, displays and control panel etc.)
2.2 Questionnaire Survey and Observational Study 2.2.1
Participants
A total of 10 Indian adults were participated in this study. Their age ranged from 19–36 years (M age = 24.00 years; SD = 1.53 years). Averages of height and weight of participants were 165.60 cm (SD = 3.67 cm) and 65.70 kgs (SD = 4.93 kgs). The average body mass of participants was 23.69 (SD = 1.16).
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Fig. 1 Dimensions of car interior of Shelby Cobra
2.2.2
Tools and Measures
Experience of package of Shelby Cobra was evaluated using a vehicle package evaluation questionnaire adapted from an edited book [6]. This questionnaire evaluates experience of different components of car interior such as experience to steering wheel location, gas pedal and brake pedal locations, gearshift location, belt height, knee space and thigh space. A total of 13 items (Please see Table 1) were utilized for package evaluation of Shelby Cobra. Photographs were also taken using iPhone 5S during observational study.
2.2.3
Procedure
Drivers were asked to adopt a suitable driving position on Shelby Cobra, as per their convenience. Then, photographs were taken for all individual drivers during the observational study and it was conducted for all the drivers. A questionnaire survey was then conducted for evaluation of car interior-related experiences of drivers.
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Table 1 Rating scale for vehicle package evaluation Sl. No. Driver package consideration 1
Steering wheel longitudinal (fore/aft) location
2
Steering wheel vertical (up/down) location
3
Steering wheel diameter
4
Gas pedal fore/aft location
5
Gas pedal lateral location
6
Lateral distance between the gas pedal and the brake pedal
7
Gas pedal to brake pedal lift-off
8
Gearshift lateral location
9
Gearshift location longitudinal location
10
Height of the top portion of the instrument panel directly in front of the driver
11
Height of the armrest on driver’s door
12
Knee space (between instrument panel and right knee with foot on the gas pedal)
13
Thigh space (between the bottom of the steering wheel and the closest lower surface of the driver’s thighs)
3 Results and Discussion 3.1 Driver Experience for the Interior of the Shelby Cobra Model 3.1.1
Direct Observations
It is observed in this study that most of the drivers (80%) are unable to see speedometer and other indicators placed on dashboard (Please see Fig. 2a). The legroom was limited for many drivers (60%) (Please see Fig. 2b). Drivers who had comparatively short height (less than 50th Pc value of Indian population) also had less reachability to door handle (Please see Fig. 2c). There is also lack of thigh clearance observed for drivers (40%) (Please see Fig. 2d).
3.1.2
Overall Experience of Drivers About Car Interior
From the questionnaire study, it was revealed that there are problems in arrangements of different parts of car interiors. At about 20% people were not accepted the longitudinal locations (fore/aft) of steering wheel. A total of 40% people was not accepted the vertical locations (up/down) of steering wheel. About 30% respondents rejected the current height of the top portion of the instrument panel which was not placed directly in front of the driver; and about 30% drivers reported knee space (between instrument panel and right knee with foot on the gas pedal) was not acceptable. A
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Fig. 2 Images related to various problems of drivers seated in Shelby Cobra
total of 60% drivers complained that thigh space (between the bottom of the steering wheel and the closest upper surface of the driver’s thigh) was not acceptable.
3.1.3
Anthropometry-Wise Differences in Car Interior Experience of Occupants
There were about 70% participants who had their height below 50th percentile value of Indian population and 30% participants were with heights above 50th percentile value of Indian population. When compared these two groups (height below versus above 50th percentile) of people on their experience, it was observed that participants with height below 50th percentile was significantly more uncomfortable with steering wheel location (up/down) [Mabove = 1.67; SDabove = 1.15; Mbelow = 7.14; SDbelow = 1.57; F (1, 9) = 62.98; p < 0.001]. Similar results was also found in case of longitudinal gearshift location [Mabove = 5.00; SDabove = 1.73; Mbelow = 7.57; SDbelow = 0.79; F (1, 9) = 13.89; p < 0.01], height of the top portion of the instrument panel is not directly in front of the driver [Mabove = 4.33; SDabove = 2.52; Mbelow = 7.14; SDbelow = 1.35; F (1, 9) = 16.58; p < 0.05] and thigh space (between the bottom
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Table 2 Differences in average ratings of occupant experience parameters Sl. No.
Occupant experience
M ± SD >50th Pc.
M ± SD 8 h (ii) 11–15 h
(iii) 16–20 h
(iv) 21–24 h
(v) 0 h
(iv) Least
(v) Not at all
Rate your satisfaction with your work environment? (i) Good
(ii) Moderate
(iii) Low
References 1. Prince, M.M., Stayner, L.T., Smith, R.J., Gilbert, S.J.: A re-examination of risk estimates from the NIOSH occupational noise and hearing survey (ONHS), pp. 950–963 (2014) 2. Agrawal, Y., Niparko, J.K., Dobie, R.A.: Estimating the effect of occupational noise exposure on hearing thresholds: the importance of adjusting for confounding variables. Cdc 2006, 234–237 (2010) 3. Leensen, M.C.J., Van Duivenbooden, J.C., Dreschler, W.A.: A retrospective analysis of noiseinduced hearing loss in the Dutch construction industry, pp. 577–590, May 2000 (2011) 4. Majumder, J., Mehta, C.R., Sen, D.: Excess risk estimates of hearing impairment of Indian professional drivers. Int. J. Ind. Ergon. 39(1), 234–238 (2009) 5. Kumar, A., Mathur, Ã.N.N., Varghese, M., Mohan, D., Singh, J.K., Mahajan, P.: Effect of Tractor Driving on Hearing Loss in Farmers in India, vol. 348, pp. 341–348 (2005) 6. Karimi, A., Nasiri, S., Kazerooni, F.K., Oliaei, M.: Noise Induced Hearing Loss Risk Assessment in Truck Drivers, vol. 12, pp. 49–55 (2010) 7. Singh, L.P., Bhardwaj, A., Deepak, K.K., Bedi, R.: Occupational Noise Exposure in Small Scale Hand Tools Manufacturing (Forging) Industry (SSI) in Northern India, pp. 423–430 (2009) 8. Noweir, M.H., Zytoon, M.A.: Occupational exposure to noise and hearing thresholds among civilian aircraft maintenance workers. Int. J. Ind. Ergon. 43(6), 495–502 (2013)
Ergonomic Study on Foundry Workers Debasis Haldar, Rauf Iqbal, Asif Mahammadsayed Qureshi, and Vivek Khanzode
Abstract Introduction: The use of ergonomic principles in foundry industries has become an important part of a comprehensive health and safety process as well as an integral part of the engineering systems. The foundry activities are mostly manual in nature, having high physical workload which is due to combination of handling load manually and mismatch of human dimension and foundry equipment; therefore, anthropometric data of foundry worker male is very essential for appropriate and efficient designing of foundry workplace. Methodology: The data was collected in Kolhapur, Maharashtra, India. For making the data comprehensive and more useful, a set of 50 body dimensions, which were found to be applicable in the design of foundry workplace, was selected, which included different dynamic anthropometric measurements like arm reach length, height and ranges of motion. A dynamometer was also used to measure grip strength and a pinch gauge to measure tip, key and palmar pinch. Results: In case of foundry worker, the movement values in degree of upper arm [medial (42 ± 6.08), lateral (101.66 ± 3.51)], the grip strength in kg [right hand (31.6 ± 4.28), left hand (30.2 ± 7.24)] and the different pinch strength in kg [tip pinch (3.59 ± 0.94), key pinch (8.09 ± 1.46), palmar pinch(5.20 ± 1.20)] are different from the respective values of control group, that is movement values in degree of upper arm [medial (37 ± 10.13), lateral (119.45 ± 14.27)], the grip strength in kg [right hand (35.36 ± 7.87), left hand (30.09 ± 8.97)] and the different pinch strength in kg [tip pinch (4.09 ± 1.35), key pinch (7.54 ± 1.38), palmar pinch (6.31 ± 1.52)]. Various other parameters were also found different from control group. Conclusion: This anthropometric analysis and data could be used to design workplace for foundry workers which would not only incorporate adjustability, but also improve the level of comfort as well as productivity for the intended workers. Keywords Foundry · Anthropometry · Workplace · Dynamometer
D. Haldar · R. Iqbal (B) · V. Khanzode National Institute of Industrial Engineering, Mumbai, India e-mail: [email protected] A. M. Qureshi K.I. Ts College of Engineering, Kolhapur, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_16
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1 Introduction The Indian foundry industry is well established. According to the recent census of world casting production, India is the second largest casting producer with a production of ~7.44 million tonnes of various grades of castings; there are ~4500 units from which 80% are small scale units, 10% are medium and 10% are large-scale units and the industry directly employs ~500 000 people and indirectly ~150 000 people [1]. Foundry industry gives direct employment to about 25% of all industrial labours [2]. While industrial developments have brought obvious benefits, it has also frequently increased risk of accident, damage to the human health and environment [3]. Like in other manufacturing industries, the workshop environment in foundries comprises many hazardous factors [4]. The foundry activities are mostly manual in nature, having high physical workload which is due to combination of handling load manually and mismatch of human dimension and foundry equipment. Manual carrying is a major source of hazards and problems for industrial workers worldwide. It has been estimated that more than a quarter of all injuries related to industrial work are directly associated with MMH activities [5]. Tasks which are performed manually constitute a considerable proportion of work done in industries around the globe, especially in developing areas [1]. Therefore, the use of ergonomic principles in foundry industries has become an important part of a comprehensive health and safety process as well as an integral part of the engineering systems. The aim of ergonomics is to optimize safety, health, comfort and efficiency of the human in the work system. Physiological activities in foundries in an ergonomic sense involve reaching, bending, lifting heavy objects, using continuous force, working with vibrating equipment and repetitive motion. It is important to implement safety and health policy to protect workers. Ergonomics enhances human performance, including the health, safety and productivity of workers [6]. In workstation design, ergonomic consideration involves matching the physical characteristics and layout of components in relation to anthropometric characteristics of the anticipated user population. This matching includes spatial accommodation, adequacy of posture, positioning of controls according to function, the ability to reach and see all the necessary elements, adequacy of strength to operate the control, ingress, egress and free mobility of the workstation users [7]. The compilation of anthropometric data is a much needed and worthwhile to design tools, equipment and workstation as well as to assess them ergonomically [8]. Therefore, anthropometric data of foundry worker male is very essential for appropriate and efficient designing of foundry workplace.
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2 Methodology 2.1 Worker Selection and Data Collection The present study was undertaken at foundry unit in Kolhapur area in Maharashtra, India. A total of 45 male foundry workers aged between 21 and 53 years were selected; their height and body weight were measured. Simple random sampling was used to select foundry worker. A set of 50 body dimensions, which were found to be applicable in the design of foundry workplace, was selected and measured, which included different dynamic anthropometric measurements like arm reach length, height and ranges of motion [9]. Grip and pinch strength of these workers were also measured. Same measurements were also taken from a group of PG students as a control group.
2.2 Dimensions and Instrument Used Ranges of motion. By using goniometer, the movements (degree) of upper arm [medial movement (the shoulder is fixed and hand is moved towards the midline) and lateral movement (moves the hand away from midline when shoulder is fixed)] were measured. Arm reaches dimensions. By using anthropometer and measuring tape, length from back and height from floor in cm of three different position (upper, mid and lower) of arm reaches of different postures were measured, that is erect standing with forward comfortable arm reach, standing with one forward step and leaning posture, erect standing with sideways comfortable arm reach, standing with one sideways step with leaning posture, standing with backward comfortable arm reach and standing with one backward step and leaning posture. Hand grip and pinch strength. The grip strength is the result of forceful flexion of all finger joints with the maximum voluntary force that the subject is able to exert under normal biokinetic conditions [10]. A hydraulic dynamometer was used to measure hand grip strength. A pinch gauge was used to measure tip pinch (thumb tip to index fingertip), key pinch (thumb pad to lateral aspect of middle phalanx of index finger) and palmar pinch (thump pad to pads of index and middle fingers). Workplace dimensions. The workplace where mould is being prepared (moulding section) was selected, and various dimensions of different workpieces in respect to workers were measured.
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2.3 Statistical Analysis Standard deviation (SD), mean, 5th, 95th and 50th percentile of above anthropometric measurements were calculated. One-tailed t test was applied to find out significant difference between two groups. The selected level of alpha significance for all tests was p = 0.05.
3 Result and Discussion Mean standing height of foundry worker was found 159.4 cm, whereas 5th, 50th and 95th percentile were 152, 165 and 174.8 cm, respectively. Mean weight of foundry worker was found 62.09 kg, and 5th, 50th and 95th percentile of weight were 50, 62 and 77 kg, respectively, which is significantly different from control group (p = 0.05). Weight of foundry worker ranged between 48 and 78 kg. It shows the fact that weight of tools or equipment for worker should be handy and comfortable to use. Heavy weight tools or equipment may be heavy for them to operate (Table 1). Full upper-limb kinematics was calculated for several Activities of Daily Living (ADLs) in healthy participants [11]. In this study, in case of foundry worker mean movement values in degree of upper arm [right arm medial (42 ± 6.08), left arm medial (101.67 ± 3.51), right arm lateral (101.67 ± 3.51) and left arm lateral (100.2 ± 5.19)] are different from mean movement values in degree of upper arm of control group [right arm medial (37.36 ± 10.13), left arm medial (39.27 ± 8.71), right arm lateral (119.45 ± 14.27) and left arm lateral (119.45 ± 15.78)]. Except the medial movement of right arm, all the movement values of workers of both upper arms were found significantly different from control group (p < 0.05) (Table 2). During standing in erect posture, mean forward comfortable arm reach at upper position from back was found 63.14 cm and height from floor was 190.14 cm, whereas 5th percentile of length and height were 49.3 cm and 177.2 cm, respectively, of foundry workers. But in case of control group, mean forward comfortable arm reach Table 1 Age, height and weight of foundry workers and control group Parameter
Group
Mean ± SD
Percentile 5th
50th
95th
Age (years)
Foundry worker
35.19 ± 9.37
25
35
52
Control group
23.45 ± 1.69
22
23
26.5
Height (cm)
Foundry worker
159.37 ± 22.80
152
165
174.8
Control group
170.18 ± 7.44
160
169.6
181.9
Foundry worker
62.09 ± 7.82
50
62
77
Control group
68.18 ± 13.05
50.55
64.6
84.6
Weight (kg)
*Statistically significant (p < 0.05)
P Value 0.0001* 0.069 0.054*
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Table 2 Medial and lateral movement of upper arm in degree Upper arm
Right arm
Left arm
Movement
Group
Dimension (degree) Mean ± SD
Percentile 5th
50th
95th
P Value
42 ± 6.08
36
45
45.9
Medial
Foundry worker Control group
37.36 ± 10.13
26
34
53
Lateral
Foundry worker
101.67 ± 3.51
98.4
102
104.7
Control group
119.45 ± 14.27
102.5
122
140
Medial
Foundry worker
52 ± 5.29
48.2
50
57.2
Control group
39.27 ± 8.71
27
44
49
Foundry worker
100.2 ± 5.19
95.5
100
104.5
Control group
119.45 ± 15.78
99
120
142.5
Lateral
0.235 0.029* 0.013* 0.031*
*Statistically significant (p < 0.05)
at upper position from back was found 71.02 cm and height from floor was 186.08 cm, whereas 5th percentile of length and height were 59.75 cm and 174.2 cm, respectively. These values of workers are significantly different from control group (p ≤ 0.05). In this same posture of workers, the 5th percentile value of arm reach length and 50th percentile value of arm reach height at mid-position were found 83.6 cm and138 cm, respectively, and the 5th percentile value of arm reach length and 95th percentile value of arm reach height of lower position were found 60.55 cm and 95.4 cm, respectively, which is also different from respective values of control group. When workers are standing with one step forward in front leaning posture, erect standing with sideways comfortable arm reach and standing with one side step with side leaning posture, the above percentile values were also found different from control group. This suggests that the maximum forward and sideways arm reach and height of worker during operation should be within these percentile values for operating properly (Table 3). During standing in erect posture, mean backward comfortable arm reaches from back of both upper and mid-positions of workers were found 39.1 cm and 66.1 cm, respectively, and 5th percentile of both positions were 21.8 cm and 46.8 cm, respectively. Whereas in control group mean backward comfortable arm reaches from back of both upper and mid-positions were found 49.55 cm and 55.88 cm, respectively, and 5th percentile of both positions were 39.67 cm and 41.15 cm, respectively. The difference of these values of control groups and workers was found statistically significant (p < 0.05). But when workers were standing with one backward step in back leaning posture, there was found significantly different values between these two groups of both arm reach length and height instead of only length. In this posture, worker’s mean backward comfortable arm reach length of upper position from back was found 91.7 cm and height from floor was 178.3 cm, whereas 5th percentile of length and height were 78.15 cm and 167.4 cm, respectively. But in case of control group, mean backward comfortable arm reach length of upper position from back was found
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Table 3 Standing arm reach and height in cm (forward and sideways) Movement
Standing in erect posture, forward comfortable arm reaches from back and height from floor
Position Parameter Group
Upper
Length
Foundry 63.14 ± 8.22 worker Control group
Height
Length
Length
Length
p Value
49.3
65.5
73.2
0.003*
59.75 72.6
81.7
177.2 191.5 201.35 0.05* 174.2 186
196.8
83.6
89.5
98
80
87.5
97.6
126.2 138
Foundry 84.87 ± 9.96 worker
69.35 86.5
95.4
79.2
88
101
113
138.6
Foundry 116.76 ± 12.24 104 worker 112.18 ± 8.54
Foundry 129.07 ± 7.6 worker
154
185.8
178
188.3
117.8 129
140.4
0.162
0.123
0.211
0.095
124.79 ± 12.54 110.9 120.6 145.8
Foundry 122.92 ± 11.74 106.4 124 worker Control group
0.485
102.1 108.8 126.85
Foundry 167.76 ± 11.30 153.6 167 worker 172.8 ± 12.35
0.258
131.2 143.5 154.5
81.95
88.40 ± 8.68
0.175
150.1
60.05 69.5
Control group Height
95th
70.55 ± 8.12
Control group Length
50th
76
Control group Height
5th
60.55 71.5
Control group Standing Upper with one forward step in front leaning posture, forward comfortable arm reaches from back Mid and height from floor
143.09 ± 9.4
Percentile
Foundry 69.85 ± 5.77 worker Control group
Height
87.85 ± 6.80
Foundry 139 ± 8.53 worker Control group
Lower
186.08 ± 7.76
Foundry 90.35 ± 4.98 worker Control group
Height
71.02 ± 7.73
Foundry 190.14 ± 9.32 worker Control group
Mid
Dimension (cm) Mean ± SD
126.18 ± 13.4
140.4
0.269
106.8 126.5 142 (continued)
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Table 3 (continued) Movement
Position Parameter Group
Lower
Length
Foundry 123 ± 10.008 worker Control group
Height
Upper
Length
Length
Length
Upper
Length
50th
107.8 125
95th
p Value
136.4
0.201
100.1 112.2 148.05 53.6
66
84.8
47
71.7
138.2
65.8
77
81.8
0.132
0.206
69.09 76.75 93.29 179
81
89
197.6
94.6
80.93 87
99.34
131
147.2
134
0.425
205.93 0.395
0.122
130.4 142.2 153.5 64
71
75
0.329
59.13 70.45 81.92 75.8
86
84.75 ± 11.09
72.9
82.55 101.8
Foundry 84.33 ± 10.81 worker
69.8
83
Control group Height
71.41 ± 8.16
Foundry 85.76 ± 5.84 worker Control group
Standing with one side step with side leaning posture, sideways comfortable arm reaches from spine and height from floor
142.02 ± 8.3
Foundry 70.53 ± 3.99 worker Control group
Height
88.84 ± 7.07
Foundry 137.46 ± 6.27 worker Control group
Lower
5th
183.15 ± 15.97 164.1 181
Foundry 88.38 ± 4.42 worker Control group
Height
78.08 ± 9.86
Percentile
Foundry 181.07 ± 11.84 162 worker Control group
Mid
79.40 ± 16.11
Foundry 75.84 ± 6.99 worker Control group
Height
118.9 ± 17.89
Foundry 66.61 ± 11.65 worker Control group
Standing in erect posture, sideways comfortable arm reaches from spine and height from floor
Dimension (cm) Mean ± SD
93
99.4
0.427
0.006*
100.44 ± 13.63 83.46 100.3 121.9
Foundry 174 ± 8.97 worker
161.4 178
184.6
0.434
(continued)
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Table 3 (continued) Movement
Position Parameter Group
Control group Mid
Length
Length
164.4 170.7 184.81
5th
130.83 ± 4.74
100.9 ± 20.14
Foundry 67.22 ± 11.3 worker Control group
50th
111
95th
120.2
p Value
0.224
112.86 ± 14.68 93.98 112.3 136.3 124.4 131
77.26 ± 14.85
140.4
0.412
124.2 131.5 136.9
Foundry 108.11 ± 14.96 84.6 worker Control group
Height
173.13 ± 8
Foundry 131 ± 5.95 worker Control group
Lower
Percentile
Foundry 108.89 ± 11.32 90.8 worker Control group
Height
Dimension (cm) Mean ± SD
113
123
73.5
100.6 124.5
54.2
64
81.6
0.217
0.088
56.85 77.25 96.97
*Statistically significant (p ≤ 0.05)
99.96 cm and height from floor was 170.57 cm, whereas 5th percentile of length and height was 86.3 cm and 157.3 cm, respectively, and this is significantly different (p < 0.05) (Table 4). Measurement of grip strength is an important component for hand efficiency [12]. In this study, we found that the mean grip strength in kg [right hand (31.6 ± 4.28), left hand (30.2 ± 7.24)] for the foundry workers and [right hand (35.36 ± 7.87), left hand (30.09 ± 8.97)] for control group. The right-hand grip strength has been found significantly lower (p < 0.05) in foundry workers (Table 5). Similar to hand grip strength values, the mean values of three types of pinch (tip, key and palmar) strength were found different between workers and control group. Mean palmar pinch strength of right hand was found 5.20 kg for the workers is significantly different (p < 0.05) from the mean palmar pinch strength value of right hand of control group (6.31 kg). Lower grip as well as pinch strength in foundry workers is probably because of physical work load that needs force application coupled with improper rest (Tables 6 and 7). Moulding work, a major process in a foundry often requires long-term skills and hence maintains traditional work methods. Many kinds of moulding work are performed at the floor level; handling of heavy materials is done by the worker in deep bending or squatting postures. As a result, the majority of such workers suffer from low back pain [4].
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Table 4 Standing (backward) arm reach and height in cm Movement
Position Parameter Group
Standing in Upper erect posture, backward comfortable arm reaches from back and height from floor Mid
Length
Foundry 39.1 ± 14.78 worker Control group
Height
Length
Length
21.8
33
58
0.031*
39.67 50.4
61.11
162.7 183
198.8
46.8
70.5
78
0.035*
24.8
47.5
68.85
31.11 39.8
58.05
68.25 80
90.65
81.62 ± 12.2
61.06 85
93.55
Foundry 91.7 ± 10.67 worker
78.15 90
106.4
86.3
111.61
136.94 ± 8.73
Foundry 46.6 ± 15.85 worker 42.07 ± 9.66
Foundry 80.3 ± 7.68 worker
99.96 ± 9.15
Foundry 178.3 ± 7.55 worker 170.57 ± 9.55
98.95
167.4 178.5
189.1
96.8
107.5
119.3
107.8 ± 9.55
96.6
109.1
116.7
110.1 133.5
147.7
Control group
0.108
0.225
0.387
0.039*
0.03*
157.3 169.85 183.75
Foundry 107.5 ± 9.22 worker
Foundry 130.1 ± 14.44 worker
0.298
165.7 182.25 191.2
150.2
Control group Height
p Value
126.9 135.5
Control group Length
95th
141.5
Control group Height
50th
124.8 131.5
Foundry 132.5 ± 6.65 worker
Control group Standing Upper with one backward step in back leaning posture, backward comfortable arm reaches from back Mid and height from floor
5th
69.19
Control group Height
55.88 ± 10.88
Percentile
41.15 57.3
Control group Lower
180.5 ± 9.36
Foundry 66.1 ± 12.79 worker Control group
Height
49.55 ± 7.79
Foundry 183.4 ± 13.97 worker Control group
Length
Dimension (cm) Mean ± SD
130.92 ± 11.15 115.3 132
0.469
0.444
146.7 (continued)
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Table 4 (continued) Movement
Position Parameter Group
Lower
Length
95th
p Value
76.45 101
113.2
0.298
78.72 93.55
107.9
58.45 71
87.8
78.04 ± 10.06
63.23 80
90.4
Hand grip strength (kg) Mean ± SD
Percentile 5th
50th
95th
31.6 ± 4.28
27.2
32
38.4
Foundry 96 ± 15.04 worker Control group
Height
Dimension (cm) Mean ± SD
92.82 ± 1o.9
Foundry 70.8 ± 11.27 worker Control group
Percentile 5th
50th
0.073
*Statistically significant (p < 0.05)
Table 5 Hand grip strength in kg Hand grip strength
Group
p value
Right hand
Foundry worker Control group
35.36 ± 7.87
25
34
47.5
Left hand
Foundry worker
30.2 ± 7.24
19.8
32
38.4
Control group
30.09 ± 8.97
19
30
43.5
0.043* 0.456
*Statistically significant (p < 0.05) Table 6 Pinch strength in kg Pinch strength
Tip pinch
Key pinch
Palmar pinch
Group
Pinch strength (kg) Mean ± SD
Percentile
p value
5th
50th
95th
3.59 ± 0.94
2.5
3.5
5.25
Right hand
Foundry worker Control group
4.09 ± 1.35
2.75
4
6.25
Left hand
Foundry worker
3.81 ± 1
2.75
3.5
5.25
Control group
3.53 ± 0.93
2.5
3.4
5
Foundry worker
8.09 ± 1.46
6
8
9.75
Control group
7.54 ± 1.38
5.75
7.5
9.75
Left hand
Foundry worker
7.81 ± 1.73
5.5
7.5
10.25
Control group
7.04 ± 1.69
5
6.5
9.75
Right hand
Foundry worker
5.20 ± 1.20
3.5
5
7
Control group
6.31 ± 1.52
4.75
6
8.75
Foundry worker
5.43 ± 1.75
3.25
5.25
7.75
Control group
5.4 ± 1.2
4
5
7.25
Right hand
Left hand
*Statistically significant (p < 0.05)
0.163 0.252 0.19 0.151 0.035* 0.486
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Table 7 Dimensions of workstation features from the working position (moulding section) Parameters
Control box
Length from 62 working position (cm) Height from Floor (cm)
58
Hopper lever
Air gun
Crane control
Moulding box
Accessories
Conveyor
3
142
73
37
80
140
181
160
158
110
88
72
Length of different workpiece from the working position of worker and height from floor in moulding section were measured and compared with dimensions of the workers. It was found that many of the dimensions of workstation have a mismatch in respect to the dimensions of the workers. -The distance between air gun and working position of worker was measured 142 cm, whereas the 5th percentile and mean value of arm reaches of mid-position were found 117.8 cm and 129.07 cm, respectively, when the posture of workers was standing with one step forward and front leaning. The height of control box from floor is 58 cm, whereas the comfortable working height at lower position in standing erect posture of workers has been found 95.4 cm (95th percentile) and 84.87 cm (mean value), respectively (Fig. 1). The distance between worker and the accessories at the back side of the worker was measured 80 cm, whereas 5th percentile and mean value of backward comfortable arm reaches of mid-position were found 46.8 cm and 66.1 cm, respectively (Fig. 1). This will not only lead to backward leaning resultant fatigue but also take extra time to complete job.
Air Gun
Hopper Lever
Moulding Box Crane Control Working Position
Accessories
Conveyor Control Box
Fig. 1 Workplace (moulding section) in foundry industry
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4 Conclusion This study has highlighted some of the concerns associated with dynamic anthropometry at workstation like reach, height and strength of foundry workers. This anthropometric analysis and data could be used to design workplace for foundry workers which would not only incorporate adjustability, but also improve the level of comfort as well as productivity for the intended workers. The data can be used to design area specific tools and equipment for the foundry workers. This can reduce the occupational health problems and injuries as well as enhance efficiency and productivity.
References 1. Sharma, R., Singh, R.: Work-related musculoskeletal disorders, job stressors and gender responses in foundry industry. Int. J. Occup. Safety Ergon. 20(2), 363–373 (2014) 2. More, R.B., Sawant, V.A.: Physiological profile of foundry workers in response to work place environment. Biolog. Forum—An Int. J. 2(2), 42–45 (2010) 3. Dell, T., Berkhout, J.: Injuries at a metal foundry as a function of job classification, length of employment and drug screening. J. Safety Res. 29(1), 9–14 (1998) 4. Horino, S.: Environmental factors and work performance of foundry workers. J. Hum. Ergol. 6, 159–166 (1977) 5. Frederick, T.K., Kumar, A.R., Karim, S.: An ergonomic evaluation of a manual metal pouring operation. Int. J. Industr. Eng. 38, 182–192 (2008) 6. Mali, C.S.,Vyavahar, R.T.: An ergonomic evaluation of an industrial workstation: a review. Int. J. Curr. Eng. Technol. 5(3) (2015) 7. Sengupta, A.K., Das, B.: Human: an autucad based three dimensional anthropometric human model for workstation design. Int. J. Industr. Eng. 19, 345–352 (1997) 8. Singh, S., Ahlawat, S., Pandya, S., Prafull, B.: Anthropometric measurements and body composition parameters of farm women in North Gujarat. J. Ergon. 3 (2013) 9. Chakrabarty, D.: Indian anthropometric dimension. National Institute of Design, Ahmedabad 380007, India (1997) 10. Incel, N.A., Ceceli, N., Durukan, P.B., Erdem, H.R., Yorgancioglu, Z.R.: Grip strength: effect of hand dominance. Singapore Med. J. 43(5), 234–237 (2002) 11. Gates, D.H., Walters, L.S., Cowley, J., Wilken, J.M., Resnik, L.: Range of motion requirements for upper-limb activities of daily living. Am. J. Occup. Ther. 70(1), 1–10 (2016) 12. Simmond, S.J., Syddall, H.E., Westbury, L.D., Dodds, R.M., Cooper, C., Sayer, A.A.: Grip strength among community- dwelling older people predicts hospital admission during the following decade. Age Ageing 44(6), 954–959 (2015)
Modernizing Ergonomics Through Additive Manufacturing Technology Mohd Imran Khan , Shahbaz Khan , and Abid Haleem
Abstract Being an advanced manufacturing technology, additive manufacturing is competent in producing a highly customized product, irrespective of the complexity involved, by simply adding materials layer after layer and building the whole part in one unit. The purpose of this paper is to align ergonomics with modern manufacturing methods explicitly additive manufacturing technology. This paper also analyses the existing problems and challenges faced by the workforce working on the shop floor due to the unavailability of individual customization. Additive manufacturing technology has a capability to produce customized pieces of equipment which are ergonomically fit for individual users. This paper may help to understand the scope of additive manufacturing technology in humanizing work and work environment. This paper aims to provide references for the development direction of additive manufacturing technology in the area of ergonomics. Keywords Additive manufacturing technology · Ergonomics · Customization · Rapid prototyping · Workforce · 3D technology
1 Introduction Additive manufacturing (AM) technology is based on the principle of accumulation of material, instead of material subtraction as in traditional manufacturing methods, and it is considered to be a disruptive technology in the field of manufacturing [1, 2]. Through this technology, it became possible to manufacture the entire component by means of the gradual accumulation of material. Term AM is generally used for all the technologies which can produce a 3D entity directly in physical form M. I. Khan Mittal School of Business, Lovely Professional University, Phagwara, Punjab - 144411, India S. Khan (B) GLA University, Mathura - 281406, India e-mail: [email protected] A. Haleem Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_17
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which is consistent with their mathematical model. AM technology is an integration of technologies such as CAD, mechanical engineering, laser technology, materials science, layered manufacturing method, and NC technology. Through this integration of technologies, any design idea can be turned into a functional prototype or even component can be produced [3]. In the last 20 years, AM technology has been evolved and is becoming a mainstream manufacturing method. Different terminologies, such as “rapid prototyping”, “solid free-form fabrication”, and “three-dimensional printing”, are used interchangeably with AM technology [4]. Recent advances in AM technology have made it possible to become an alternative to traditional manufacturing in various application areas. Policy planners are using this technology for strategic development of their industry. Through the combination of information technology with new materials, this technology is becoming a face of “the third industrial revolution” [5–7]. AM technology has many prominent advantages when compared with traditional machining and distortion processing method such as “direct manufacturing process without moulds,” “unrestricted degree of structural complexity,” “high utilization of materials,” “providing more freedom for the innovative design” and “environment friendly”. Intense Research and Development (R&D) in AM technology have made possible to meet the growing demand of areas which needs high precision and customization, such as customized medical implants, an individual customized product for ergonomic needs, low quantity customized industrial products, cultural and creative displays, and other items [8–10]. In near future, application of AM technology is inevitable to expand in automotive, aerospace, space and other emerging fields. When the application of AM technology is extended in ergonomics, it enhances productivity and prevents injury by customizing products for individual use. Product developed through AM technology increases ergonomics performance of individual workers.
1.1 Linking AM Technology Features with Ergonomics Development of virtual model through AM technology gives a better idea to the designers before producing physical entity. The following feature of AM technology makes it suitable for individual customization in ergonomics: a. b. c. d. e. f. g.
reduction in production time production of lightweight component accuracy and precision in component produced reconstruction of components improved quality of components produced quickly create models at lower cost exact fitting of various parts of the human body
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h. excellent surface quality i. enhanced aesthetic property. Thus, it is evident that the distinguishing feature of AM technology can make the ergonomics more reliable and can humanize the workplace to a greater extent.
2 Need of the Study Many problems of shop floor workers related to health, physical stress, and fatigue are reported in the literature. There are many reasons for these problems regarding the health and efficiency of the workers such as working condition, job type, lack of safety equipment, and lack of individual customized product. Most of the literature address the working conditions of the industry are rarely focused on the individual customization of the ergonomics products. Standardized ergonomic equipment is adjustable and designed to accommodate a wide range of body sizes and shapes but may not satisfy the demand of each and every worker on shop floor due to the complex nature of the human body. In this paper, we suggest that AM technology may deliver individual customization with low production time and in turn, may reduce the health/safety-related issue of worker and enhance productivity. This study proposes AM technology to overcome the issues faced by workers due to the lack of individual customization.
3 Potential Use of AM Technology in Ergonomics 3.1 Cost This is one of the most important factors of any business activity. AM technology is providing a high-quality product at a lower cost [11]. This is possible by reduced material waste, low power consumption, ease in design, and automated systems in production [12]. The workers’ accessories such as helmet, safety goggles, gloves, and shoes depend on the shape or body structure of the worker. Individual customizations are costlier by conventional manufacturing technique. Therefore, companies are not interested to invest the money on the customized workers accessories which leads to creating fatigue as well as other health-related issues. However, AM technology may provide customized products for individual use at a lesser cost. This can motivate the top management to adopt individually customized accessories for the workers.
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3.2 Material Flexibility One of the major advantages of AM technology is the flexibility in the use of material [13, 23]. AM technology can use a range of material for producing high-quality component [14]. Flexibility in materials enhances the quality of the product in terms of surface finish, strength to weight ratio. Ergonomically fit product can be manufactured by reaping the benefit of material flexibilities. Materials can be selected based on the requirement, e.g., soft materials may be used for the gloves, shoes, etc. A significant criterion for product selection is the strength to weight ratio. The weight of a component can be reduced by using lighter material which may ultimately provide an injury free workforce. Different materials can be used in different parts of the component. The strength of the parts depends on the material used as well as the post-processing method. Due to flexibility in post-processing material the strength can also be increased by changing the post-processing material.
3.3 Customization Numerous studies shows that the application of AM technology in different applications such as medical and low quantity customization [15]. In ergonomics, there is a need for products which is highly customized in nature and can satisfy individual demand. AM technology has a tremendous capability to customize the product which can be utilized to produce ergonomically fit product for individual user [16]. In the AM technology, according to the posture and shape of worker equipment or accessories can is designed and manufactured. Individual customization is done through reverse engineering. The body part (e.g., hand to design gloves) is scanned with the help of a 3D scanner, and this scanned file is imported in CAD software. This CAD model is modified and designed for the required product. The designed part is saved in STL file which is required for the 3D printing. This STL model is printed with the help of a 3D printer.
3.4 Rapid Availability Rapid product availability is one of the major concerns of the production system. A study conducted by Ng et al. [17] shows that a socket is manufactured in four hours instead of a day with the help of AM technology. This process enhances the speed of manufacturing. Individual customization takes more time by traditional manufacturing methods, but in AM technology, these customizations are done rapidly [18]. If a new worker is joined the workforce, then the accessories are demanded as soon as possible. With the help of AM technology, these accessories are available in shorter time along with fit and comfort.
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Fig. 1 CAD model for 3D printing
3.5 Weight Reduction In the context of ergonomically fit design, one major issue is the weight of product or accessories. The weight of equipment and accessories causes many types of temporary and permanent injury. Weight can be reduced through improved design as well as improved materials [16]. Through improved design, the weight can be reduced by cutting down unnecessary materials [16]. The design can be enhanced through the grid structure in place of solid fill structure. Figure 1 shows the improved design model of a helmet which reduced the weight of the helmet.
4 Adoption of AM Technology AM technology is highly automated manufacturing technology with the capability to manufacture complex shape. This technology consumes lesser electric power during the manufacturing of the product, and this power consumption can be further reduced by optimizing process parameters such as layer thickness and material type [19]. These capabilities attract the industry to adopt AM technology for its efficient and cleaner production. AM technology generally produced the final product which reduces the assembly effort [20, 21, 24]. These assemblies are a repetitive kind of work which is the main cause of the fatigue in workers. Therefore, adoption of the AM technology may reduce the worker’s fatigue. Another factor which differentiates the AM technology from conventional manufacturing technology is a material waste. The material waste is very less in AM technology which reduces the disposal of the waste materials. With the less waste, this technology provides less impact on the environment which is the major concern of today’s world. AM technology setups are highly automated, which required less human interaction, and manufacturing operations (i.e., addition of layer) is performed in a closed chamber or environment. These capabilities of AM technology reduced the chances of accident and enhanced worker safety. From the above discussion, we find that
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AM technology is highly automated, efficient, cost-effective, eco-friendly, and safe. Therefore, adoption of this technology can reduce the cost, environmental impact, and ergonomics-related issues.
5 Research Direction and Future Scope AM technology has a capability of enhancing customization and usage of product at a lower cost. Flexible nature of AM technology has disrupted conventional fabrication of ergonomically designed products by providing highly customized products. Through this technology, a specific geometrical model can be produced physically with a high degree of accuracy for humanizing work and work environment. By focusing on individual customer need AM technology is changing industrial manufacturing model. In recent trends, the performance and reliability of materials used in the development of the product through AM technology are poor and poses a barrier in the development of customized additive manufacturing moulding technology. Developing new materials such as functionally graded materials, tissue engineering materials, non-homogeneous materials, has important significance to the development of AM technology. Progress in the area of technology up-gradation, cost reduction is in the nascent stage and needs full consideration for its commercialization and greater business value [22]. To standardize the AM technology in the manufacturing industry, a lot of R&D work needs to be accomplished.
6 Conclusion Being an advanced technology, AM technology has the potential to produce a part/component with high precision, at a faster speed and with high reliability for individual need. During an industrial operation, accessories of worker are very complex and need a high degree of customization for individual use; in such cases, AM technology may play a vital role to produced customized product for individual workers. With the development of new material, AM technology may bring revolution in the area of ergonomics by producing a customized product for individual use.
References 1. Xu, B.S: Remanufacture engineering and its development in China. China Surf. Eng. 23(16) (2010) 2. Wang, H.J.: Research status and development tendency of additive manufacturing. J. Beijing Inf. Sci. Technol. Univ. 3, 20–24 (2014) 3. Wang, G.C.: Application of additive manufacturing. 3rd Edn. China Machine Press, China (2014)
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4. Xu, R.P.: Rapid Prototyping Technology and Rapid Prototyping Manufacturing. 3rd Edn. Atomic Energy Press, China, Beijing (2004) 5. Walters, P., Davies, K.: 3D printing for artists: research and creative practice. J. Norwegian Print Assoc. 5(1), 12–15 (2010) 6. S& P Consulting (2013) 3D printing will bring manufacturing revolution, (online). https:// news.xinhuanet.com/yzyd/fortune/20130527/c_115924936.htm?prolongation=1%3e. Last Accessed 20 Oct 2017 7. Lu, B.L., Di, C.: Development of the additive manufacturing (3D printing) technology. Machine Build. Autom. 4, 1–4 (2013) 8. Dimitrov, D., Schreve, K.D.B.N.: Advances in three-dimensional printing-state of the art and future perspectives. J. New Gener. Sci. 4(1) (2006) 9. Gibson, I., Rosen, D.W.S.B: Additive manufacturing technologies. 23 edn. Springer, New York (2010) 10. Yu, D.M., Fang, A., Zhang, J.B.: 3D printing: technology and application. Metal World 6, 6–11 (2013) 11. Wang, G.C., Wang, X.Y., Zhao, G.Q.: Laminated object manufacturing technology of rapid prototyping. J. Shandong Univ. Technol. 1(1), 59–64 (2001) 12. Lian, C., Yong, H., Yingxin, Y., Shiwei, N., Haitao, R.: The research status and development trend of additive manufacturing technology. Int. J. Adv. Manuf. Technol. 89, 3651–3660 (2017) 13. Salmi, M., Tuomi, J., PaloheimoKaija, S., Björkstrand, R., Paloheimo, M., Salo, J., Kontio, R., Mesimäki, K., Mäkitie, A.A.: Patient specific reconstruction with 3D modeling and DMLS additive manufacturing. Rapid Prototyping J.18(3), 209–214 (2012) 14. Lei, S.C., Frank, M.D., Anderson, D., Brown, T.: A method to represent heterogeneous materials for rapid prototyping: The matryoshka approach. Rapid Prototyp. J. 20(5), 390–402 (2014) 15. Milovanovic, J., Trajanovic, M.: Medical applications of rapid prototyping. Mech. Eng. 5(1), 79–85 (2007) 16. Eyers, D., Dotchev, K.: Technology review for mass customisation using rapid manufacturing. Assembly Autom. 30(1), 39–46 (2010) 17. Ng, P., Lee, P.S.V.: Goh JCH : Prosthetic sockets fabrication using rapid prototyping technology. Rapid Prototyp. J. 8(1), 53–59 (2002) 18. Graham, S.: Rapid prototyping: a key to fast-tracking design to manufacture. Assemb. Autom. 20(4), 291–294 (2000) 19. Javaid, M., Haleem, A.: Additive manufacturing applications in medical cases: A literature based review. Alexandria J. Med. (In press) (2017) 20. Gibson, I.: The changing face of additive manufacturing. J. Manuf. Technol. Manag. 28(1), 10–17 (2017) 21. Nicholas, A.M., Christopher, B.W., Kimberly, P.E., Don, T.: Decision support for additive manufacturing deployment in remote or austere environments. J. Manuf. Technol. Manag. 27(7), 898–914 (2016) 22. Bhattacharjya, J., Tripathi, S., Taylor, A., Taylor, M., Walters, D.: Additive manufacturing: current status and future prospects. In: Collaborative Systems for Smart Networked Environments, Springer Berlin Heidelberg, pp. 365–372 (2014) 23. Fatma, N., Haleem, A., Javaid, M., & Khan, S.: Comparison of fused deposition modeling and color jet 3D printing technologies for the printing of mathematical geometries. J. Ind. Integr. Manage., 1–13 (2020). https://doi.org/10.1142/s2424862220500104 24. Haleem, A., Javaid, M., Khan, S., & Khan, M.: Retrospective investigation of flexibility and their factors in additive manufacturing systems. Int. J. Ind. Sys. Eng. 36(3), 400. https://doi. org/10.1504/ijise.2020.110932
Factors Affecting Work-Related Musculoskeletal Disorders in Caregiving Staff at Hospitals and Medical Organization Deevesh Sharma, Awadhesh Bhardwaj, and Monica Sharma
Abstract The research has pointed out the risk of work-related musculoskeletal disorders to nurses and caretakers working at hospitals and other medical organizations. Due to increase in population, changes in lifestyle and environment the number of patients are increasing day by day. Majority of hospitals in India are equipped with trained staff but lack of facilities and comfort provided to them. The research was conducted in the various hospitals and medical organizations to collect information on factors affecting the caregiving staff in these organizations. The data was collected from organizations in Delhi and Jaipur based on the location and patient load. Factors including average patient-weight lifted, lifting postures, noise, lighting, and air quality were found to play important roles in working efficiency as well as the risk of work-related musculoskeletal disorders in caregivers. A questionnaire-based survey was done to identify the influence of different factors on the staff as well as the factors affecting the working efficiency were recorded at various organizations. Keywords WMSD · Hospitals · Caregiving staff
1 Introduction Hospitals and medical organizations are one of the most important and sensitive elements of society. Designers and architects significantly contribute toward betterment of facilities and comfort for the patients as they are the ones who need D. Sharma (B) · A. Bhardwaj Department of Mechanical Engineering, Malviya National Institute of Technology Jaipur, Jaipur, Rajasthan, India e-mail: [email protected] A. Bhardwaj e-mail: [email protected] M. Sharma Department of Management Studies, Malviya National Institute of Technology Jaipur, Jaipur, Rajasthan, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_18
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constant care and attention. This research has pointed out some of the most important factors which affect the health of caregiving staff at hospitals and other medical organizations. In a typical Indian hospital, the caretakers and nurses handle on an average of 50– 60 patients on daily basis. These patients weigh an average of 55–65 kg per nurse, which is a lot of weight for the staff to handle in one shift. The staff has also to be very careful with these patients as they are with various temporary or permanent disabilities. Working in a compromised environment is intolerable for the staff as the job requires intensive care.
2 Literature Review Work-related musculoskeletal disorders (WMSDs) are a very common health problem pertaining throughout the industrial world, and it is one of the major reasons of disabilities. WMSDs are related to the condition of nerves, muscles, tendons, and other supporting structure of musculoskeletal systems that result in pain, discomfort, fatigue, local swelling, tingling, and numbness. WMSDs usually results from cumulative damage resulting from months and years of exposure to excessive level of psychosocial and physical stress at work [1]. The risk of WMSDs in caregivers is very high if not taken care of. Factors like proper working posture, lighting, noise, and air quality contribute significantly toward the risk of temporary or permanent injury. These factors are to be frequently monitored and specified as per the job. Posture assessment tools like rapid entire body assessment (REBA) can be used to identify bad lifting postures of staff and remedial actions can be taken. Body balance and biomechanical analysis can also help toward good ergonomic interventions. In a busy hospital noise as a factor cannot be ignored, as the flow of patients and panic environment is quite obvious in such working environments. Nelson in the guide has pointed out the importance of handling the patients in the best way possible and also has discussed that physical and environmental factors influence the performance of the nursing staff [2]. Continuous high-intensity noise levels may lead toward aggressive behavior of staff and negligence toward health of the patients and people in need. Sudden increase in noise intensity can lead to hypertension, tachypnoea, tachycardia, and vasoconstriction in staff [3]. Many researchers have pointed out various negative effects of noise on caregiving staff in hospitals [4–7]. As per the study done by Beyea in 2007, the acceptable range of noise intensity in hospitals is expected to be maximum 45 dB in daytime and 35 dB in the night [4]. Higher quality and proper lighting facility have high potential toward increasing efficiency of hospital staff [8]. In a healing environment lighting is the most significant factor, not only patients but nurses are able to perform their respective activities with easy and comfort. Proper lighting helps psychologically to the nurses and improves their performances and safeguards them from any health risks; this in turn helps in the favor of patients too [9].
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Air quality recommended by ASHRAE [10] states that in winters and summers the relative humidity of 30% and 50%, respectively, should be maintained in almost all general departments and areas of a hospital. The temperature range is also recommended to be within 22–26 °C [10]. Also to avoid bacteria contamination in air of hospitals, the temperature and humidity should be maintained by also keeping in mind the comfort range for customers as well as the working staff. Due to panic and anxious environment for staff, the temperatures should be well-maintained and also the risk of staff getting infected through air should be avoided by controlling the humidity.
3 Methodology The research was done based upon the literature survey done earlier and the factors which play significant role in a nursing staff’s working environment were identified. The data regarding comfortable ranges of these factors based on the available literature in books, journal articles, and conference articles was collected. Based on location and accessibility, three hospitals each from Jaipur and Delhi were identified to collect data for posture, comfort level, lighting, air quality, and noise. A basic Nordic questionnaire was distributed among the total 136 caregiving staff in 6 hospitals, out of which 88 responses were collected. Data regarding noise, illumination, and air quality was recorded at emergency ward, outpatient department, and intensive care unit in each of the 6 hospitals with the condition of confidentiality. The details of the data and their interpretation have been discussed later in the paper. Areas of concern and their significance are also discussed along with the urgent need for ergonomics interventions.
4 Results Data collected through questionnaire reflected that around 45% of the caregiving staff was struggling with lower back, upper arms, shoulder, and knee pains. The REBA scores were observed to vary in the range from 5 to 11, which is under high-risk zone of WMSDs. Figure 1 shows one of the photographs from posture assessment. Personal interviews of the staff also uncovered that after occasional busy days the rate of absenteeism also increases, and many of the staff members do not even come back to work. Along with the posture analysis, noise was also observed and its intensity was recorded using a dosimeter at three locations in each of the six hospitals, the data recorded is represented in Table 1. The data clearly shows that the noise levels in emergency areas are very high as compared to the prescribed range of 35–45 dB. Also, the REBA score was calculated on the basis of photographic analysis for respective cases at various locations. Due
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Fig. 1 Single person front lift of a patient
Table 1 Noise levels and corresponding REBA scores at various locations in each hospital Hospital
Noise levels in decibels (dB) and corresponding REBA score Emergency ward
REBA
OPD
H1
64
10
52
9
31
7
H2
69
11
58
10
39
8
H3
71
11
63
10
29
6
H4
58
9
44
8
24
6
H5
42
8
45
9
37
8
H6
73
10
47
9
35
8
REBA
ICU
REBA
to noise the staff also complained about sudden stress and aggressive nature while working, which should be never acceptable at a medical care unit. The light intensity of illumination was recorded at various areas of each of the six hospitals using a lux meter. The data of light intensity with its corresponding REBA score calculated on the basis of photographic analysis for the respective case is represented in Table 2. The illumination required in a medical organization is an average of 500–600 lx, but as the data reflects that the illumination in emergency wards is very low. The recorded data from the hospitals at emergency ward, OPD, and ICU was recorded, and rounded off average values are represented in Table 3. The data clearly reflects that in many of the cases the range of humidity and temperature do not fall as prescribed by the literature. The corresponding REBA score was also calculated on the basis of photographs taken for the respective cases.
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Table 2 Light intensity and corresponding REBA scores at various locations in each hospital Hospital
Illumination (lx) and corresponding REBA Scores Emergency ward
REBA
OPD
REBA
ICU
REBA
H1
242
10
756
7
683
6
H2
411
9
894
5
856
5
H3
256
10
798
6
784
6
H4
182
9
552
6
681
7
H5
369
8
641
6
758
6
H6
294
10
579
7
697
6
Table 3 Air quality and corresponding REBA scores at various locations in each hospital Hospital
Humidity (%), Temperature (°C), and corresponding REBA scores Emergency ward
OPD
ICU
(%)
(°C)
REBA
(%)
(°C)
REBA
(°C)
REBA
H1
72
36
10
66
32
7
(%) 62
26
6
H2
69
34
9
57
28
7
55
24
6
H3
54
30
9
56
28
6
52
22
5
H4
68
35
8
63
30
7
59
26
6
H5
63
34
7
59
31
6
55
29
7
H6
59
32
10
55
29
6
52
27
6
5 Discussions A qualitative analysis showed that the staff was highly uncomfortable in the emergency wards due to high noise, and it hindered them in communicating with other officials too. Noise levels were lower in the OPD area, and it was in prescribed range in the ICU area of hospitals. Vinodhkumaradithyaa in 2008 did a survey of various noise levels in hospitals and found out that the noise intensity was above the recommended range, but no relationship was developed [11]. The main problem due to high noise in the hospitals is that it makes it difficult to communicate within the staff as well as with the doctors and in turn the work is many a times delayed which should not be in the case of an emergency ward. A well-designed hospital with better facilities can improve the efficiency of staff and also reduce the risks associated while working [12]. Lighting plays a very important role in designing any medical care environment. In any hospital, the emergency ward is the busiest, and it needs high attention, as the patients may lose life due to delay or error in treatment. The staff was found to have frequent headaches and found it difficult to treat trauma patients in low lights. OPD and ICU were found to be fairly illuminated as per the job and care requirements.
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Due to high temperatures and relative humidity, the staff faced many issues regarding productivity. A qualitative analysis was done in order to correlate with the quantitative data which concluded that the caregiving staff experienced discomfort in terms of high humidity and sweating due to which it was harder to concentrate on work. Previous studies done in the field of WMSDs and environmental factors have not derived any direct relationship between the factors and the risks associated with posture. This experimental study has found out significant results to show the effect of environmental factors on postures adopted by the nurses while working and the risk of WMSDs. The REBA scores for corresponding case of humidity, temperature, noise, or illumination shows no specific pattern but makes it very clear that there is a direct effect of these factors on the body postures of caregiving staff.
6 Conclusion Medical caregiving organizations are very significant in society, and they are expected to be perfectly designed and follow prescribed environmental factors. Factors like illumination, posture, noise, and air quality were recorded and found not to be in the prescribed range as documented by relevant supporting literature. The risk of WMSDs is found to be high in the caregiving staff in the hospitals, and we have surveyed based on posture and other factors discussed. Noise, illumination, and air quality indirectly induce awkward postures in nurses and caregiving staff, and the REBA scores calculated have proved the effect of these factors on the risk of WMSDs. The illumination and air quality need to be in prescribed range; otherwise, there are errors and delays in treatment of the patients. This is intolerable in any medical organization. It was found that the emergency ward and areas were the least taken care of in terms of the factors discussed above. These emergency or trauma wards need utmost attention, as they handle those medical cases where the risk of life is high and the time is very less. There is no room for error in an emergency ward, and the priority to this department of the organization should be as much as of an operation theater. Improving the environment and designing it well as per the standards is beneficial to caregiving staff and reduces the risk of WMSDs. Also following such standards help in improving the productivity of nurses and in turn benefits the patients as well in numerous ways.
References 1. Podniece, Z.: Work-related musculoskeletal disorders: back to work report. Europ. Agency Safety Health Work, Belgium (2007)
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2. Nelson, A.L.: Safe Patient Handling And Movement: A Practical Guide For Health Care Professionals. Springer Publishing Company, New York (2005) 3. Cmiel, C.A., Karr, D.M., Gasser, D.M., Oliphant, L.M., Neveau, A.J., Cmiel, C.A.: Noise control: a nursing team’s approach to sleep promotion. AJN 104(2), 40–48 (2004) 4. Beyea, S.: Noise a distraction, interruption, and safety hazard. AORN J. 86(2), 281–285 (2007) 5. Mazer, S.E.: Hear, hear. Assessing and resolving hospital noise issues. HFM 18(4):24–29 (2005) 6. Mazer, S.: Stop the noise: reduce errors by creating a quieter hospital environment. PSQH: 1–4 (2005) 7. Penney, P.J., Earl, C.E., Penney, P.J., Earl, C.E.: Occupational noise and effects on blood pressure: exploring the relationship of hypertension and noise exposure in workers. AAOHN J. 52(11), 476–480 (2004) 8. Edwards, L., Torcellini, P.: A Literature Review of the Effects of Natural Light on Building Occupants. National Renewable Energy Laboratory, Handbook, Golden, Colorado (US) (2002) 9. Kamali, N.J., Abbas, M.Y.: Healing environment: enhancing nurses’ performance through proper lighting design. Procedia-SBS 35, 205–212 (2012) 10. ASHRAE (2003) Chapter seven: healthcare facilities. In: HVAC Applications handbook. ASHRAE: Ch.7 11. Vinodhkumaradithyaa, A., Srinivasan, M., Ananthalakshmi, I., Kumar, D., Jeba Rajasekhar, R., Daniel, T.: Noise levels in a tertiary care hospital. N & H 10(38), 11–13 (2008) 12. Rechel, B., Buchan, J., Mckee, M.: The impact of health facilities on healthcare workers’ well-being and performance. IJNS 46(7), 1025–1034 (2009)
Redesigning Agricultural Tools Using Anthropometry of Male Agricultural Workers of Dayalbagh Region, Agra, India P. Singh, S. Srivastava, and N. S. Thakur
Abstract A considerable number of agricultural operations/tasks are still performed manually. Use of farm hand tools and agricultural implements helps in accomplishing these tasks with increase in the performance, comfort, satisfaction, and functionality of workers. A large proportion of the workforce in the world is involved in agriculture or related occupations. Hand tools have been in use for a very long time and have been developed in an almost evolutionary manner. Design of a hand tool depends on many factors like mode of operation, anthropometric data of user population of specific region, material, and shape of handle. Research has shown that there are anthropometric differences between different populations for almost every part of the human body. Anthropometric measurements have been used in various studies to design hand implements and manually operated equipment like screw driver, hand saw, sickle, pliers, scrapers, shovel handle, khurpi, weaving tools, weeder etc. The proposed research analyzes the design and design modifications of agricultural hand tools, implements and machines being used in agricultural fields in Dayalbagh region, Agra, India. Ergonomic consciousness is increasing in the design of the agricultural hand tools and equipment. Anthropometry plays an important role in the design of various manually operated hand tools and equipment. Selected body dimensions were measured from a sample of 55 male subjects. Anthropometric data is then used to redesign the existing hand tools and equipment, namely khurpi, sickle, spade, weeder, and thresher, used in Dayalbagh region. Keywords Farm tools · Anthropometry · Agricultural workers
P. Singh · S. Srivastava (B) · N. S. Thakur Department of Mechanical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, (Deemed University) Dayalbagh, Agra, India e-mail: [email protected] P. Singh e-mail: [email protected] N. S. Thakur e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_19
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1 Introduction Ergonomists and occupational health and safety practitioners, in general, aim to minimize the discomfort and risk of injury while improving work-efficiency and workenvironment in an occupational setup [1–8]. In an agricultural setup, ergonomically designed hand tools and equipment play an important role to increase the workefficiency and work-safety. In India, most of the farmers continue to use indigenous tools and agricultural implements as these are cheaper, economical, and easily available in the local market. It is needed to redesign these tools by blending traditional and modern scientific knowledge in completing the work in lesser time while reducing work-injury and fatigue. To achieve higher performance, more human comfort, and minimal musculoskeletal injury, it is necessary to design hand tools and agricultural equipment ergonomically keeping in consideration the worker’s capabilities and work-demands [9]. Anthropometric body dimensions play an important role in the design of manually operated farm tools and equipment. Agricultural workers and farmers in India perform most of the agricultural operations manually. Hence, for the design of hand tools, farm equipment, and machinery involving human efforts, region-specific anthropometric data is needed. There is great scope of improving agricultural hand tools and equipment based on scientific application of anthropometric data of agricultural workers of different regions. Anthropometric body dimensions based design of hand tools and equipment greatly enhances safety, health, comfort, and productivity of agricultural workers [10–12]. Agrawal et al. [13] illustrated the application of anthropometric data in the design of farm equipments through some examples. Kumar et al. [14] reported a study to develop a cost-effective thresher based on ergonomic principles. The present work focuses on studying various types of hand tools and motor/tractor driven tools used in Dayalbagh region, Agra. It is aimed to collect anthropometric data of agricultural workers of this region and evaluate the relevant body dimensions to redesign agricultural tools and equipment used by workers.
2 Methods 2.1 Subjects The anthropometric data were collected from 55 male subjects of 18–25 years age group.
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2.2 Body Dimensions Selected body dimensions were measured including age and body weight of agricultural workers. Figure 1 shows the measurement of body dimensions of male subjects.
2.3 Equipment Used Anthropometric data of this region was measured by height gauge, vernier caliper, portable weighing scale, and measuring tape.
3 Results The values of minimum, maximum, mean, SD, CV, and 5th and 95th percentile of anthropometric data of 55 male subjects are presented in Table 1.
4 Discussion 4.1 Redesigning Grip Diameter for Hand Tools like Sickle, Spade, and Khurpi Sickle, spade, and khurpi are the most common tools used in Dayalbagh region, Agra. Mean handle diameter of sickle is measured as 3.4 cm, the mean circumference of the khurpi handle is 10.2 cm (in terms of diameter, it is 3.25 cm), and the mean diameter of the spade handle at the hand’s grip end is 3.6 cm. Anthropometrically, the diameter of the handle should lie between the middle finger palm grip diameter and internal grip diameter such that while a worker grips the handle, his longer finger should not touch the palm and should not exceed the internal grip diameter. The 95th percentile and 5th percentile value of the middle finger palm grip diameter and internal grip diameter for this region are 2.76 and 3.83 cm (Table 1). So the handle diameter will range between 2.76 and 3.83 cm. Therefore, a handle diameter of 3.3 cm is recommended for this region. Dewangan et al. [9] recommended a handle diameter of 3.7 cm for northeastern India (Fig. 2).
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(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
Fig. 1 Measurement of body dimensions: a weight; b stature; c shoulder height; d elbow height; e waist length; f arm length; g middle finger palm grip diameter; h internal grip diameter
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Table 1 Summary of anthropometric data Dimensions
Min
Max
Mean
SD
SEM CV (%) Percentile 5th
Weight, kg
43.50
81.00
45.60
95th
58.09 9.42 1.27
16.21
Stature
156.20 179.00 168.35 5.08 0.69
3.02
160.46 176.88
78.40
Shoulder height
130.40 150.20 141.71 4.71 0.64
3.32
133.96 149.70
Elbow height
96.00 118.60 105.43 3.64 0.49
3.46
100.00 110.18
Waist length
72.39
99.06
82.73 7.06 0.95
8.54
73.41
97.03
Arm length
61.40
77.50
58.89 3.55 0.48
5.16
61.60
74.10
Forearm
41.30
52.00
46.50 2.42 0.33
5.21
41.48
50.00
Middle finger palm grip diameter
1.54
3.09
2.38 0.29 0.04
12.08
1.80
2.76
Internal grip diameter
3.02
5.62
4.73 0.45 0.06
9.48
3.85
5.37
Measurements are in cm, until otherwise specified Min = minimum, Max = maximum, SD = standard deviation, SEM = standard error of mean, CV coefficient of variation
Fig. 2 Handle of sickle, spade, and khurpi
4.2 Redesigning Weeder Handle Height by Considering Anthropometric Data of This Region The existing handle height of the weeder used in Dayalbagh region is 119.4 cm (Fig. 3). Gite and Yadav [15] recommended the optimum handle height for a push– pull type weeder lie within 0.7 and 0.8 of shoulder height, and a handle height of 100 cm is recommended for Indian workers. The 5th and 95th percentile values of shoulder height are 133.96 and 149.70 cm, respectively, for Dayalbagh region (Table 1). Thus, the recommended handle height of weeder for this region is 106 cm.
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Fig. 3 Weeder
4.3 Redesigning Thresher With Ergonomic Considerations On the basis of anthropometric data of Dayalbagh region, it was observed that the 95th percentile male forearm dimension was 50 cm. To prevent the contact of forearm with threshing drum, it has been proposed to increase the chute cover length to 61 cm, i.e., equivalent to 5th percentile dimension of arm length (Table 1). Chute length may include the chute cover length and 95th percentile of forearm for proper feeding of crops. Therefore, it is recommended that the chute length should be 111 cm. It is important to ensure that the worker should not bend over the chute during feeding. So the chute must be at elbow level from standing platform of the thresher to prevent bending postures of worker during working. The 5th and 95th percentile values of elbow height of male subjects of this region have been found to be 100 and 110.18 cm, respectively (Table 1). Thus, the height of the standing platform should be adjustable between this range. For a fixed-type platform, a height of 105 cm has been recommended for this region (Figs. 4 and 5). Fig. 4 Thresher
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Fig. 5 Different design parameters of thresher
5 Conclusion In this study, it was clear that the anthropometric dimensions are different for different regions. While manufacturing agricultural tools and equipment, it is necessary to keep in mind to consider specific anthropometric data of regions. Recommended design changes in handle diameter of hand tools (sickle, spade, and khurpi), weeder handle height, and chute cover length, chute length, and standing platform height of thresher of Dayalbagh region would surely improve upon productivity of work and safety and comfort of agricultural workers. However, the present work has certain limitations, which are smaller sample size and lesser age range of subjects. Future studies should incorporate using more precise instruments to measure body dimensions, involving subjects of higher age range, say 18 to 50 years, and recommending design changes in the tools/equipment based on different age groups and body mass index (BMI) groups of subjects. Acknowledgements The authors are thankful to the Dayalbagh Educational Institute, Deemed University, Dayalbagh, Agra, for providing the facilities in Industrial Kinesiology laboratory. This work is supported by UGC, New Delhi, under Grant F. No. 3-38/2012 (SAP-II) dated 02/10/2012; and by DST, New Delhi, under Grant No. 100/IFD/2563/2012-2017 dated 20/07/2012.
References 1. Anand, Y.K., Srivastava, S., Srivastava, K.: Risk of occupational health hazard: Assessment using CDSwFR and minimization using EMOwJCS. Work 51(3), 621–632 (2015) 2. Srivastava, S., Anand, Y.K.: An intelligent system to address occupational health of workers exposed to high risk jobs. In: Proceedings of IEEE Congress on Evolutionary Computation, pp. 1977–1983. IEEE, Brisbane (2012) 3. Anand, Y.K., Srivastava. S., Srivastava, K.: Hybrid meta-heuristic based occupational health management system for Indian workers exposed to risk of heat stress. In: Trzcielinski, S., Karwowski, W. (eds.) Advances in Ergonomics in Manufacturing, pp. 110–120. CRC Press, Taylor & Francis, Boca Raton, FL (2012) 4. Anand, Y.K., Srivastava, S., Srivastava, K.: An integrated ANN-EMO approach to reduce the risk of occupational health hazards. J. Artif. Intell. Soft Comput. Res. 2(2), 77–95 (2012)
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5. Srivastava, S., Anand, Y.K., Soamidas, V.: Reducing the risk of heat stress using artificial neural networks-based job combination approach. In: Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management, pp. 542–546. IEEM, Macau (2010) 6. Anand, Y.K., Srivastava, S., Srivastava, K.: Optimizing the risk of occupational health hazard in a multi objective decision environment using NSGA-II. In: Deb, K., et al. (eds.) Lecture Notes in Computer Science, pp. 476–484. Springer-Verlag, Berlin Heidelberg (2010) 7. Bansal, R., Gupta, A., Garg, S., Srivastava, S.: Determination of safe asymmetric lifting of hand-pump body. In: Proceedings of International Conference on Humanizing Work & Work Environment, pp. 368–373. Springer, IIT Bombay (2018) 8. Bansal, R., Srivastava, D., Srivastava, S.: Designing safe lifting of centrifugal-pump casing in a medium scale factory in Agra. In: Proceedings of International Conference on Humanizing Work & Work Environment, pp. 380–385. Springer, IIT Bombay (2018) 9. Dewangan, K.N., Owary, C., Datta, R.K.: Anthropometry of male agricultural workers of northeastern India and its use in design of agricultural tools and equipment. Int. J. Ind. Ergon. 40, 560–573 (2010) 10. Dewangan, K.N., Owary, C., Datta, R.K.: Anthropometric data of female farm workers from north eastern India and design of hand tools of the hilly region. Int. J. Ind. Ergon. 38, 90–100 (2008) 11. More, S.H., Vyavahare, R.T.: Anthropometric and grip strength data of agricultural workers for marathwada region of Maharashtra (India). Int. J. Appl. Eng. Technol. 4(2), 148–153 (2014) 12. Vyavahare, R.T., Kallurkar, S.P.: Anthropometry of male agricultural workers of western India for the design of tools and equipment. Int. J. Ind. Ergon. 53, 80–85 (2016) 13. Agrawal, K.N., Singh, R. K. P., Satapathy, K.K.: Anthropometric considerations for farm tools/machinery design for tribal workers of North Eastern India. Agric. Eng. Int. CIGR E J. (2010) 14. Kumar, A., Mohan, D., Patel, R., Varghese, M.: Development of grain threshers based on ergonomic design criteria. Appl. Ergon. 33, 503–508 (2002) 15. Gite, L.P., Yadav, B.G.: Optimum handle height for a push-pull type manually-operated dryland weeder. Ergonomics 33, 1487–1494 (1990)
Effect of Environmental Parameters on Performance and Fatigue of a Worker Performing a Metal Pouring Operation Saman Ahmad, A. Varshney, S. Singhal, V. Agrawal, and A. Saleem
Abstract Casting industry is generally considered risky, with workers being exposed to hazards like heat, fumes, and manual handling of hot material. Further, in small-scale units, most of the work is carried out manually where workers are exposed to unfavorable environmental conditions like high temperature and noise levels and poor illumination, which adds to the hazardous nature of work involved. The present study investigated the effect of environmental factors on workers performing a manual metal pouring operation. Subjects performed a simulated metal pouring operation at different levels of noise (80, 90, and 100 dB (A)), illumination (300, 400, and 500 lx), and temperature (34, 37, and 40 °C). The number of molds filled, heart rate, and oxygen saturation were taken as the dependent parameters. ANOVA carried out on the data revealed that temperature, noise and illumination had a statistically significant effect on task performance. It was further found that temperature also had a statistically significant effect on heart rate of the subjects performing the task. Keywords Casting · Environmental factors · Heart rate
1 Introduction Casting, one of the most important parts of any fabrication industry, is often carried out at a small scale with just a few workers. Work in foundries is heavy and almost continuous. Foundry workers are known to have higher MSD rates than workers in other industries. Traumatic injuries while handling casting, hot core, and molten metal are common. Other hazards may include exposure to heat, noise, and fumes evolved while melting, to name just a few [1]. Manual pouring of the molten metal is perhaps one of the most hazardous tasks in casting industry [2]. It involves lifting of heavy loads, improper postures, and
S. Ahmad (B) · A. Varshney · S. Singhal · V. Agrawal · A. Saleem ZHCET Aligarh Muslim University, Aligarh, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_20
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exposure to the hot metal. Although automation has been recommended and implemented in large-scale foundries, its high cost makes it unsuitable for the smaller units. The problem gets compounded further when work is carried out under unfavorable environmental conditions, as is the case of most of the small-scale units. Workplace environmental conditions such as extreme heat/cold, chemical smell, noise, poor lighting, and dust have direct as well as indirect effects on employee job performance [3]. Companies with higher environmental problems have more performance-related problems such as low productivity and high absenteeism [4]. The conditions act as stressors and decrease employee concentration toward tasks which tends to result in low productivity, poor work quality, and physical and emotional stress [3]. Effective applications of ergonomics in working conditions can enhance job performance and provide worker safety, physical well-being, and job satisfaction. Negative effects of high temperature on worker performance and safety are wellestablished. Humans attempt to maintain their core body temperature around 37 °C. Changes in this core body temperature affect the health, comfort, and working efficiency of a person. For a worker expected to carry out heavy work for 75% of shift duration, the equivalent permissible heat stress is 26 °C [1]. However, levels of WBGT between 30 and 50 °C have been measured in several foundry surveys. At WBGT levels over 30 °C, the risk of incurring heat illness progressively increases, with the level of risk being higher for the heavier physical work [1]. According to OSHA guidelines, the acceptable noise level in the workplace is 90 dB (A) for an 8 h period. For every 5 dB (A) increase in noise levels, the exposure duration should be halved. Excessive noise affects the human health both directly and indirectly. Heart disease, temporary or permanent hearing loss, sleep disturbance, adverse effect on comprehension, attention, and vigilance are some of the direct impacts of noise. Other effects include physiological responses like a change in heart rate and blood pressure. Further, it has been established that noise may increase the risk of accidents [5] and decrease task performance [6] by interfering with the ability to hear auditory cues. The effects of noise on non-auditory task performance have, however, been inconclusive with different studies indicating that noise reduced task performance, has no effect on it or increases it. It is generally believed that tasks performance improves with an increase in illumination up to a certain level. The exact level of illumination, however, depends on the nature of the task. More visually demanding the task; higher the illumination requirement. Thus, the provision of lighting for optimum user performance is complex and task-specific. There are many parameters that influence visual performance, and many of these are task-dependent. Some parameters of general importance include the contrast between an object to be viewed and its background, and the size of the object, the luminance of the object and the time for which it is viewed [7]. Heart rate has a linear relationship with oxygen consumption and hence the energy consumed. Also, it is very easy to monitor. Therefore, it has been widely used as a measure of workload. A physiological workload at average heart rate greater than 150 beats/min is considered extremely heavy and may not be acceptable in the workplace [8].
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2 Methodology During a survey of small-scale foundries of Aligarh, it was observed that workers were subjected to very high levels of noise and temperatures. Temperatures in the range of 40–45 °C were observed. Noise levels ranged from 87 dB (A) to 102 dB (A). Further, the illumination of the rooms generally depended on ambient light or in a few cases fluorescent bulbs. When metal was poured into the molds, a lot of gases originated from the mold which further reduced visibility. Keeping in mind the highly dangerous nature of work, i.e., handling of hot molten metal, the effect of exposure to unfavorable environmental conditions needs to be assessed both from the point of view of safety and productivity. Thus, the present study aims at evaluating the effect of noise, illumination, and temperature on the performance of a worker performing a metal pouring task.
2.1 Subjects Six subjects participated in the study. All subjects were male students of Z.H.C.E.T with no prior experience of load lifting. They had no history of back pain. They were given proper training for the task prior to the experimental runs (Table 1).
2.2 Experimental Design A three-factor (3 × 3 × 3) full factorial design was used to determine the effects of parameters under investigation. Experiments were carried out at noise levels of 80, 90, and 100 dB(A), illumination levels of 300, 400, and 500 lx and temperatures of 34, 37, and 40 °C
2.3 Experimental Task The task involved a simulated metal pouring operation. Subjects were required to carry a sand-filled crucible with the help of a tong from station 1 and fill 12 molds Table 1 Descriptive statistics for 6 male participants
Subject Age (Years)
Mean 21.66
Standard Deviation 0.52
Height (cm)
172.8
9.1
Weight (kg)
75.7
12.2
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Fig. 1 Experimental setup
kept at station 2 before returning back to station 1. Molds were placed on a platform 70 cm high. The carrying distance between the two stations was 3 m (Fig. 1). Sand was chosen over molten metal for the experiment because the density of sand (2.32 g/cm3 ) is very close to the density of molten aluminum, and it can safely be used by non-industrial workers. Similar material substitution had been used by Fredericks et al. [2]. Recorded noise of a typically used blower was played through speakers to simulate the actual working conditions as closely as possible. Combinations of 5 fluorescent tube lights, 4 halogen bulbs (500 W each), and 4 CFLs (20 W each) provided the required illumination. To achieve the required temperatures, up to 4 room heaters were used. Task performance was measured in terms of the time taken to fill the molds. Worker fatigue was measured in terms of change in heart rate and oxygen saturation, before and after the task.
3 Results and Discussions Using the methodology described above, observations were gathered and ANOVA analysis was carried out using the SPSS software. The results showed that all three factors, namely noise, temperature, and illumination had a significant effect on time taken to complete the task. All two-way and three-way interactions between temperature, noise, and illumination were statistically non-significant. Temperature had a statistically significant effect on task performance, heart rate, and oxygen saturation. However, the peak heart rate remained within the acceptable range. It was observed that with an increase in temperature, the time taken to fill molds increased as did the change in heart rate and oxygen saturation. The results are in line
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with Haboubi [9], who found an increase in heart rate and oxygen saturation with an increase in temperature when experiments were carried out in an environmental chamber. It is, however, worth noting that the present study was carried out using unacclimatized subjects. Since acclimatization plays a major role in an individual’s response to heat endurance capacity, further investigations, preferably using acclimatized foundry workers, may be carried out to get a clearer picture of the actual effect on task performance (Figs. 2 and 3). Further, it was found that though illumination has an effect on task durations, it had no statistically significant effect changes in heart rate and oxygen saturation. Surprisingly, it was noted that as the illumination level increased, the task duration also increased. Though researchers are generally of the opinion that task performance increases with increase in illumination, most studies have focused on visual tasks. There is hardly any literature available on the effect of illumination on a lifting task performance. Since optimal illumination is task-specific, further research is needed to get a better understanding of the role of illumination in a metal pouring task (Fig. 4).
Fig. 2 Effect of temperature on the change in (a) oxygen saturation and (b) heart rate while performing a manual metal pouring operation
Fig. 3 Effect of (a) temperature and (b) noise level on task duration while performing a manual metal pouring operation
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Fig. 4 Effect of (a) noise level on the change in oxygen saturation and (b) illumination on task completion time while performing a manual metal pouring operation
4 Conclusions The present study highlights the effect on workers performance due to exposure to high temperatures, noise, and illumination. Subjects performing the task at high temperatures showed higher levels of physiological stress. Noise was found to act as a stressor and resulted in a change in the oxygen saturation. In light of the observations, a proper solution is required to safeguard the well-being of the workers as well as improving the productivity. Isolation of workers from the noise source and decreasing the exposure durations may be considered to address the issues of noise and heat stress.
References 1. Lei, L., Dempsey, P.G., Xu, J.G., et al.: Risk factors for the prevalence of musculoskeletal disorders among chinese foundry workers. Int. J. Ind. Ergon. 35, 197–204 (2005). https://doi. org/10.1016/j.ergon.2004.08.007 2. Fredericks, T.K., Kumar, A.R., Karim, S.: An ergonomic evaluation of a manual metal pouring operation. Int. J. Ind. Ergon. 38, 182–192 (2008). https://doi.org/10.1016/j.ergon.2007.02.003 3. Kahya, E.: The effects of job characteristics and working conditions on job performance. Int. J. Ind. Ergon. 37, 515–523 (2007). https://doi.org/10.1016/j.ergon.2007.02.006 4. Yeow, P.H.P., Nath Sen, R.: Productivity and quality improvements, revenue increment, and rejection cost reduction in the manual component insertion lines through the application of ergonomics. Int. J. Ind. Ergon. 36, 367–377 (2006). https://doi.org/10.1016/j.ergon.2005.12.008 5. Shikdar, A.A., Sawaqed, N.M.: Worker productivity, and occupational health and safety issues in selected industries. Comput. Ind. Eng. 45, 563–572 (2003). https://doi.org/10.1016/S03608352(03)00074-3 6. Parsons, K.C.: Environmental ergonomics: A review of principles, methods and models. Appl Ergon 31, 581–594 (2000). https://doi.org/10.1016/S0003-6870(00)00044-2 7. Zakaria, A.M., Noweir, K.H., El-Maghrabi, G.: Evaluation of occupational hazards in foundries. J. Egypt. Public Health Assoc. 80, 433–462 (2005) 8. Wu, H.-C., Wang, M.J.J.: Determining the maximum acceptable work duration for high-intensity work. Eur. J. Appl. Physiol. 85, 339–344 (2001). https://doi.org/10.1007/s004210100453
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9. Al-Haboubi, M.H.: Energy expenditure during moderate work at various climates. Int. J. Ind. Ergon. 17, 379–388 (1996). https://doi.org/10.1016/0169-8141(95)00002-X
Design of Land Leveller Height Measuring Physiological and Psychophysical Parameters P. Singh, S. Srivastava, and N. S. Thakur
Abstract Nowadays, the leveling operation is carried out by tractor-driven equipment. However, in developing countries like India, there are many farmers who level their lands by traditionally designed leveller (local name paata). Also in hilly regions or where the space is limited, leveling by tractor is quite uncommon, and land leveller is a better alternative. Therefore, in this study, an attempt has been made to present an ergonomic design of the land leveller while considering physiological and psychophysical parameters viz heart rate, overall discomfort score, and body part discomfort score (BPDS). Ergonomic design of land leveller aims to minimize these discomfort scores while ensuring the safe range of heart rate of workers. This land leveller help in improving the working capacity and efficiency of the workers and therefore they can work for longer duration with lesser fatigue. A field setup is selected near the Industrial Kinesiology laboratory of University Department, to carry out experimental work to find out the optimum handle height of leveller. Heart rate data is collected at four different handle heights using BioHarness Telemetry System. Psychophysical data are recorded using Corlett and Bishop technique (1976). On the basis of the results of experiments and the anthropometric data of local workers, a handle height of 92 cm is recommended for land leveller. Keywords Land leveller · Physiological effect · Psychophysical effect
P. Singh · S. Srivastava (B) · N. S. Thakur Department of Mechanical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, (Deemed University) Dayalbagh, Agra, India e-mail: [email protected] P. Singh e-mail: [email protected] N. S. Thakur e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_21
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1 Introduction Occupational ergonomics addresses health and safety issues of occupational workers while improving productivity of work-system. Many researchers have offered multidimensional solution to reduce risk of occupational health hazards [1–7]. In Indian agricultural context, most of the agricultural activities are still performed manually by using traditional design hand tools and equipment. A number of research studies have been carried out in India to design/redesign these tools and equipment ergonomically [8–13]. Gite [14] conducted experiments and studied postural discomfort and physiological reactions of the workers during operation with six handle heights to find the optimum handle height for animal-drawn mold board plow. They recommended a handle height of 77 cm for a fixed handle. Gite and Yadav [15] recommended a handle height of 100 cm for a push–pull type manually operated dryland weeder. But no specific study was carried out for finding the optimum handle height of land leveller. Land leveller is an equipment that is used for farming and agriculture with a purpose to level the land. Leveller is one of the common hand tools used in Dayalbagh region where the present study was performed. It is of traditional design made of wood with an iron base in the bottom. Two workers hold and pull the pulling handle of leveller, while another one presses it downward by holding leveller handle. The height and length of the leveller commonly available in Dayalbagh region, Agra, are 88 cm and 85.1 cm, respectively (Fig. 1). At times, leveller-worker has to bend over it considerably which may not be a correct posture. Thus, an attempt was made to find out the optimum handle height for a manually operated leveller (paata) with ergonomic considerations.
Fig. 1 Height and length of leveller with pulling handle
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2 Methods 2.1 Subjects The experiments were performed with eight male subjects. All of them were competent to operate leveller. Their mean age, stature, shoulder height, and weight were 24.1 (s.d. ± 0.53) years, 166.73 (s.d. ± 5.77) cm, 139.91 (s.d. ± 4.70) cm, and 62.46 (s.d. ± 12.03) kg, respectively. During the experiments, the mean climatic conditions were ensured.
2.2 Experimental Design The experiments were conducted to determine the heart rate during levelling operations with different handle heights and to know the postural discomfort after completion of each trial. Four handle heights, which were 0.85, 0.75, 0.65, and 0.55 times mean shoulder height (SH), were considered in a field setup (Fig. 2). The observations made during the experiments were heart rate, overall discomfort rating, and body part discomfort score (BPDS).
2.3 Heart Rate Measurement The heart rate was recorded continuously during levelling operation with different heights using a ‘BioHarness Telemetry System’ and ‘AcqKnowledge 4.1 BioHarness software’ (Fig. 3).
2.4 Postural Discomfort Measurement Corlett and Bishop technique was used to measure overall body discomfort and localized body discomfort. Twenty-three body regions (Fig. 4) were evaluated using this technique. The score was measured on an 8-point psychophysical rating scale (0 = no discomfort, 7 = extreme discomfort).
2.5 Procedure Each subject operated the leveller for all the four handle heights. The handle height sequence for each worker was different and was determined randomly. Necessary
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Fig. 2 Operating the leveller at four different heights: (a) 0.55 SH; (b) 0.65 SH; (c) 0.75 SH; (d) 0.85 SH
adjustments were also made in the experimental leveller to get the particular handle height. The subject had a rest of 30 min before start of the work. Heart rate in resting position was also recorded for 5 min by fixing a BioHarness device on the chest. After this the subject was ready to operate leveller for 10 min in the field, and his heart rate was continuously recorded. Immediately after fininshing the work, the subject was interviewed for overall discomfort rating and body part discomfort scores, which took about five minutes. Then, the subject was allowed to rest for ten minutes, and next trial was started. All the trials were conducted between 10:00 and 15:00 h each day.
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Fig. 3 Heart rate recorded with Acqknowledge 4.1 BioHarness software Fig. 4 Body parts regions for assessing postural discomfort
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Table 1 Heart rate data of subjects while working with four different handle heights Subject Sub1 Sub2 Sub3
Rest
0.85 SH
0.75 SH
0.65 SH
0.55 SH
90.17
109.22
110.46
117
116.73
87.58
120.5
123.77
122.98
128.4
131.92
141.06
130.93
140.28
112.6
Sub4
97.14
101.84
103.55
106.7
110.14
Sub5
103.06
157.97
169.17
167.37
172.92
Sub6
77.08
114.43
101.97
109.49
126.05
Sub7
87.86
104.11
122.84
117.06
126.22
Sub8
85.85
114.44
110.5
125.86
126.78
All units are in BPM
2.6 Observations The observed values of the physiological parameter, i.e., heart rate of the eight subjects while working with four different heights, were tabulated and presented in Table 1.
3 Results Table 2 shows the mean and standard deviation of heart rate while working with four different handle heights. The mean values of postural discomfort after levelling operation while working at four different handle heights are given in Table 3. Overall discomfort ratings as well as BPDS with respect to different handle heights are given in Table 4. Table 2 Means and standard deviation of heart rate
Height
Working handle height
Heart rate (BPM) (± SD)
H1
0.85 SH
119.30 (± 17.10)
H2
0.75 SH
122.92 (± 21.19)
H3
0.65 SH
124.67 (± 17.81)
H4
0.55 SH
130.94 (± 17.87)
SH = shoulder height, BPM = beats/min, SD = standard deviation
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Table 3 Mean values of postural discomfort S. No.
Body parts
Body part discomfort score H1
H2
H3
H4
1
Neck
1.38
1.75
1.00
2.25
2
Left shoulder
2.38
2.38
1.38
2.75
3
Right shoulder
2.38
2.50
1.38
2.38
4
Left arm
2.25
2.00
1.88
2.50
5
Right arm
2.13
2.25
2.00
2.63
6
Left elbow
1.88
1.75
0.88
1.50
7
Right elbow
1.88
1.88
0.88
1.63
8
Left forearm
1.88
2.13
1.13
2.13
9
Right forearm
1.88
2.00
1.13
1.75
10
Left wrist
1.38
1.50
1.25
2.00
11
Right wrist
1.50
1.75
1.38
1.50
12
Left palm
2.00
2.38
2.00
1.75
13
Right palm
2.13
2.50
1.38
1.50
14
Upper back
1.50
1.88
1.25
2.25
15
Mid back
2.25
2.63
1.63
3.38
16
Lower back
2.25
3.25
1.50
2.88
17
Buttocks
1.13
1.38
0.88
2.00
18
Left thigh
2.38
2.13
2.25
1.75
19
Right thigh
1.88
2.13
1.63
1.75
20
Left leg
2.00
2.38
1.50
2.38
21
Right leg
1.75
2.50
1.75
2.63
22
Left foot
2.25
2.38
1.63
2.13
23
Right foot
1.75
2.38
1.38
2.13
24
Overall rating
4.13
4.75
3.44
4.88
Table 4 Postural discomfort while working with four different handle heights Height
Working handle height
Overall discomfort rating
Body part discomfort score (BPDS)
H1
0.85 SH
4.13
44.13
H2
0.75 SH
4.75
49.75
H3
0.65 SH
3.44
33.00
H4
0.55 SH
4.88
49.50
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4 Discussion
Body Part Discomfort Score (BPDS)
By using the mean values of postural discomfort in Table 4, a graph was plotted which shows BPDS given by the subjects while working at different handle heights. It was clear from the Graph 1 that the highest discomfort regions were mid back and lower back for H4 and H2 heights. BPDS for H3 handle height were found lowest throughout all the body parts region as compared to other treatments except left palm and left thigh region. The criteria for deciding optimum handle height of leveller (paata) would be lower physiological cost of the worker, i.e., minimal heart rate, and minimum postural discomfort during levelling operation. Table 2 shows that the heart rate decreases with increse in the handle height. This result was also supported by Gite [14], who demonstrated a decrease in the heart rate with an increase in the handle height. The handle height H1 had the lowest heart rate (119.30 beats/min), whereas the highest value (130.94 beats/min) was found in H4 handle height. But in case of postural discomfort, H3 is lowest. Overall discomfort rating and body part discomfort score for this height were 3.44 and 33.0 which were noted (Table 4). The heart rate and postural discomfort both were highest in H4 handle height. The difference between the heart rate of H1 and H3 was not as much as compared to postural discomfort. Therefore, considering the heart rate, overall discomfort rating, and body part discomfort scores, the H3 height seems to be the optimum handle 4.00 3.50 3.00 2.50
H1 2.00 H2 1.50 H3 1.00 H4 0.50 0.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Body Part 1: neck, 2: left shoulder, 3: right shoulder, 4: left arm, 5: right arm, 6: left elbow, 7: right elbow, 8: left forearm, 9: right forearm, 10: left wrist, 11: right wrist, 12: left palm, 13: right palm, 14: upper back, 15: mid back, 16: lower back, 17: buttocks, 18: left thigh, 19: right thigh, 20: left leg, 21: right leg, 22: left foot, 23: right foot
Graph 1 Body part discomfort score at four handle heights
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height for a manually operated land leveller. The shoulder height of this region is 141.71 cm [16]. Thus, the recommended handle height of land leveller (paata) is 92 cm.
5 Conclusion The optimum handle height of manually operated land leveller (paata) is recommended as 92 cm for male agricultural workers of Western Uttar Pradesh, India. This optimum handle height is based upon heart rate values obtained using physiological and psychophysical studies carried out in the present work. Although this height may not be the same for all the regions of India, as the anthropometric data are different for different regions. Many studies on anthropometry have been carried out in India for design/redesign the agricultural tools and equipment [8–10, 12, 13]. These studies clearly show the different anthropometric data for all the regions. Therefore, the optimum handle height of land leveller is recommended as 0.65 times shoulder height for all the regions of India. Acknowledgements The authors are thankful to the Dayalbagh Educational Institute, Deemed University, Dayalbagh, Agra, for providing the facilities in Industrial Kinesiology laboratory. This work is supported by UGC, New Delhi, under Grant F. No. 3-38/2012 (SAP-II) dated 02/10/2012; and by DST, New Delhi, under Grant No. 100/IFD/2563/2012-2017 dated 20/07/2012.
References 1. Anand, Y.K., Srivastava, S., Srivastava, K.: Risk of occupational health hazard: Assessment using CDSwFR and minimization using EMOwJCS. Work 51(3), 621–632 (2015) 2. Srivastava, S., Anand, Y. K.: An intelligent system to address occupational health of workers exposed to high risk jobs. In: Proceedings of IEEE Congress on Evolutionary Computation, pp. 1977–1983. IEEE, Brisbane (2012) 3. Anand, Y.K., Srivastava, S., Srivastava, K.: Hybrid meta-heuristic based occupational health management system for Indian workers exposed to risk of heat stress. In: Trzcielinski, S., Karwowski, W. (eds.) Advances in Ergonomics in Manufacturing, pp. 110–120. CRC Press, Taylor & Francis, Boca Raton, FL (2012) 4. Anand, Y.K., Srivastava, S., Srivastava, K.: An integrated ANN-EMO approach to reduce the risk of occupational health hazards. J. Artif. Intell. Soft Comput. Res. 2(2), 77–95 (2012) 5. Srivastava, S., Anand, Y. K., Soamidas, V.: Reducing the risk of heat stress using artificial neural networks-based job combination approach. In: Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management, pp. 542–546. IEEM, Macau (2010) 6. Anand, Y.K., Srivastava, S., Srivastava, K.: Optimizing the risk of occupational health hazard in a multi objective decision environment using NSGA-II. In: Deb, K., et al. (eds.) Lecture Notes in Computer Science, pp. 476–484. Springer-Verlag, Berlin Heidelberg (2010) 7. Singh, G.K., Srivastava, S.: Grip strength of occupational workers in relation to carpal tunnel syndrome and individual factors. Int. J. Occup. Safety Ergon. (2018)
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8. Agrawal, KN., Singh, R.K. P., Satapathy, K.K.: Anthropometric considerations for farm tools/machinery design for tribal workers of North Eastern India. Agric. Eng. Int. CIGR E J. (2010) 9. Dewangan, K.N., Owary, C., Datta, R.K.: Anthropometry of male agricultural workers of northeastern India and its use in design of agricultural tools and equipment. Int. J. Ind. Ergon. 40, 560–573 (2010) 10. Dewangan, K.N., Owary, C., Datta, R.K.: Anthropometric data of female farm workers from north eastern India and design of hand tools of the hilly region. Int. J. Ind. Ergon. 38, 90–100 (2008) 11. Kumar, A., Mohan, D., Patel, R., Varghese, M.: Development of grain threshers based on ergonomic design criteria. Appl. Ergon. 33, 503–508 (2002) 12. More, S.H., Vyavahare, R.T.: Anthropometric and grip strength data of agricultural workers for marathwada region of Maharashtra (India). Int. J. Appl. Eng. Technol. 4(2), 148–153 (2014) 13. Vyavahare, R.T., Kallurkar, S.P.: Anthropometry of male agricultural workers of western India for the design of tools and equipment. Int. J. Ind. Ergon. 53, 80–85 (2016) 14. Gite, L.P.: Optimum handle height for animal-drawn mould board plough. Appl. Ergon. 22, 21–28 (1991) 15. Gite, L.P., Yadav, B.G.: Optimum handle height for a push-pull type manually-operated dryland weeder. Ergonomics 33, 1487–1494 (1990) 16. Singh, P.: Design of Agricultural Implements with Ergonomic Consideration, M.Tech. Dissertation, D.E.I. (Deemed University), Agra (2016)
Integrated Supply Chain Problems and Organizational Ergonomics: An Insight Rishav Khanal and J. Sanjog
Abstract Integration of suppliers (Integrated suppliers) in the supply chain helps to improve product flow, reduce lead time for supply of goods, increase supply reliability, reduce inventory levels, decrease administrative costs, and thus reduce the total production cost. However, the people involved in the supply chain may encounter problems relating to resistance for system change, lack of proper communication and coordination between manufacturers and suppliers, etc., on account of the integration of suppliers. An attempt has been made to identify the scope of organizational ergonomics in solving the problems encountered due to the integration of suppliers in the supply chain. Organizational policies and process which are an integral part of organizational ergonomics may help to design an effective and well-organized human-centered integrated supply chain. Keywords Organizational ergonomics · Integrated supply chain · Integrated suppliers · Human centered supply chain · Upstream supply chain
1 Introduction In earlier times, industries were mostly concerned about the activities within their premises and did only what they thought would give them monetary profit. Consequently, such industries did not give proper attention to the overall management/procurement of raw materials, productive use of raw materials, distribution of finished goods, etc., throughout the entire logistics network. In order to address the above-mentioned problem, the concept of Supply Chain Management (SCM) was introduced. SCM primarily focusses on the movement of materials from the early raw material stage, transformation of raw materials to finished goods, and the sale of finished products to the intended consumers. SCM aims to achieve competitive advantage, maximization of customer values through vigorous management of R. Khanal · J. Sanjog (B) Department of Mechanical Engineering, Shepherd Institute of Engineering and Technology (SIET), Sam Higginbottom University of Agriculture, Technology and Sciences (SHUATS), Allahabad 211007, Uttar Pradesh, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_22
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various supply chain activities, development and application of effective, and wellorganized supply chains [1]. The inward movements of materials to an organization (manufacturer) are classified under upstream activities [2]. The concept of integrated suppliers was introduced for improving the supply chain between manufacturers and their suppliers. The integrated supply chain primarily focuses on the upstream supply chain activities. Integration of suppliers (integrated suppliers) in the supply chain helps to improve product flow, increase production rate, reduce lead time for supply of goods, increase supply reliability, reduce inventory levels facilitating reduction in inventory costs, decline in administrative costs, reduced total production cost and increase in the profits for the supplier and the manufacturer. With the help of information sharing, the manufacturers and their suppliers attain a collaborative relationship [3] in their functioning. However, the integration of suppliers in the supply chain activities may also result in bringing about some people-related problems also. The following paragraph highlights some of the selected problems pertaining to humans/employees/workforce due to an integrated supply chain. Since the suppliers are integrated, some of the employees are bound to be given additional responsibilities for proper inventory management resulting in increased workload/work content. Similarly, some personnel will be relieved from the duties which they had been performing previously and given new tasks. This scenario may lead to an initial resistance from the workforce due to additional or change of responsibilities [3]. Normally, the manufacturers forecast the demand and convey the same to the suppliers. However, in the integrated supplier concept, the demand will be estimated initially by both the parties. Over a period of time, the suppliers may forecast higher demand (considering their business interests) which may not reflect the current market trend, thereby leading to overestimation of demand. Subsequently, conflicts may arise between the manufacturers and their suppliers due to miscommunication, overestimation of demand by the suppliers. Previously, manufacturers and suppliers were solely engaged with their respective share/section of the supply chain in the absence of an integrated supply chain. After the implementation of the integrated supply chain, suppliers and the manufacturers have to look into each other’s businesses and work toward better co-ordination between them. Thus, integration of suppliers with the manufacturers may create a hectic work schedule for the concerned people/workforce in the supply chain to carry out the work more efficiently. Integration of the suppliers with the manufacturers brings about increased visibility, responsibility, and ownership of all the inventories [3] (instead of a merely shifting the stocks/materials from the supplier to the manufacturer and vice versa), which may not be normally liked by people. From the problems mentioned in the above paragraph, it may be reasonably assumed that the people-related problems arising due to the integration of suppliers in the supply chain can only be solved by understanding the human needs, abilities, limitations, and human well-being. The need of the hour is perhaps to implement human-centered supply chains in order to mitigate the people/human-centered problems arising on account of the integrated supply chain.
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Organizational ergonomics, being a scientific discipline is concerned with sociotechnical systems takes into consideration organizational structures, policies, and processes for optimizing human well-being and overall system performance [4]. Design and evaluation of tasks, jobs, products, environments and systems are performed to make them compatible with the needs, abilities, and limitations of people [4]. The present paper tries to identify the scope of Organizational Ergonomics in solving the problems pertaining to the people due to the integration of suppliers in the supply chain.
2 Methodology Adopted Systematic approach was adopted to search published literatures/articles/books written in English language from electronic databases. Suitable publications identified following the online literature search were studied.
3 Results and Discussion Before the integration of the suppliers in the supply chain, the organization (manufacturers) and the suppliers were functionally viewed as two separate units. After the integration of suppliers with the organization (manufacturers), they may be functionally viewed as a single entity. Integration of suppliers in the supply chain activities may result in people-oriented problems like initial resistance from the workforce due to additional or change in responsibilities, conflicts between the manufacturers and their suppliers due to miscommunication and overestimation of demand by the suppliers, hectic schedule forced upon the concerned people in the supply chain resulting in incidence of fatigue among the workforce, general aversion of people toward increased transparency, responsibility and collective ownership of inventories, etc. However, during the literature survey, the application of organizational ergonomics for solving peopleoriented problems in the integrated supply chain was found to be very scarce. Hence, highlighting the application of organizational ergonomics in solving people-oriented problems (as described in the subsequent paragraphs) was considered necessary in the present context. Ergonomics effectively influences various aspects of the workplaces like job design, task design, team design, work design, and creation of dynamic and rewarding work environment [5]. Organizational ergonomics can provide a fully harmonized work system that ensures employee job satisfaction and commitment [6]. The physical and mental condition of the workers can be kept in good condition resulting in increase of productivity due to a harmonized work system. Therefore, the integrated
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supply chains may be suitably designed by addressing the workforce-related issues using organizational ergonomics principles. High Integration of Technology, Organization and People (HITOP) method is used for effecting technological change in industry by adopting a step-by-step manual procedure by considering the human needs [7]. HITOP analysis may be incorporated to successfully solve the problems arising due to the integration of suppliers with the manufacturers as evinced in Fig. 1. System Analysis Tool (SAT) is another tool which is helpful for macro-ergonomics assessments of work-system processes [8]. The table for the evaluation of variables is created and decision table or decision matrix helps to show the results. The factor tree for the problems, objectives, and activities are prepared, the last factors contributing as the major factor affecting the problems. Then, the alternative model is known with the help of input–output flow diagram and then they are evaluated. The diagram of the probable problem factor tree visualized (as a simple example) for solving the anticipated problems faced by the people due to the integration of the suppliers and the manufacturers is shown in Fig. 2. Macro-ergonomic Analysis of Structure (MAS) method used for the determination of the ideal work-system design, combines empirically developed analytical models
Fig. 1 Flow diagram showing the inclusion of HITOP analysis for solving people-related problems in integrated supply chain
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Fig. 2 Example of a problem factor tree for some people-related problems in integrated supply chains
to investigate the outcome of three main sociotechnical system elements (technological subsystem, personnel subsystem, external environment) on the framework of the organization’s work system which is considered as the fourth key element [9]. MAS method may also be found to be beneficial for solving human-related problems related to the integration of suppliers and manufacturers in the supply chain. Creativity Development Quick Scan technique helps to initiate discussions between the management and employees about the present situation, and explore possibilities for improvements [10]. Creativity Development Quick Scan method may be innovatively used in the integrated supply chain to inculcate creativity among the workforce for solving various human-related issues. Macro-ergonomics approach may be used for optimization of supply management, synchronization of supplies with current production, initiating cooperation on the level of supply chains (suppliers), management of logistic localization of the partner/cooperate, finding multiple sources of supplies, audit of suppliers, etc. [11].
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4 Conclusion Integration of suppliers with the manufacturers in the supply chain creates problems for the relevant people involved in the system. However, it has been observed that organizational ergonomics methodologies have not been used very much in the industry for solving such problems. Nevertheless, organizational policies and process which are an important part of organizational ergonomics can be developed/applied using appropriate techniques/methods to design an effective and well-organized human-centered integrated supply chain.
References 1. NC State University, https://scm.ncsu.edu/scm-articles/article/what-is-supply-chain-manage ment. Last Accessed 12 Oct 2017 2. Waters, D.: Logistics, 1st edn., p. 9. Palgrave Macmillan, New York (2003) 3. Fraunhofer, ecr-europe-integrated-suppliers. https://www.gs1.ch/docs/default-source/pro zesse-dokus/ecr-europe-integrated-suppliers—ecr-is-also-for-suppliers-of-ingredients-rawmaterials-amp-packaging.pdf?sfvrsn=61c76297_2. Last Accessed 12 Oct 2017 4. IEA. http://www.iea.cc/whats/index.html. Last Accessed 12 Oct 2017 5. Sharma, P., Gupta, S.: The Consonance of Organizational Ergonomics in Indian Construction. https://www.nbmcw.com/roads-pavements/36186-the-consonance-of-organizational-erg onomics-in-indian-construction.html. Last Accessed 12 Oct 2017 6. Nithya, E., Organizational Ergonomics – a tool for improving organizational effectiveness, http://www.indianmba.com/Occasional_Papers/OP253/op253.html, last accessed 2017/10/12 7. Majchrzak, A., Gasser, L.: HITOP Analysis. In: Stanton, N.A., Hedge, A., Brookhuis, K., Salas, E., Hendrick, H. W. (Eds.). Handbook of human factors and ergonomics methods, pp. 84.1–84.3, CRC Press, Florida (2005) 8. Robertson, M.M.: Systems Analysis Tool (SAT). In: Stanton, N.A., Hedge, A., Brookhuis, K., Salas, E., Hendrick, H. W. (Eds.). Handbook of Human Factors and Ergonomics Methods, pp. 88.1–88.7, CRC Press, Florida (2005) 9. Hendrick, H.W.: Macroergonomic Analysis of Structure (MAS). In: Stanton, N.A., Hedge, A., Brookhuis, K., Salas, E., Hendrick, H.W. (Eds.). Handbook of Human Factors and Ergonomics Methods, pp. 89.1–89.9, CRC Press, Florida (2005) 10. Dul, J.: Ergonomics’ contributions to a company’s innovation strategy. In: Salvendy, G., Karwowski, W. (eds.) Advances in Occupational, Social, and Organizational Ergonomics, pp. 782–785. CRC Press, Florida (2010) 11. Pacholski, L., Mateja, B.: Macroergonomic development of industrial production processes. In: Salvendy, G., Karwowski, W. (eds.) Advances in Occupational, Social, and Organizational Ergonomics, pp. 782–785. CRC Press, Florida (2010)
Ergonomic Interventions for Manual Material Handling Tasks in a Warehouse Vibha Bhatia, Parveen Kalra, and Jagjit Singh Randhawa
Abstract Manual material handling plays a crucial role in carrying out multifarious activities in manufacturing plants which includes lifting, bending, pulling, pushing, and carrying. Depending on the condition of the workplace, repetitiveness, and severity of the task, it may develop musculoskeletal disorders such as lower back pain and occupational injuries in the workers. The prevalence of MSDs in workers may result in reduced efficiency, productivity, and performance. In the present study, MMH activities in the warehouse are the prime area of interest which may lead to postural inadequacies in workers. The aim of the study was to ascertain ergonomic issues faced by the workers in the warehouse and to suggest ergonomic interventions to reduce the risk of work-related MSDs. After the extensive field study of the warehouse, ergonomic assessment of the workers was carried out by applying REBA to analyze the awkward working postures. The ergonomic analyses of the warehouse revealed that the risk of occurrence of WMSDs varied from medium to high in most of the workers. This suggested the dire need for implementation of ergonomic interventions and spreading awareness among the workers. Proper training related to ergonomic principles must be given at regular intervals to the workers. It was concluded that the ergonomic redesign of the work system would mitigate issues of WMSD, exertion, and low productivity. Small interventions may lead to the regeneration of a better environment without affecting the daily works. To improve the ergonomic aspects of the warehouse environment, significant recommendations were given. Keywords Manual material handling · WMSD · Warehouse · REBA · Ergonomic interventions
V. Bhatia (B) · P. Kalra · J. S. Randhawa PEC University of Technology, Chandigarh, India e-mail: [email protected] P. Kalra e-mail: [email protected] J. S. Randhawa e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_23
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1 Introduction Ergonomics is the branch of science which deals with the concept of designing the work in accordance with worker’s capability and may play a leading role in increasing the productivity of the company. Ergonomics act as the crucial factor in determining industrial parameters like manufacturing, material handling, planning, and distribution systems. Implementation of ergonomic rules in such situations results in increased quality and productivity, reduction in medical expenses, labor expenses and absenteeism [1]. These factors are mostly responsible for competitiveness in industries at the global level. Tasks involving repetitiveness and exertion, less recovery time, more force, and odd working postures are mostly associated with MSDs [2]. The increase in problems related to lower back is directly related to handling frequency and weight of objects [3]. The workers associated with handling tasks are more prone to back injuries than the supervisors who rarely do material handling task [4]. Industrially established countries have acknowledged the effect of musculoskeletal disorders (MSDs) on workers as the prominent reason for the heavy loss to industry and economy. In most of the industries, the need for manual material handling (MMH) tasks cannot be subsided, leading to serious health issues with costly treatment like lower back problems [1]. MMH is associated with 25% of workers, 87% of manufacturing time, and 55% of industry space layout [5]. Although a reduction in requirement of MMH has been observed due to the advancement in automation technologies but in developing countries due to the slow rate of industrial development this trend is not that accurate. In the present study, efforts have been made to record and analyze the common handling procedure in a warehouse. Ergonomic evaluation tool like REBA has been used for identification of the awkwardness in postures while doing handling work. These tools helped in detecting the need for intervention and further improvements in work handling habits.
2 Methodology The study was conducted in a medium-sized warehouse of the fast moving consumer goods (FMCG) industry. The warehouse consisted of the storage of the finished goods packages coming from the nearby production unit of consumer products where inventory was kept according to the sales order requirement. The study was done with the aim of spreading awareness among the workers and the industry employees regarding the losses they are incurring due to improper implementation of ergonomic principles in the industry and what modifications can be done to bring positive change in the situation. Workers were orally informed about the methods and objectives of the study and the written consent was taken for the data collection. At first, the complete cycle of
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work handling operations was randomly observed for 3 days. Material handling check sheet was used to record all the manual material handling details and problems related to daily work operations. A questionnaire containing the musculoskeletal disorders checklist was distributed among the workers before the actual study. The plant layout was sketched to find out the possible areas of improvement using ergonomic principles. All the data was collected without causing any disturbance to the normal working pace of the workers. Videography was done to capture the whole cycles of manual material handling works being done in the warehouse area like lifting, pulling, pushing, carrying, etc. The work cycle chosen for the study consisted of the lifting of the carton box from the conveyor, carrying, and putting the carton box on the wooden pallet. The video was made using a DSLR camera. The area under study had packaged rectangular cardboard cartons consisting of soap clusters moving on conveyor. To capture the important aspects of the working postures more focus was kept on the postures at the beginning and end of the work cycle. Two workers were employed for shifting packaged cartons from the conveyor to wooden pallets. Further, these pallets were displaced with the help of pallet trucks which are capable of carrying heavy loads. The average weight of the cardboard carton was measured to be 8.5 kg with no noticeable change in the size and shape. The surface roughness, sturdiness, and texture of the cartons were almost the same. No handles were provided on rectangular cartons for proper gripping. The methodology used in the study is shown in the flowchart given as Fig. 1. Ergonomic analysis: Rapid Entire Body Assessment tool (REBA) was used as ergonomic tools for the assessment of posture-related risks.
RISK ZONE IDENTIFICATION Random ObservaƟon
Videography
Material Handling Check Sheet
WORK AREA/CYCLE SELECTION FOR CURRENT STUDY
VIDEOGRAPHY OF SELECTED WORK CYCLE ERGONOMIC EVALUATION REBA
INTERVENTIONS Fig. 1 Flowchart of methodology
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Fig. 2 REBA calculation flowchart [6]
Reba: REBA postural analysis system was developed originally in the healthcare industry. The degree of musculoskeletal risks can be detected by analyzing the workspace system. It includes the analysis of upper/lower arm, neck, wrists, trunk, legs, and also the effect of load and force couplings. REBA flowchart is shown in Fig. 2. After careful filtering of the photographs or video frames, REBA was used on six common critical working postures to evaluate the ergonomic risk of the job or task. The following snapshots were taken out from the video for REBA score analyses (Figs. 3, 4, 5, 6, 7 and 8). The findings from the REBA study were discussed with the material handlers and supervisors in the warehouse. Brainstorming was done to find out the practical interventions that could bring positive outcome and reduce the occurrence of MSDs.
3 Results and Discussion The questionnaires filled by the workers were analyzed and was concluded that the major areas of occurrence of musculoskeletal disorders are neck, lower back, and trunk. The possible causes of these MSDs were identified after observation as 1. Inadequate knowledge of working postures 2. Inadequate design of plant layout 3. Poor implementation of ergonomic principles in design dimensions of trolleys,
Ergonomic Interventions for Manual Material … Fig. 3 First posture
Fig. 4 Second posture
Fig. 5 Third posture
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Fig. 7 Fifth posture
Fig. 8 Sixth posture
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Table 1 REBA scores and recommended actions Critical working postures
REBA Score
Risk Level
Actions
1
13
Very high
Implement change now
2
14
Very high
Implement change now
3
9
High
Investigate and implement change soon
4
9
High
Investigate and implement change soon
5
8
High
Investigate and implement change soon
6
12
Very high
Implement change now
conveyors, pallets, packaging boxes, etc. The REBA score sheet was made after the ergonomic analyses. The REBA score box containing REBA scores, risk level, and severity of recommended actions is shown in Table 1. Posture first, second, and sixth resulted in higher REBA scores as 13, 14, and 12, respectively. These postures mostly involved severe bending and twisting of the back which make them susceptible to high-risk zones. Some of the interventions which could reduce the REBA score were tabulated as follows in Table 2. It was suggested that intervention of hydraulically operated height adjustable pallets and trolley trucks may be considered a remedy for higher REBA scores up to some extent. Table 2 Work factors and recommendations Work characteristics
Risk factors
Recommendations
Carton box load
Force (high force)
Reduction of unit load
Obstruction to movement
Force (high force)
Clear and wide aisle
Equipment maintenance (trolleys & pallets)
Force (high force)
Periodic maintenance of equipment
Storage height
Awkward posture
Using assists to minimize bending, twisting
Quantity of material
Repetition and duration
The ready availability of equipment like trolley, pallets, etc
Age of workers and working Personal characteristics technique (strength, experience)
Work rotation and training related to WMSDs
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4 Conclusions The study suggested that all the MMH-related tasks cannot be avoided as it will disturb the normal functioning of the plant where labor constitute an important part of the work cycle. The high REBA scores in critical postures confirmed the need for effective intervention in the work cycles. Introduction of hydraulic pallet system may improve the critical postures ergonomically and is expected to reduce REBA score significantly. The recommendations and suggested interventions may be implemented to bring out expected improvement in the work cycles and to reduce the prevalence of MSDs in the warehouse.
References 1. Waddell, G., Burton, A.K.: Occupational health guidelines for the management of low backpain at work. Occup. Med. 51(2), 124–135 (2001) 2. Colombini, D., Occhipinti, E., Delleman, N., Fallentine, N., Kilbom, A., Grieco, A.: Exposure assessment pf repetitive upper limb movements. G. Ital. Med. Lav. Ergon. 23, 129–142 (2001) 3. Kraus, J.F., Schaffer, K.B., Mc Arthur, D.L., Peek-Asa, C.: Epidemiology of acute low back injury in employees of a large home improvement retail company. Am. J. Epidemiol. 146(8), 637–645 (1997) 4. Gradner, .I., Landsittel, D.P., Nelson, N.A.: Risk factores for back injury in 31,076 retail merchandise store workers. Am. J. Epidemiol 150(8), 825–833 (1999) 5. Gamberi, M., Manzini, R., Regattieri, A.: A new approach for the automatic analysis and control of material handling systems: integrated layout flow analysis (ILFA). Int. J. Adv. Manuf. Technol. 41(1), 156–167 (2009) 6. Torres, Y., Vina, S.: Evaluation and redesign of manual material handling in a vaccine production centre’s warehouse. Work 41(1), 2487–2491 (2012)
Ergonomics in Product Design—Past, Present, and Future: A Review Saed Enam Mustafa, Mohammad Asghar Khan, and Hasan Faraz
Abstract Ergonomics is one of the emerging fields of interest for the researchers of the twenty-first century but is being incorporated into unusual traits of human life from the period of prehistoric Greek civilization. On the former, it has been tried to present how Greeks have used ergonomics in the manufacture of various products. Later on, during the twentieth century, there have been many changes in the application of ergonomics in different aspects of the product design. In this paper, an attempt has been made to represent how ergonomics in product design has changed its face from the prehistoric Greek civilization to the present age and what are the future trends of ergonomic developments in product design. Keywords Ergonomic design · Desire · Product design · Future perspective
1 Introduction Ergonomics have been incorporated into the life of human being since the ancient Greek, though they did not use the terminology. At that time, it has been used in different fields like in tool design, transportation, utensils, etc., in order to minimize the workload and safety [1]. All over the past, human beings have purposefully tried to manufacture items of good looks and have been pleased in them. The design is frequently used in industries and developments, but also in the everyday lifecycle [2]. The insight of delicately manufactured items may provide desire and provocation. Comparatively, items with unpleasant design may be distasteful. ‘Ergonomics’, on the supplementary hand, takes pride in its scientific provenance, in spite of devouring a foot in both the physical and the social disciplines. Truly, designers do sometimes S. E. Mustafa (B) · M. A. Khan · H. Faraz Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India e-mail: [email protected] M. A. Khan e-mail: [email protected] H. Faraz e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_24
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use ergonomic facts, and ergonomists do sometimes present it in usable and systems which work well enough, most of the time [3]. Up to present days, ergonomic has been considered within this context, like an old-fashioned skill inclined method than as a spirited trait of product improvement. The prime objective of a producer, as well and a customer, has remained the growth of the function to cost proportion. The prime stress has remained the practical functionality products rather than on the desires of possible consumers. The analysis of produced goods and in precise, the consumer interface can do well if ergonomic facets are systematically merged at the primary step into the different stages of product improvement [4]. Individuals have a different opinion on using articles to fulfill their requirements. Engineers and ergonomists can approach the public from different angles and these viewpoints should be understood deliberately by engineers and ergonomists, considering the requirement of persons as purposeful measures [5]. Nowadays, Ergonomists intrude more and more early in the development of systems and products. In this way, their work is shifting, and now includes activities that deal with conception and innovation. In our opinion, this proclaims the emergence of a new trend in our discipline that will grow rapidly and become noteworthy in the next eras. It is vital for ergonomists to grab this new trend and prepare themselves for facing the contest that comes with it [6]. From the previous data, future proposals can be entailed. The procedure of changing information and to use that information has come to be progressively essential. Importance has to be placed on focussing the users’ own explanation to provide significant perceptions for designers concerning the features contributing to desire, comfort, and ease. The figures resulting from such experimental investigation can give an imperative response to forthcoming customer fashions associated with predilections for product planning [7].
2 Ergonomic in Past The application of ergonomic by the Greek can simply be understood through some pictures below.
2.1 Suitable Tools Design See Fig. 1.
2.2 The Ergonomic Design of Utensils for Daily Necessities See Figs. 2 and 3.
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Fig. 1 Stonecutting instruments [1]
Fig. 2 Bronze container with two handles [1]
Fig. 3 Infant’s feeding bottle [1]
With the help of these pictures, we can see how Greek used the principles of ergonomics in order to minimize the workload as well as for safety and to design their everyday useful products. But in olden days, the people in design development rarely have awareness, proficiency or distinct abilities in working upon user-centered
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approach [8]. From the past few years, developing sustainably has been the focus of scientists in the field of design and engineering [9].
3 Ergonomics at Present The inclusion of ergonomic reflections is often a facilitator to new thoughts for engineering designers [10]. The connection of designing with science is in continuous change [11]. Ergonomics originated design offers safe, contented, and proficient outcome by considering human traits. Ergonomically planned products avoid fatigue and distress. In the early 2000s, dynamics was a keyword in the design of office chairs, as opposed to the statics of maintained posture. People do move about as they please. Design should encourage and support free-flowing motions, as sketched in Fig. 4, with opportunities for transitory postures at the whim of the person. Emotional requirements have stayed the basis of impact for futuristic products containing a dignified blend of every feature. Limitations on time and funds have a predominantly substantial effect on design preparation [12]. The consumer interface of a product can be enhanced if ergonomic qualities are scientifically inculpated at a primary phase as shown in Fig. 5.
Fig. 4 Different sitting angles of people [2]
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Fig. 5 Schematic demonstration of a product lifespan [3]
DEFINITION
SCHEME
ASSESS
RECOGNITION
APPLICATION
4 Tendencies for the Future Looking into the future, life cycle valuation may be no longer the lone methodology to understand the functioning of product and function structures. Several norms imitating product and function value and consumer contentment would be lookedfor to estimate the system outcomes [13]. Consumer desires may consist of issues like efficacy, esteem, function, and desire [14]. The human-focused strategy has its backgrounds in an arena like ergonomics, computer technology, and artificial intelligence [15]. Various user products and services assure to make lives at ease, further pleasurable, more effectual or better, but they fail to do so [16]. In the recent decade, ergonomics has entered into the stream of medical science with a great velocity creating a strong relationship between the two poles apart streams, thereby enforcing the researchers to find out the factors through which human activities can be reinforced with engineering applications in order to achieve a new experience of comfort and ease while carrying out such tasks with the least effort which were difficult to achieve beforehand. For example, robotic hands, changing a lost higher limb with a useful limb, etc. The prerequisite for a useful prosthetic limb having self-control of the motor and realistic sensual response is very important and its progress is extremely essential aimed at the immediate future [17].
5 Conclusion So, with the help of this paper, we acknowledged that there has been a continuous reformation in the trends of the application of ergonomics in product design related to different aspects of human life. There has been a vast change in ergonomics in product design from the past to the present and also possibly in the near future. Product design has been considered as a differentiating tool to flourish in a competitive market [18]. Freshly designed digital tools have different features than the preceding ones
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and consumers approach these innovations in a different way [19]. With consumerfriendly goods, companies can provide benefits to its consumers, which beat those of contending ones [20]. So to conclude, we can say that there is a vast scope of development for ergonomics in product design as well concerning different areas of human life. Further researches may lead to the arrival of new fields of study and of course, the specialization of present branches in the stream.
References 1. Marmaras, N., Poulakakis, G., Papakostopoulos, V.: Ergonomic design in ancient Greece, vol. 30, pp. 361–368 (1999) 2. Chandrasegaran, S.K., Ramani, K., Sriram, R.D., Horváth, I., Bernard, A., Harik, R.F., Gao, W.: Computer-aided design the evolution, challenges, and future of knowledge representation in product design systems. Comput. Des. 45(2), 204–228 (2013) 3. Bloch, P.H.: Seeking the ideal form : product, Forty 1986, pp. 16–29 (1994) 4. Haubner, P.J.: Ergonomics in industrial product design ∗ 0139 (2015) 5. Acosta, G.G., Morales, K.L., Ernesto, D., Lagos, P.: Addressing human factors and ergonomics in the design process, product life cycle and innovation : trends in consumer product design, Kroes 2001 (2007) 6. Robert, J., Brangier, É.: Prospective ergonomics : origin, goal, and prospects, vol. 41, pp. 5235– 5242 (2012) 7. Taylor, P., Demirbilek, O., Sener, B.: Product design, semantics and emotional response, December 2013, pp. 37–41 (2013) 8. Taylor, P., Gulliksen, J., Lantz, A., Lantz, A.: Design versus design-from the shaping of products to the creation of user experiences. Int. J. Hum.–Comput. Interact. 2014, 37–41 (2010) 9. Radjiyev, A., Qiu, H., Xiong, S., Nam, K.: Ergonomics and sustainable development in the past two decades (1992 e 2011): Research trends and how ergonomics can contribute to sustainable development. Appl. Ergon. 46, 67–75 (2015) 10. Haslegrave, C.M., Holmes, K.: Integrating ergonomics and engineering in the technical design process 25(4), 211–220 (1994) 11. Broadbent, J.: Generations in Design Methodology, vol. 6925 (2015) 12. Goodman-Deane, J., Langdon, P., Clarkson, J.: Key influences on the user-centered design process, vol. 21, June 2010, pp. 345–373 (2010) 13. Chou, C., Chen, C., Conley, C.: An approach to assessing sustainable product-service systems. J. Clean. Prod. 86, 277–284 (2015) 14. Khalid, H.M., Helander, M.G.: Theoretical issues in ergonomics science a framework for effective customer need in product design, October 2014, pp. 37–41 (2014) 15. Giacomin, J.: What is human centred design ?, July 2015 (2015) 16. Khalid, H.M., Helander, M.G.: Concurrent engineering: research and applications (2006) 17. Micera, S.: The quest for a bionic hand: recent achievements and future perspectives. Brain Stimul. 12(2), 508 18. Noble, C.H., Kumar, M.: Using product design strategically to create deeper consumer connections (2008) 19. Taylor, P.: Explorations of perceived qualities of on-body interactive products, February 2015, pp. 37–41 (2013) 20. Luczak, H., Zink, K.J., Dul, J.: The strategic value of ergonomics for companies (2003)
A Comparative Analysis of a Mouse and Touchpad Based on Throughput and Locations for a Laptop Computer Mohd Shah Faizan, Tauheed Mian, and Mohammed Muzammil
Abstract In the present era, the use of laptop computer becomes an inseparable part of human life. This throws a challenge to the designers of the computer that the device may be designed keeping in mind the human capability. The human–computer interaction is generally done through the pointing devices such as a mouse, touchpad, joystick, etc. Hence, they should be designed to improve the performance by way of increasing the speed and accuracy during a certain task. In the present research, an analysis was carried out to study the two input pointing devices, namely touchpad and mouse on the basis of throughput and location of the laptop computer. For this, an interface based on ISO 9241, [2000] was designed to study the performance of the subjects. Eighteen subjects were chosen to perform this task to test the accuracy and speed of these two pointing devices. The experiment was performed with five different locations of the laptop. Results are found in terms of throughput using modified Fitts law. From the analyses, it was found that throughput for mouse ranges from 2.86 to 3.27 bits/s, and for touchpad it ranges from 1.89 to 2.16 bits/s. it was also evident from the results that the mouse gave better results at the farther position while the touchpad was proved to be better at closer distances. Keywords Pointing devices · Throughput · Interface · Location
1 Introduction Today, Internet is the necessity for the majority of the world’s population. According to Global Web Index, people spend 6–7 h a day on the Internet. Browsing the Web can be carried out on a wide range of computer-based products (e.g., smartphones, smart TVs, desktops, laptops, tablets, game consoles, e-book readers) using various input devices (e.g., mouse, touchpad, touch screen, pointing stick, trackball, and remote controllers). Among these, desktops and laptops are widely used in offices
M. S. Faizan (B) · T. Mian · M. Muzammil Mechanical Engineering Department, Aligarh Muslim University, Aligarh, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_25
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and institutions. In the present research work, we have analyzed two input devices, namely laptop computer mouse and touchpad. A computer mouse is an indirect, relative, isotonic, position-control, translational input device with two degrees of freedom and three states. It means mouse has movement on the x- and y-axis and three states are a range, tracking, or dragging. Similarly, the touchpad is a direct, absolute, isometric, position-control input device with two degrees of freedom and two states. Research has been done on the aspects of this field from a very long time. The touchpad, like the mouse, conforms to Fitt’s human model for movement along a single dimension [1]. Also, like the mouse, many touchpads integrate a tactile feedback mechanism that mimics the click of a mouse that, when tested in the laboratory resulted in both lower error rate and increased comfort [2]. Though mouse tends to promote higher performance compared to touchpads, it was found that the applied force used to select was greater than that of touchpads, causing more stress to the fingers [3]. A mouse has always maintained the function of selecting an item on screen by pressing and releasing a button when the cursor is over the item, with greater emphasis on accuracy than speed [4]. It has been found that mouse use is the most accurate and less error prone input mode for personal computers [5]. The research was conducted examining the usability of various inputs, showing the mouse use to be higher in pointing accuracy and lower in error rates relative to alternate input methods in key tasks such as dragging, clicking, and pointing [5]. Other tasks have also been investigated such as remote pointing input devices for smart TVs [6]. Returning to everyday tasks, a recent study compared performance of three input devices (the finger tapping, a stylus, and a mouse) in three pointing activities bidirectional tapping, one-dimensional dragging, and radial dragging or pointing to items arranged in a circle around the cursor [7]. The study confirmed that finger tapping is faster but more inaccurate with small targets than stylus and mouse. While the latter performed better in dragging tasks. If we talk about the aspects of WMSDs, the one side positioning of the mouse from the midline of the body resulted in the development of MSD due to excessive shoulder muscle activity [8]. On the other hand, the use of touchpad resulted in more neutral posture and causes the positioning of arm near the body midline [9]. However, the research showed that the touchpad induces discomfort in the region of shoulder and neck [10]. As there have been little researches on the usability of pointing devices in terms of speed and accuracy and user satisfaction, the focus of the study concentrates on a series of experiments that were designed and developed to evaluate the speed, accuracy, and user satisfaction in the use of a laptop. These involved comparisons of mouse and touchpad.
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Fig. 1 Designed interface for the experimental analysis
2 Methodology 2.1 Interface Design The interface for this comparative study is designed based on the guidelines of ISO 9241, [2000]. The layout is in the form of a regular arrangement of concentric circles. The circles are equally spaced with the innermost circle as the main target area as shown in Fig. 1. According to its distance from the target, the score is allotted to each circle. Basically, the score is the representation of the extent the hit point deviated from the target area.
2.2 Experimental Setup The analysis is carried out by recruiting eighteen subjects, each having good prior knowledge and experience in the field of computer work. The college environment is selected to perform the analysis with appropriate lighting and proper external condition. Moreover, the ergonomically design chair is considered for seating while the normal table is preferred for supporting a laptop. The Standard Company’s touchpad and mouse are incorporated in the analysis. Furthermore, five different locations are selected and marked on the table for varying the touchpad and mouse position. Basically, locations are varied by 50 mm each by considering the table’s end as a reference.
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2.3 Variables The experiment is done by considering the two input devices, namely mouse and touchpad. Apart from varying the input devices, the longitudinal distance of touchpad and mouse from the user is also varied.
2.4 Procedure Before carrying out the experimental measurement, each subject is briefed about the task to be performed. Then the subject is allowed to be seated on the ergonomically designed chair. Furthermore, the other parameters such as seat height, the distance of the chair from the table, laptop’s screen inclination with the base, and lightning were kept same throughout the experiment. The experiment is conducted, first by considering a mouse and locating it and a laptop to mark ‘A’. Then the subject is instructed to click the red circle one by one in a serpentine manner, starting from the upper left entity as shown in Fig. 1. Simultaneously, the time taken to click all the 28 readings is recorded and a score of each reading is evaluated. The experiment is then again conducted, this time by using touchpad while the position of laptop and the subject remain same. Likewise, further experiments are conducted for all the five positions of the laptop on 18 subjects.
3 Result The data obtained subsequent to experimentation is in the form of scores and movement time. The scores are examined and the standard deviation of hitting points around the main target is evaluated from it. Since the main objective of the experiment is to evaluate the speed and accuracy of input devices; therefore, modified Fitt’s law is employed to evaluate both terms simultaneously in the form of throughput. According to the modified Fitt’s law, the index of difficulty is the logarithmic function of the ratio of the distance between two targets to the width of the target. Index of Difficulty(ID) = log2
D +1 We
(1)
where D is the distance between the two targets and W e is the modified width of the target. The width is evaluated from the standard deviation as, W e = 4.133 SD. Subsequently, throughput is determined in bits/s as shown in Table 1, which is the ratio of index of difficulty (ID) to the movement time (MT). Throughput =
ID MT
(2)
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Table 1 Throughput in bits/s for different positions of the laptop Position
Point (mm)
Throughput in bits/s Mouse
Touchpad
Difference
A
100
2.86
1.89
0.97
B
150
3.09
2.16
0.93
C
200
3.06
2.03
1.03
D
250
3.27
2.07
1.2
E
300
3.11
2.01
1.1
Fig. 2 Actual image of the subject performing a task (left), schematic representation of experimental setup showing how the distance is varied (right)
The results are calculated in terms of throughput, which is a preferred parameter for considering both speed and accuracy simultaneously. Subsequently, the effect of speed and accuracy in the form of throughput is studied with varying the distance as shown in Fig. 2. The results obtained are shown in Table 1, for both the input devices with varying positions.
4 Discussion The throughput is about constant for touchpad at farther positions while throughput for the mouse is increasing for farther positions. So it can be said from the results that the mouse was ranked by the users as more accurate one while doing work on the table. The reason for such results could be, that working with mouse give lesser fatigue as compared to the touchpad. Another reason might be that, at a farther distance for using touchpad, the subject needs sharp movements of hands and arms which causes a high pressure on hand as well as on other parts of the body. It is clear
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Throughput in bits/sec
3 2.5 Mouse
2 1.5
Touchpad
1 0.5 0
0
100
200
300
400
Position
Fig. 3 Variation of throughput with the position of the input device
from Fig. 3 that the peak for the touchpad is at the nearer position while the peak for the mouse is at farther positions. The reasons for this are the same as we have discussed earlier.
5 Conclusion and Future Scope It can be concluded from the study that a laptop computer mouse is much better when doing a repetitive task such as data entry, working with Microsoft Excel, Microsoft word, etc. So we can say in offices and institutions, mouse should be provided with laptops for effective and better work. This will also result in lesser fatigue to the users. The present research analysis was carried out using eighteen subjects. One can take more subjects for better results. In the present analysis, subjects taken are the college students, so one can take subjects from working firms also. This will reflect a better result.
References 1. Fitts, P.M.: The information capacity of the human motor system in controlling the amplitude of movement. J. Exp. Psychol. 47, 381–391 (1954) 2. MacKenzie, I.S., Oniszczak, A.: The tactile touchpad - late-breaking/short talks. CHI 97, 309– 310 (1997) 3. Akamatsu, M., MacKenzie, I.S.: Changes in applied force to a touchpad during pointing tasks. Int. J. Ind. Ergon. 29, 171–182 (2002)
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4. Villar, N., Izadi, S., Rosenfeld, D., Benko, H., Helmes, J., Westhues, J., Hodges, S., Ofek, E., Butler, A., Cao, X., Chen, B.: Mouse 2.0: multi-touch meets the mouse. proceedings of UIST. In: ACM Symposium on User Interface Software and Technology, pp. 33–42 (2009) 5. MacKenzie, I.S., Kauppinen, T., Silfverberg, M.: Accuracy measures for evaluating computer pointing devices. CHI 3(1), 9–16 (2001) 6. MacKenzie, I.S., Jusoh, S.: An evaluation of two input devices for remote pointing. In: Eighth IFIP Conference, EHCI, pp. 235–250 (2001) 7. Cockburn, A., Ahlstrom, D., Gutwin, C.: Understanding performance in touch selections: tap, drag and radial pointing drag with near, stylus, and mouse. Int. J. Hum. Comput. Stud. 70(3), 218–233 (2012) 8. Cook, K., Burgess-Limerick, R., Chang, S.: The prevalence of neck and upper extremity musculoskeletal symptoms in computer mouse users. Int. J. Ind. Ergon. 26, 347–356 (2000) 9. Cook, K., Kothiyal, K.: Influence of mouse position on muscular activity in the neck, shoulder and arm in the computer users. Appl. Ergon. 29, 439–443 (1998) 10. Kelaher, D., Nat, T., Lawrence, B., Lamar, S., Sommerich, C.M.: An investigation of the effects of touchpad location within a notebook computer. Appl. Ergon. 32, 101–110 (2001)
Ergonomic Assessment of Chaff Cutting Task Md Samiullah Ansari, Faisal Hasan, Siddharth Bhardawaj , and Saiful Wali Khan
Abstract Chaff cutters are extensively used in agriculture for cutting fodder to feed livestock. Conventional chaff cutting machines operated manually are linked with large number of injuries in the past. Apart from single incident traumatic events, the machine could be the source of development of WMSDs over time. In the present study, ergonomics of chaff cutting machine have been evaluated through physiological measures. Electromyography (EMG) of four right upper limb muscle viz. biceps brachii (BB), triceps brachii (TB), trapezius (TR), and deltoid (DL) was evaluated for five subjects. Normalized RMS and slope of median frequency (MF) showed that BB was most fatigued muscle in the operation of chaff cutter compared to TB, TR, and DL. The identification of upper limb muscles involved in the task will serve as a starting point for tool modification. Keywords Chaff cutter · EMG · Agriculture ergonomics
1 Introduction Agriculture contributes to about 18% of Indian GDP while engaging 50% of country’s workforce [1]. Livestock sector is important part of agriculture that contributes to about 25% of total agriculture economy [2]. India stand first in the population of livestock where majority of its feed come from residue from the crop, grass, and weeds (comprising green fodder, dry fodder, and concentrates) [3]. Chaff cutter is an agricultural equipment used to cut fodder before being fed to the livestock. In design, the manual chaff cutter consists of a flywheel having curved blades. Two rollers geared to the flywheel are used to feed the fodder into the cutter. The whole assembly is mounted on a frame, generally fixed to the ground. A handle mounted at the rim of flywheel is used by the worker to rotate the flywheel to continue cutting of fodder.
M. S. Ansari (B) · F. Hasan · S. Bhardawaj · S. W. Khan Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, UP, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_26
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With an estimate of 10.4 million manual chaff cutters operating in India, high number of injuries directly linked to chaff cutter have been reported [4]. Being an extensively used device in agriculture, it is important to look into the ergonomics of design of these chaff cutters to improve the workers’ safety as well as their productivity. Awkward posture and repeated movements are linked with the development of work-related musculoskeletal disorders (WMSDs) and accidents at work places [5]. Physiology measurement from Electromyography (EMG) has provided objective assessments for discomfort and fatigue [6, 7]. Identification of muscles involved in the task is the first step in tool modification [8]. In the present paper, manual chaff cutting operation is being studied from the view point of EMG to identify the upper limb muscles involved in the task which could later serve as a starting point for tool modification.
2 Methodology 2.1 Participants Five healthy participants were recruited for the study. All the participants were university graduate students with age 25.0 ± 1.6 year and weight 62.6 ± 7.9 kg. All the participants were prior informed about the experiment. The study protocol and experiments were approved by university ethics board.
2.2 Muscle Groups Chaff cutting operation involves continuous motion of arms in sagittal plane involving shoulder rotation, elbow flexion/extension, and hand flexion/extension. Hence, muscles of the right arms and shoulder viz. biceps brachii (BB), triceps brachii (TB), trapezius (TR), and deltoid (DL) were taken into consideration for the study.
2.3 Instrumentation Bipolar active surface EMG electrodes (SX230, Biometrics Ltd., UK) were used for the measurement of EMG. The electrodes were interfaced with the PC using DataLINK subject unit and base unit (DLK900, Biometrics, UK). EMG data was sampled at 1000 Hz and saved in PC using DataLINK PC software (ver 7.0, Biometrics Ltd). To minimize the EMG noise grounding strap was tied at the wrist.
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Fig. 1 Participant performing the chaff cutting task
2.4 Design of Experiment The experimental task consisted of performing the chaff cutting operation for 2 min at the pace suitable to the participant. Two repeated trials were taken for each participant where each trial was separated by minimum rest period of 10 min to avoid muscle fatigue prior to next trial.
2.5 Procedure The subjects were first asked to practice the task. After the participant felt confident, actual experimental trials were conducted. First, sensors were places on the respective muscle group after skin preparation. After completing the interfacing, the participant was asked to perform the chaff cutting operation for 2 min. Rest period of at least 10 min was given to participant after which second trial was conducted. Figure 1 shows the participant performing experimental trial.
3 Results and Discussion The acquired EMG data was calculated for feature in time and frequency domain. Normalized EMG RMS was computed using peak dynamic normalization approach [9]. FFT was performed on the acquired EMG signal for computing the slope of
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median frequency (MF). 50 ms triangle-bartlett windowing was used for segmentation. Figure 2 shows the acquired signal and software interface for single trial of a participant. Figure 3 shows the peak normalized RMS and slope of median frequency for the experimental task. It was found that BB provided unvarying effort during the task as evident with low value of normalized RMS compared to DL, TB, and TR [9]. BB was also the most fatigued muscle group as signified from the slope of MF (Fig. 3b). Studies regarding posture assessment of chaff operators are also essential to assess the WMSD risks. Interventions can be though at first place to reduce the workload on the muscles during chaff cutting operations. Various incidents are recorded where
Fig. 2 Acquired sEMG within Biometrics DataLINK software
Fig. 3 Normalized RMS (a) and slope of median frequency (b) in chaff cutting task
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amputation of hand-arms were reported working with chaff cutters [4]. Feed mechanism is required to be modified in such cases so that hand or arm may not accidently drag into the cutters.
4 Conclusion and Future Scope BB was found to be the most fatigued muscle in the operation of chaff cutter compared to DL, TB, and TR. The study of psychophysical aspect in work is important to be studied for accessing the prevalence of WMSDs and taking out interventions for redesigning the chaff cutting task.
References 1. Madhusudhan, L.: Agriculture role on Indian economy. Bus. Econ. J. 06(04), 1 (2015) 2. Department of Animal Husbandry, Dairying and fisheries Annual Report 2017–18 (2018) 3. Dikshit, A.K., Birthal, P.S.: India’s livestock feed demand: estimates and projections. Agric. Econ. Res. Rev. 23(June), 15–28 (2010) 4. Kumar, A., et al.: Prevention of chaff cutter injuries in rural India. Int. J. Inj. Control. Saf. Promot. 20(1), 59–67 (2013) 5. Da Costa, B.R., Vieira, E.R.: Risk factors for work-related musculoskeletal disorders: a systematic review of recent longitudinal studies. Am. J. Ind. Med. 53(3), 285–323 (2010) 6. Bhardwaj, S., Khan, A.A.: Ergonomics investigation for orientation of the handles of wood routers. Int. J. Occup. Saf. Ergon. 24(4), 592–604 (2018) 7. Sormunen, E., Nevala, N.: User-oriented evaluation of mechanical single-channel axial pipettes. Appl. Ergon. 44, 785–791 (2013) 8. Bhardwaj, S., Khan, A.A.: Psychophysical factors in wood routing tasks. Glob. Sci-Tech. 7(1), 23–29 (2015) 9. Burden, A., Bartlett, R.: Normalisation of EMG amplitude: an evaluation and comparison of old and new methods. Med. Eng. Phys. 21(4), 247–57 (1999)
Experimental Study of Rate of Heat Release of Sprays in Supercritical Direct Injection Combustion System Using Sensor Sanaur Rehman
Abstract In present study, supercritical spray combustion and conventional (nonsupercritical) spray combustion are analyzed at same experimental conditions in direct injection constant volume combustion chamber under lean burning conditions. Combustion characteristics like rates of heat release during combustion process are studied in both combustion modes using piezo-resistive pressure transducer or sensor. Commercial diesel fuel and dieseline blend (50% gasoline and 50% diesel by volume) are used for normal spray combustion and supercritical fuel spray combustion, respectively. Fuel injection pressures used are 100, 200, and 300 bar. Hot surface temperatures remain constant at 623 K and cylinder air pressures used are 20, 30, and 40 bar. It is found that rate of heat release is significantly higher in supercritical spray combustion as compared to conventional spray combustion at all experimental conditions. Which means faster combustion process occurs in supercritical spray conditions due to higher fuel–air mixing rates associated with homogenous fuel–air mixing. Hence homogeneous supercritical spray combustion is a faster and cleaner diesel combustion technology for automotive diesel engines affecting human health and environment significantly. Also, it is found that rate of heat release increases with increase in IP, but decreases with increase in CP in both combustion modes at constant HST. Keywords Rate of heat release · Supercritical sprays · Hot surface ignition · Constant volume combustion chamber · Sensors
1 Introduction Stringent emissions regulations about pollutants and green house gases emissions from internal combustion engines, also depleting reserves of petroleum-based fuels point toward the need of new technology that can significantly improve the engine combustion process. One potential solution to simultaneously achieve high efficiency S. Rehman (B) Combustion and Pollution Control Laboratory, Department of Mechanical Engineering, ZHCET, AMU, Aligarh, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_27
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and reduction in engine emissions is proposed [1–4]. In some studies [5], it is found that SC spray injection and combustion results in 80–90% reductions in emissions of NOx and PM. These emissions are mainly responsible for polluting environment and causing severe human health problems like respiratory, mental problems, etc. The core of this new concept is to inject the fuel into engine cylinder in supercritical state (SC). The supercritical state is that state of matter when temperature and pressure of fluid are above the critical point. But at higher temperatures, required for SC state, coking phenomenon occurs in fuels [1]. The formation of coke means thermal decomposition of fuel at high temperatures that result in formation of some heavy products (coke). This coke formation cause choking of injector nozzles [1]. Therefore, to avoid this coke formation, some anticoking agents are used. Anticoking agents such as CO2 , H2 O, EGR, natural gas, or gasoline can be mixed with the fuel before injection [1–5]. Gasoline as an anticoking agent is a good choice for SC spray combustion study because of its many useful properties [6, 7]. Dieseline (DL) blend is mixture of diesel fuel and gasoline. DL blend has a lower critical temperature as compared to diesel fuel (approximately 450 °C) because of the addition of gasoline (approximately 357 °C, [8]). Constant volume combustion chamber (CVCC) is generally used for the basic combustion studies [9–13]. One simple and attractive method for the analysis of combustion process inside CVCC is the measurement of instantaneous pressure inside CVCC. This method is widely used in determining internal combustion engine performance and in CVCC [11, 14]. The pressure signal can be used for calculation of heat released as a result of combustion process. Recent trends toward smaller engine sizes with high pressure common-rail injection systems for high efficiency have increased spray/piston interactions and cause extensive fuel spray impingement on piston bowl walls [15–17]. Therefore, experimental conditions chosen in present study are typically those found in small size high-speed direct injection diesel engines. On the basis of the above studies, present work focuses on combustion characteristic (ROHR) of SC spray combustion process and its comparison with the conventional (non-supercritical) combustion process under similar experimental conditions. This work helps in understanding and developing SC spray combustion for significantly reducing harmful emissions affecting human health and environment significantly.
2 Experimental Setup 2.1 Experimental Setup and Description Present experimental setup and its components are shown in Fig. 1. The set up is designed and fabricated to measure normal and SC spray combustion characteristics of hollow conical sprays in CVCC under different experimental conditions. Cylindrical combustion chamber having fuel injector on one side and hot surface plate of
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Fig. 1 A Experimental setup and its components, B Image showing ROHR measurement
stainless steel on the other side of the chamber just opposite to each other is used. Fuel injector has pintle nozzle for producing hollow conical spray which is impinging on hot surface/plate. Bosch fuel injection pump is connected to the heated and insulated fuel injector through high-pressure fuel line. Fuel injection pump is operated manually with the help of lever mechanism. Fuel injection pressure is measured with pressure gauge mounted on pump shown in Fig. 1. Pressure gauge is mounted on combustion chamber for measuring initial (static) cylinder air pressure (CP). Temperature controller and indicator show the hot surface temperature (HST) and DL blend critical temperature through thermocouples (K type). The thermocouple is inserted in the fuel return valve of the fuel injector for measuring DL blend critical temperature. Sensor or piezo-resistive pressure transducer is used for recording pressure rise before and after combustion process at various experimental conditions on one channel of four channel digital oscilloscope (scopemeter).
2.2 Experimental Methodology The commercially available diesel fuel ad DL50 blend (50% gasoline and 50% diesel by volume) was used for studying normal spray combustion and supercritical spray (SC) combustion, respectively. Experimental conditions are shown in Table 1 given below. For each set of reading, mean value is calculated from the four repeated readings at same conditions to minimise the error in measurement. In case of supercritical spray combustion, in beginning, temperature of hot surface plate (HST) inside the combustion chamber is increased by means of heating coil and then temperature of hot surface plate is controlled and maintained at 623 K. The highly compressed air is introduced into the combustion chamber through the inlet valve at various cylinder air pressures (20, 30, and 40 bar). The hot surface temperature and cylinder air pressure are maintained inside the combustion chamber for steady state. Cylinder air pressure
236 Table 1 Experimental conditions
S. Rehman Operating parameters (controlled Typical values parameters) Fuel injection pressure
100, 200 and 300 bar
Fuel injection quantity
0.15 ml@100 bar, 0.14 ml@200 bar, 0.13 ml@300 bar
Cylinder air pressure
20, 30 and 40 bar
Hot surface temperature
623 K
is varied from 20 bar to 40 bar in steps of 10 bar for every fuel injection pressure (100, 200, and 300 bar) at constant HST. The DL50 is heated by heating fuel injector and measuring DL50 temperature. The thermocouple is inserted in fuel return valve of fuel injector for measuring DL blend critical temperature. The supercritical condition (critical temperature and pressure) for DL50 is nearly 629.3 K and 17.75 bar as estimated. The critical temperature for DL50 was estimated using Kay’s rule [18] and critical pressure for DL50 was estimated through Thompson’ relation [19]. Critical constants for different fuels and blend are given in Table 2. After heating the DL 50 blend inside injector above the required critical temperature of 356.3 °C, DL 50 blend is pressurised by Bosch fuel injection pump up to various injection pressures (100, 200, and 300 bar, which are above DL50 critical pressure) with the help of lever and in this way the supercritical (SC) spray condition of DL 50 blend is achieved. After achieving supercritical spray condition, DL50 blend is injected into the combustion chamber through injector having a pintle nozzle. At fixed HST and CP and IP conditions are changed as stated earlier. Injection, ignition events, and combustion events of impinging supercritical spray are recorded on the screen of four channel oscilloscope (digital scopemeter) with the help of various transducers (sensors). Maximum rate of pressure rise is calculated by dividing pressure rise (P) by time taken (t) to reach maximum pressure on channel C as shown in Fig. 1B. After noting down the readings from oscilloscope, all the exhaust gases are expelled out from the combustion chamber through the exhaust needle valve. Whole procedure is repeated again for other sets of readings. In case of conventional combustion, the whole procedure as of SC spray combustion is repeated. Only difference is that electric heater of fuel Table 2 Critical constants of diesel fuel, dieseline blend and gasoline
Fuels
Critical temperature (Tc) (K)
Critical pressure (Pc) (bar)
Diesel fuel (DF2)
714.71
19.23
Dieseline blend (DL50)
629.30
17.75
Automotive gasoline (AG)
543.9
25.7
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injector is turned off and the fuel is injected at its normal temperature. All steps of measurement and calculation are same as of SC spray combustion.
2.3 Rate of Heat Release (ROHR) Calculation in Direct-Injection Constant Volume Combustion Chamber Rate of heat release (ROHR) is an important parameter for the analysis of combustion phenomenon in diesel engine cylinder. Following equation is used for calculating ROHR in J/s or KJ/s. The derivation of following equation is given in study [20]. V is volume of combustion chamber and it is equal to 9.9 * 10−4 m3 and γ = 1.3. d Q n /dt = (1/(γ − 1) × V × 7.5 × (dv/dt)
3 Results and Discussions 3.1 Maximum Rate of Heat Release Characteristics ROHR is defined as the rate of release of fuel chemical’s energy during the diesel engine combustion process [17]. Maximum ROHR is the heat release rate corresponding to maximum pressure reached during combustion process [20]. In rest of this paper, maximum ROHR will be termed as simply ROHR. Graphs in Fig. 2A show the variation of ROHR in KJ/s with fuel injection pressure (IP) at fixed hot surface temperature (HST) equal to 623 K and at different cylinder air pressures (20, 30 and 40 bar) for both conventional (non-supercritical) and SC spray combustion process in DI CVCC system. Graphs in Fig. 2B show variation of percentage increase in ROHR with IP at HST = 623 K bar and at various CPs in the form of bar charts. ROHR is estimated and analyzed during SC spray combustion and conventional spray combustion process. Equation used to calculate ROHR in present study is shown in Sect. 2.3. The method and procedure for the measurement of rate of pressure rise [11, 14] and calculation of ROHR are same in both combustion processes. It can be seen in Fig. 2A that ROHR continuously increases with increase in IP in both SC and conventional spray combustion process. ROHR increase with increase in IP is due to enhanced fuel–air mixing rates associated with higher IP. Similar trends of heat release rate with injection pressures were reported elsewhere [17]. However, increase in ROHR with increase in IP in conventional spray combustion is relatively small at higher CP. This is may be due to fact that with increase in CP, ignition delay decreases and subsequently ROHR in premixed combustion phase reduces with negligible effect on ROHR in mixed-controlled combustion phase [21].
HST = 623 K, CP = 20 bar
Non-Supercritical Combustion Supercritical Combustion
100
150
200
250
300
350
Percentage Increase in ROHR
44 40 36 32 28 24 20 16 12 8
100 90 80 70 60 50 40 30 20 10 0 50
Percentage Increase in ROHR
S. Rehman
100 90 80 70 60 50 40 30 20 10 0 50
Percentage Increase in ROHR
ROHR (KJ/s)
238
130 120 110 100 90 80 70 60 50 40 30 20 10 0 50
ROHR (KJ/s)
Injection Pressure (bar)
44 40 36 32 28 24 20 16 12 8
Non-Supercritical Combustion Supercritical Combustion
150
200
250
300
350
ROHR (KJ/s)
Injection Pressure (bar) 44 40 36 32 28 24 20 16 12 8
Non-Supercritical Combustion Supercritical Combustion
150
200
250
300
Injection Pressure (bar)
(A)
50.18
100 150 200 250 300 350
HST = 623 K, CP = 30 bar
61.25
35.23 27.63
100 150 200 250 300 350 Injection Pressure (bar)
HST = 623 K, CP = 40 bar
100
67.88 58.27
Injection Pressure (bar)
HST = 623 K, CP = 30 bar
100
HST = 623 K, CP = 20 bar
350
HST = 623 K, CP = 40 bar
116.29
57.82
5.09
100 150 200 250 300 350 Injection Pressure (bar)
(B)
Fig. 2 A Variation of maximum ROHR with fuel injection pressure at HST = 623 K and at different CPs (20, 30 and 40 bar) in both combustion systems. B Variation of percentage increase in ROHR with fuel injection pressure at HST = 623 K bar and at various CPs
It is can also be seen from Fig. 2A, B that ROHR is higher in case of SC spray combustion as compared to conventional spray combustion at HST = 623 K for all CP. Moreover, percentage increase in ROHR significantly rises with increase in IP as shown in Fig. 2B for SC spray combustion as compared to conventional combustion being highest at 300 bar (116.29%). The higher ROHR in SC spray combustion process is due to fruitful change in properties of fuel in SC state. The thermophysical properties of fuel such as density, volatility, diffusivity, critical constants, surface
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tension, thermal conductivity, and viscosity significantly changes in SC state [22]. In SC sprays, the fuel is injected into cylinder air inside combustion chamber in SC state. SC is a state having single homogeneous phase [1–4]. In present study, DL50 blend is used for SC spray combustion. Also in SC state of fuel, surface tension reduces considerably, which causes easy breakup of fluid from core stream and rapid radial penetration into the air and results in quick homogeneous fuel–air mixture [7]. Also, SC injection of fuel (DL50) in form of spray inside combustion chamber significantly increases the spray/jet cone angle [7, 23] and this facilitates mixing of fuel with air inside the cylinder considerably. Furthermore, it is found that length of fuel spray penetration into cylinder air is significantly longer for liquid sprays than that of SC jets; therefore, resistance encountered by fuel molecules in SC fluid injection is larger than that experienced by fuel droplets in the combustion chamber (the latter having higher momentum), allowing more quick mixing of SC fuel into cylinder air. The higher volatility of DL50 blend due to more lighter/volatile components from gasoline causes vaporization and mixing faster with the air upon injection of SC fuel. The lighter components are deflected to wider angles than heavy components (diesel fuel), when injection of SC fuel occurs and consequently results in faster fuel–air mixing. The SC fluids are also having higher diffusivity than liquids and diffusivity promotes mixing; therefore, SC DL50 mixes quickly with air due to this property. All these favorable properties of SC DL50 support the faster and homogeneous fuel–air mixing as compared to mixing in conventional spray combustion and hence results in high rate of heat release in SC spray combustion than convention spray combustion at HST equal to 623 K and all CPs. Also in case of SC spray combustion, the impingement of SC fuel spray on hot surface reduces due to less spray tip penetration length of SC spray and wider cone angles of SC spray [7] and these factors may causes hot air combustion of SC spray. However, normal spray combustion is due to hot surface ignition. Mainly ignition of SC spray occurs in hot cylinder air. Therefore, a homogeneous mixing of SC fuel and air occurs rapidly inside CVCC and results in higher ROHR at HST equal to 623 K and at various CPs. Also, faster and quick combustion takes place in SC mode associated with higher rate of heat release and this faster combustion is mainly due to homogeneous fuel–air mixing. Homogeneous fuel–air mixing results in fast, smoother, and clean combustion; hence, SC spray combustion is a clean combustion technology for engines.
4 Conclusion In present study, SC spray combustion and conventional (non-supercritical) spray combustion processes are analyzed at same experimental conditions inside DI CVCC under very lean burning conditions. ROHR characteristic (combustion characteristic) during each type of combustion process is compared at same experimental conditions. It is found that ROHR increases with increase in IP, but decreases with increase in CP in both combustion processes at constant HST. It is also found that
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ROHR is significantly higher in SC spray combustion as compared to conventional spray combustion at all experimental conditions studied. This means faster combustion process occurs in SC spray conditions than normal spray conditions. This faster combustion is mainly due to homogeneous fuel–air mixing in SC spray conditions. Homogeneous fuel–air mixing occurs due to fruitful changes in thermophysical properties of SC fuel (DL50 blend). It is also found that increase in ROHR in SC spray combustion is even higher at higher IP in comparison to conventional spray combustion. Hence, homogeneous SC spray combustion becomes more faster at higher IP. Faster SC spray combustion due to homogeneous fuel–air mixing results in cleaner combustion, which reduces emission of pollutants (NOx and PM) from automotive engines in environment significantly and consequently affecting human health. Acknowledgements This work was supported by (TEQIP-II) project, MHRD, Govt. of India. Author also expresses his gratitude to Prof S. S. Alam, Mechanical Engineering Department, ZHCET, AMU, Aligarh for his support and guidance.
References 1. Tavlarides, L.L., Anitescu, G.: Supercritical diesel fuel composition, combustion process, and fuel system. US Patent 7488357, issued February 10 (2009) 2. Anitescu, G., Lin, R.-H., Tavlarides, L.L.: Preparation, injection and combustion of supercritical fuels, poster P-2. In: Directions in Engine-Efficiency and Emissions Research (DEER) Conference; Dearborn, MI, 3−6 August 2009. http://www1.eere.energy.gov/vehiclesandfuels/ pdfs/deer_2009/poster1/deer09_anitescu.pdf. Accessed April 2012 3. Anitescu, G., Tavlarides, L.L., Geana, D.: Phase transitions and thermal behavior of fuel-diluent mixtures. Energy Fuels 23(6), 3068–3077 (2009) 4. Anitescu, G.: Supercritical fluid technology applied to the production and combustion of diesel and biodiesel fuels. Ph.D. thesis, Syracuse University (2008) 5. Canter, N.: Tech. Beat, Tribology and Lubrication Technology, pp. 10–11 (2010) 6. Anitescu, G.; Bruno, T.J.: Volatility of gasoline and diesel fuel blends for supercritical fuel injection, poster P-2. In: Directions in Engine- Efficiency and Emissions Research (DEER) Conference, Detroit, MI, 3 − 6 October 2011. http://www1.eere.energy.gov/vehiclesandfuels/ pdfs/deer_2011/wednesday/posters/p-02_anitescu.pdf. Accessed Apr 2012 7. Anitescu, G., Bruno, T., Tavlarides, L.L.: Dieseline for supercritical injection and combustion in compression ignition engines: Volatility, phase transitions, spray/jet structure and thermal stability. Energy Fuels 26, 6247–6258 (2012). ACS Publications 8. Anselme, M.J., Gude, M., Teja, A.S.: The critical temperatures and densities of the n-alkanes from pentane to octadecane. Fluid Phase Equilib. 57(3), 317–326 (1990) 9. Ghojel, J.I., Tran, X.-T.: Ignition characteristics of diesel-water emulsion sprays in a constantvolume vessel: effect of injection pressure and water content. Energy Fuels 24, 3860–3866 (2010) 10. Rabl, S., Davies, T.J., McDougall, A.P., Cracknell, R.F.: Understanding the relationship between ignition delay and burn duration in a constant volume vessel at diesel engine conditions. Proc. Combust. Inst. 35, 2967–2974 (2015) 11. Lapuerta, M., Sanz-Argent, J., Raine, R.R.: Heat release determination in a constant volume combustion chamber from the instantaneous cylinder pressure. Appl. Therm. Eng. 63, 520–527 (2014)
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12. Lapuerta, M., Sanz-Argent, J., Raine, R.R.: Ignition characteristics of diesel fuel in a constant volume bomb under diesel-like conditions. Effect of the operation parameters. Energy Fuels 28, 5445–5454 (2014) 13. Kuszewski, H., Jaworski, A., Ustrzycki, A., Lejda, K., Balawender, K., Wos, P.: Use of the constant volume combustion chamber to examine the properties of autoignition and derived cetane number of mixtures of diesel fuel and ethanol. Fuel 200, 564–575 (2017) 14. Tinaut, F.V., Melgar, A., Giménez, B., Reyes, M.: Characterization of the combustion of biomass producer gas in a constant volume combustion bomb. Fuel 89, 724e731 (2010) 15. Ladommatos, N., Xiao, Z., Zhao, H.: The effect of piston bowl temperatures on diesel exhaust emissions. In: Proceedings of IMechE Part D: J. Automobile Engineering, vol. 219, pp. 371–388 (2005) 16. Rao, K.K., Winterbone, D.E., Clough, E.: Combustion and emission studies in a high speed DI diesel engine. IMechE International Conference, Paper C448(070), 117–129 (1992) 17. Heywood, J.B.: Internal Combustion Engines, 2nd edn. McGraw Hill International, New York (2011) 18. Kuo, K.K.: Principles of Combustion, Second edn. Wiley, New York (2005) 19. Thomson, G.H., Brobst, K.R., Hankinson, R.W.: An improved correlation for densities of compressed liquids and liquid mixtures. AIChE J. 28, 671–676 (1982) 20. Rehman, Sanaur: Hot surface ignition and combustion characteristics of sprays in constant volume combustion chamber using various sensors. Cogent Eng. 5, 1464879 (2018) 21. Grigg, H.C., Syed, M.H.: The problem of predicting rate of heat release in diesel engine. In: Proceedings of the Institution of Mechanical Engineers, vol. 184, pt. 3 J (1969–1970) 22. Lin, R., Tavlarides, L.L.: Thermophysical properties needed for the development of the supercritical diesel combustion technology: evaluation of diesel fuel surrogate models. J. Supercrit. Fluids 71, 136–146 (2012) 23. Doungthip, T., Ervin, J.S., Williams, T.F., Bento, J.: Studies of injection of jet fuel at supercritical conditions. Ind. Eng. Chem. Res. 41, 5856–5866 (2002)
Analysis of Health Issue and Musculoskeletal Problem for Workers in Manufacturing Sectors K. Adalarasu, T. Aravind Krishna, S. Sashank, and S. Kathirvel
Abstract India is undergoing rapid industrial growth in manufacturing and services sectors since liberalization of the economy in 1991. This growth has led to an increase in health problems and loss of productivity due to absenteeism ‘due to ill health.’ Ergonomics literatures have identified work-related musculoskeletal disorders (WMSDs) to be associated with several work-related factors. The objective of this study is to assess the musculoskeletal injury and health issue among thirtyfive workers working in small-scale manufacturing sector in South India using selfassessment questionnaire and 36 health survey (SF-36) questionnaire. Employees performing different types of jobs (lathe, forging, milling, shaping, etc.) were assessed. We find that workers suffer from high pain in neck, shoulder, and low back with low back pain being significantly high (p < 0.05) compared to neck or shoulder pain. Here, the pain is developed due to poor workplace conditions and work pressure. The evaluation of quality of life of workers done by comparing scores obtained from Short Form 36 health survey (SF-36) for physical health vs. emotional problems also shows that their health conditions are affected due to working conditions. To reduce WMSDs, we are in the process of identifying the contributing factors and providing ergonomic interventions, which will improve the health, worker comfort levels and will help enhance the productivity of the employer and the employee. Problems arising from WMSDs in the low back region have been well documented among industry workers. Present study also supports the findings.
K. Adalarasu (B) Department of Electronics and Instrumentation Engineering, SASTRA Deemed to be University, Thanjavur, India e-mail: [email protected] T. Aravind Krishna Centre for Business Research in Data Logic and Analysis, Coimbatore, India S. Sashank Department of Mechanical Engineering, SASTRA Deemed to be University, Thanjavur, India S. Kathirvel Department of Electronics and Communication Engineering, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_28
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Keywords Work-related musculoskeletal disorders · Low back pain · Emotional problems
1 Introduction India has undergone rapid industrial growth post-liberalization of the economy in 1991. This has led to more employment opportunities in manufacturing sector, but with an increase in health problems and loss of productivity due to absenteeism due to health issues. The small and medium enterprises sector accounts for around 45% of the manufacturing output in India [1]. Shop floor workers in the small and medium industries (SMEs) engage in manually intensive tasks, use conventional machines, and work in adverse conditions compared to workers in large-scale industries where conditions, systems, and procedures are well established [2]. Thus, people who work in SMEs are exposed to a variety of health hazards such as WMSDs. WMSDs are a subset of musculoskeletal disorders (MSDs) that arise due to occupation-related exposures and lead to injury or illness [3]. Hence, identification and prevention of WMSDs are very important. However, SMEs take few safety and health measures due to shortage of funds. Studies conducted in SMEs have found that these industries are more prone to WMSDs and lag in establishing and practicing occupational health and safety programs. For instance, Singh et al. [2] assessed noise and heat exposure & work-related safety practices used in small- and medium-scale casting and forging units in North India. It is shown that the heat exposure and ambient noise are comparatively high according to the norms of ACGIH/NIOSH. 95% of the workers suffered speech interference and over 68% of the people did not use not even personal protective device. The result also revealed that workers at such kind of industries were wide-open to heat and ambient noise at higher levels and were highly prone to be affected by noise induced hearing loss (NIHL). Seema et al. [1] studied occupational hazards and health problems among workers in Delhi and found that each and every worker was found to be exposed to at least one occupational hazard or the other. Dust/smoke (61.7%) followed by noise (45%) were the most prominent exposures. Other exposures were due to chemicals, metals, fumes, vapors, heat, vibration, and radiation. The study also found that majority of the workers were not aware of the health problems associated with their occupation and level of self-reported occupational health problems was 87.6%. Musculoskeletal symptoms (76%) and ocular complaints (41.6%) were the most predominant symptoms. Activities performed in traditional small-scale industries (SSIs) such as khadi village industries, handlooms, and handicrafts are also prone to WMSDs. Chandni and Neeta [4] studied workers performing activities in such traditional SSIs to find ergonomic risk associated with WMSDs by assessments using REBA. They concluded that 92–95% of handicraft workers had risks of MSDs. Workers performing tasks such as embroidery and patch working were associated with high risk, while workers doing activities such as stitching, sampling, and weaving and
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were associated with medium risk of MSDs. Nandita and Debkumar [5] investigated the activities performed by women workers in small-scale agro food processing industries in Assam. Aimed at identifying epidemiologic evidences associated with WMSDs, they assessed ergonomic risk using RULA and QEC to conclude that 90% of the workers suffer from back pain and that awkward postures, force, and repetitiveness were responsible for development of WMSDs. Singh et al. [6] studied in a small-scale forging industry. Based on risk assessments using RULA on 102 workers (performing forging, punching, trimming furnace, broaching, and grinding), they observed that around 20% among the workers were exposed to high risk and needed speedy interventions. Around 34.33% of the individual had medium risk while 45.32% had lower risk. They also used subjective assessment of discomfort to support the results. Qutubuddin et al. [7] analyzed the various exposures such as musculoskeletal disorders, health hazards, and ambient noise of people working in saw mills in Karnataka State to assess exposure to WMSDs, noise exposure, and occupational health hazards. The study used postural analysis (to assess ergonomic risk) and survey and visual analogue scale techniques (to justify the observations) to conclude that MSDs are prevalent among workers performing various activities in saw mills. They observed that use of bad postures during work was significantly practiced by the workers and there is a need to investigate for interventions. Sain and Meena [8] concluded based on the studies conducted in different SSIs and unorganized industries (such as sand core makers, gold smiths, carpenters, and agriculture) that the workers suffer from musculoskeletal disorders. They observed that the WMSDs are associated with strenuous manual tasks performed in poor environments over prolonged periods and with minimum safety. Shannon et al. [9] observed that poor working posture leads to neck pain and back pain which eventually alters the general health. Hence, musculoskeletal disorders are quite common among occupational problems faced by workers in SMEs. It is well established that musculoskeletal disorders play a vital role in causing disability among the working population all over the world. Several literatures reiterate that shop floor workers are susceptible to work-related musculoskeletal disorders because of the repetitive and labor-intensive work nature. Gangopadhyay and Dev [10] reviewed MSDs, occupational health problems, effects of ergonomic interventions in improving occupational health and productivity among workers and the accruing cost benefits to the SSIs. They observed that manual work and unergonomic design of workplaces and tools are the reasons for WMSDs and occupational health problems in SSIs. For example, the subject can get shoulder pain when loading or unloading die or while handling jigs and fixtures. He can get back pain when lifting heavy loads or continuously working in awkward postures, etc. Prolonged exposures to ergonomic risk factors are also associated with other health problems such as disk degeneration, low back pain, and muscle fatigue. This study focuses on analysis of occupational stress-related risk factors among the workers in a small-scale manufacturing industry through pain/discomfort experienced during work hours using self-assessment questionnaire and 36 health survey questionnaire. There are many ways of identifying exposures ranging from selfassessment of physical exposure to measurement of muscle activations and spinal
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loads [11]. Short Form health survey questionnaire (SF-36) is one of the popular tools to evaluate health-related quality of life. The SF-36 evaluates using eight scales: physical functioning, role physical, bodily pain, general health, vitality, social functioning, role emotional and mental health. In addition to this SF-36 also uses component analyses to add physical and mental dimensions to the measurements [12].
2 Methods and Materials 2.1 Participants Thirty-five (35) participants (22 males, 13 females, mean age (years) = 46.8; SD = 6.0, average experience (years) = 7.2; SD = 2.5) participated in this study. The physical characteristics of the participants are as follows: age: 35–57 years and weight: 45–64 Kgs. All participants were ITI holders with working experience of 4–13 years.
2.2 Experimental Design and Protocols First, the participants were evaluated for mini-mental state, and then the study was described to the participants. A self-administered questionnaire was provided to quantify the overall discomfort score at various body regions, namely neck, shoulder, back, elbow, hand/wrist, thigh, knee, leg, and feet/ankle (Fig. 1). Criteria for pain scale and their score are depicted in Table 1. Cronbach’s alpha test was used to estimate the reliability, or internal consistency, of a composite score. The three categories of Cronbach’s alpha were considered: 0.70 and above (good), 0.80 and above (better), and 90 and above (best). To check the reliability of data collected, we performed Cronbach’s alpha test. Cronbach’s alpha value was 0.70. So, collected data has good reliability Workers performing different types of jobs such as lathe, forging, milling, shaping, chemical washing, welding, drilling were assessed.
3 Results and Discussion Experience of discomfort is a subjective measure. Questionnaires are widely used for identifying musculoskeletal disorders and quality of life for workers. Workers were briefed about SF-36 and RGB pain scale and were asked to fill the pain experienced by them using pain scales. Quality of life of workers was evaluated by comparing scores obtained from SF-36. Score for health condition was significantly high (p
19 Years
1
0.66
112
73.68
Female
40
26.32
Weight
29
19.08
?50
69
45.39
51–60
41
26.97
>7
13
8.55
Gender
Workshops Fitting Shop
42
27.63
Carpentry Shop
38
25.00
Welding Shop
34
22.37
Machine Shop
38
25.00
170
65
42.76
Height (cm)
Percentage of Students (n=152)
5
Percentage
17 Years
Male 3
No. of Students (N = 152)
MSDs Symptoms
Fig. 1 Various MSD symptoms among students
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Fig. 2 Working postures of students in the workshop
3.3 Comfort Level Analysis Comfort levels are scores or indices used to quantify the level of comfort felt during a job or while handling various equipment. A comfort level scale 1 to 3 (1: Not comfortable, 2: Moderately comfortable, 3: Very comfortable) was selected to assess the comfort level of students while using hand tools and working at any workstation. Some hand tools like file, hacksaw, saw and jackplane were selected for analysis by their grip quality and handle size. Table height in carpentry and fitting shop and machines height were also considered for comfort analysis. Table 2 shows comfort level scores for various parameters identified for the workshop. The average comfort score is 2.16, which is above moderate. The minimum comfort score of 1.78 was found in the fitting shop for grip quality of file tool. Other areas of concern have handled the size of saw and grip quality of saw with comfort level scores of 1.83 and 1.98, respectively. On the whole, results show that improvements are required in areas where the score is less than 2.
4 Results and Discussion A case study of students working in a workshop of an engineering institute was conducted to investigate MSDs and other discomforts. The survey data was analyzed, and it was found that it has been observed that 72% of students reported musculoskeletal disorders related problems while working in the workshop. The most MSDs were found in the shoulder and finger part of the students. This is due to the repetitive use of the hand tool and improper postures and un-ergonomically designed workstations. The comfort scores for various parameters of hand tools were also calculated. The average comfort score was 2.16, which is above moderate. The two parameters handle the size of saw and grip quality of saw with comfort level scores of 1.83 and 1.98, respectively, also required improvement in hand tool design.
422 Table 2 Comfort level scores
P. Saraswat et al. S. No
Parameter
Average comfort score
1
Grip quality of the file
1.78
2
Handle size of the file
2.07
3
Handle size of hacksaw
2.19
4
Grip quality of hacksaw
2.16
5
Work table height of fitting shop
2.24
6
Grip quality of the saw
1.98
7
Handle size of the saw
1.83
8
Grip quality of jackplane
2.16
9
Handle size of jackplane
2.15
10
Work table height of carpentry shop
2.18
11
Work table height of the welding shop
2.45
12
Breathing in the welding shop
2.21
13
Lathe machine height
2.37
14
Shaper machine height
2.42
5 Recommendations After the analysis of musculoskeletal disorders (MSDs) and comfort score, there are some recommendations which are given below, to improve the working environment in the workshop. • The lot of improvement is needed to redesign the worktable. The repetitive nature of work is increasing the MSDs to students. Work table should be designed according to anthropometric measurements. The height of the table should be adjustable. • Working postures of the students should be according to the direction of the task, i.e., backward or forward. • The texture of hand tools must be nonslip; it should provide proper grip. • The average comfort score indicates the need to redesign of small hand tools. The design of handle size and grip quality of file and hacksaw, file and saw should be redesigned ergonomically.
6 Conclusion A mechanical workshop is a place where students can get hands-on practice in improving their workmanship and engineering skills. However, incorrect postures and un-ergonomically designed hand tools can lead to the cultivation of harmful
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practices which would result in severe MSDs in future if not in the immediate present. The significant improvements are needed in the tools as well as the workstations to achieve the desired ergonomic level for students. The reasons for low comfort levels were identified as un-ergonomically designed hand tools and workstations. In particular, comfort scores indicated that sizes of handles, as well as grip quality of various hand tools, require significant modifications. The results are quite similar to that of the findings of Bandyopadhyay and Sen [2] and other studies. The present study has helped in identifying various areas for improvements in hand tool design and workstation design in such institutional workshops. The results of the survey have given some basic guidelines as to which parameters need the most attention from the viewpoint of ergonomic improvement. A standardized ergonomic approach would indeed go a long way in preventing work-related musculoskeletal symptoms among students. Use of ergonomic principles and ergonomically redesigned hand tools can improve the work life and would result in reduced MSDs.
References 1. Abou-ElWafa, H.S., El-Bestar, S.F., El-Gilany, A.H., Awad, E.E.: Musculoskeletal disorders among municipal solid waste collectors in Mansoura, Egypt: a cross-sectional study. BMJ Open 2, e001338 (2012) 2. Bandyopadhyay, B., Sen, D.: Assessment of energy balance against the nutritional status of women carriers in the brickfields of West Bengal. Int. J. Occupation. Saf. Ergon. 22(3), 399–404 (2016) 3. Dianat, I., Karimi, M.A., Asl, H.A., Bahrampour, S.: Classroom furniture and anthropometric characteristics of Iranian high school students: Proposed dimensions based on anthropometric data. Appl. Ergon. 44, 101–108 (2013) 4. Domljan, D., Vlaovi, Z., Grbac, I.: Pupils working postures in primary school classrooms. Periodicum Biologorum 112(1), 39–45 (2010) 5. Gunning, J., Eaton, J., Ferrier, S., Frumin, E., Kerr, M., King, A., Maltby, J.: Ergonomics Handbook for the Clothing Industry. Union of Needletrades, Toronto (2001) 6. Hashim, A.M., Dawal, S.Z.M.: Evaluation of Students’ Working Postures in School Workshop. Int. J. Ergon. (IJEG) 3(1), 25–32 (2013) 7. Johanning, E.: Evaluation and management of occupational low back disorders. Am. J. Ind. Med. 37, 94–111 (2000) 8. Kilbom, A., Makarainen, M., Sperling, L.: Tool design, user characteristics and performance: a case study on plate-shears. Appl. Ergon. 24(3), 221–230 (1993) 9. Mehta, R.K., Agnew, M.J.: Influence of mental workload on muscle endurance, fatigue, and recovery during intermittent static work. Eur. J. Appl. Physiol. 112, 2891–2902 (2012) 10. Nejad, N.H., Choobineh, A., Rahimifard, H.: Musculoskeletal risk assessment in small furniture manufacturing workshops. Int. J. Occupation. Saf. Ergon. 19(2), 275–284 (2013) 11. Sain, M.K., Meena, M.L.: Occupational health and ergonomic intervention in Indian small scale industries: a review. Int. J. Rec. Adv. Mech. Eng. 5(1), 13–24 (2013) 12. Smith, D.R., Wei, N., Zhang, R.X., Lian, X.H., Wang, R.S.: Musculoskeletal disorders among Chinese nursing students. Ergon. Aust. 18, 18–22 (2004)
A Comparative Study of Thermal Environment Between Two Varieties of Pantry Car Available in Indian Railway Md. Sarfaraz Alam, Arunachalam Muthiah, and Urmi Salve
Abstract Pantry car workers play an important role in the catering system of the railways by serving onboard passengers for longer distance and duration. According to Government record, Indian railway has 338 pairs of trains running with pantry cars. Most of the train’s coaches are Integral Coach Factory (ICF) and few are Linke Hofmann Busch (LHB) make model. Due to changes in internal thermal facilities, it is expected to have different thermal experience while working in such situation. To understand the above, a study was formulated with an objective to compare and measure few environmental variables and thermal comfort of pantry car workers at both models. Total 29 pantry car workers (chefs and waiters) participated in this study, conducted during 2017 summer session. Environmental variables were measured using handheld anemometer. Psychometric chart was used to assess the position of relative air temperature at both types of workplaces. Analysis revealed that positions of relative air temperature at both pantry cars were out of comfort zone of ASHRAE standard. Further, all thermal variables were compared between both types of pantry car. Results revealed that there was a significant difference of dry-bulb temperature between both types. On the other hand, there were no considerable difference in humidity and airflow. It can be concluded that although the internal facilities are very different between these two types of pantry cars, the thermal comfort and variables are quite similar in both situations. A detailed study is required to understand the causal factors of the same. Keywords Thermal comfort · Rail pantry car · Relative air temperature
1 Introduction Indian railways has the largest rail network in Asia and the world’s secondlargest under one management, transporting 20 million passengers and more than 2 million tonnes of freight daily [1]. With 63,974 km of route lengths, Indian Md. S. Alam (B) · A. Muthiah · U. Salve Department of Design, Indian Institute of Technology Guwahati, Guwahati 781039, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_48
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Railways is one of the world’s largest railway networks with more than 12,000 passenger trains (Express/Mails, Superfast Express/Mail, Sampark Kranti Express, Yuva Express, Kavi Guru Express, Vivek Express, Rajya Rani Express, Jan Sadharan Express, Suburban trains, Shatabdi Express, Rajdhani Express, Humsafar Express, AC Express, Duronto Express, Tejas Express, etc.) running across the nation every day [1, 2]. Railways will continue to play a major role in the transportation sector in the twenty-first century [1]. Catering on Indian railways is of utmost importance and is one of the most important passenger amenities. Pantry cars occupy an important place in the catering system of the railways by serving the onboard passengers of long-distance train. Most of the long route trains in India have pantry car facilities [3]. According to Government of India, Ministry of Railways-2015, Indian railway has 338 pairs of trains running with pantry cars [4]. Among those pair of trains, most of the coaches of the train are Integral Coach Factory (ICF) make model and few are Linke Hofmann Busch (LHB) make model. The existing situation of ICF make model and LHB make model coaches’ train pantry cars is given in Fig. 1 and Fig. 2, respectively. Fig. 1 Working environment in a ICF make model coaches railway pantry car
Fig. 2 Working environment in a LHB make model coaches railway pantry car
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The existing situation of ICF make model coaches’ pantry car is uncomfortable or not suitable for kitchen chefs or workers because of the working environment condition and workplace area both are not conducive to human thermal comfort [5, 6]. In the existing situation, LHB make model coaches’ pantry car workplace area is comfortable as compared to ICF make model coaches’ pantry car [7]. But environment conditions at the time of cooking huge quantity of food are very humid because they increase a temperature of the air-conditioned (A.C) environment. If the temperature of A.C is decreased, they cannot cook food at the proper timing, it takes more time to boil/heat food, and very high toxic gas is produced at the time of cooking when the temperature is increased in the indoor environment [8, 9]. So, existing condition of both types of pantry chefs is facing high sweat-related problem at the time of cooking. Railway pantry car chefs are confronted with conditions with one or a combination of thermal hazards, including heat, flames, hot liquids, steam and hot surfaces. Environments with high heat and humidity, such as kitchens, contribute to heat-related illnesses among workers who spend long hours under these stress conditions [9]. Because of the very nature of the cooking process, devices in kitchens (e.g., furnaces, stoves, ovens) keep generating heat and moisture. Most of the heating devices create a high radiant heat and sometimes flames. Therefore, it is common that kitchens are hot and also humid [10]. These conditions can have an adverse effect on culinary workers by causing discomfort and fatigue. Heat stress is still the most neglected occupational hazard in tropical and subtropical countries. Heat stress and related dehydration can result in acute or chronic kidney failure. So, keeping in mind, the purpose of this study is to identify the thermal environment in ICF make model and LHB make model type of rail coaches’ pantry car in India.
2 Research Method 2.1 Study Location and Period The study was carried out in the Northeast Frontier Railway (also known as the N.F. Railway) one among the 17 railway zones in India. Headquartered in Maligaon, Guwahati in the state of Assam, it is responsible for rail operations in the entire Northeast and parts of West Bengal and Bihar. Due to security and safety reasons, a study period of only fifteen days was permitted. Hence, the period of study was selected in the first two weeks of March (1 to 15) 2017 summer session, which includes few of the hottest, days of the month.
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2.2 Participants and Tools In this study, the survey has been conducted on 29 pantry car workers. The workers from four chefs, ten waiters in an Avadh Assam Express (ICF make model train) and five chefs, ten waiters in a Rajdhani Express (LHB make model train), respectively. The study entails field measurements of environmental variables: air temperature (°C), the percentage of humidity (%RH) and airflow (KT), using handheld anemometer in pantry car areas during their working hours. Also the tools used in the study are psychometric chart, graph thermal comfort ASHRAE-55 and camera.
3 Result and Discussion 3.1 Psychometric Chart Analysis Online psychometric chart is used to get comfort zone area. The input data of temperature, humidity, metabolic rate and clothing are determined based on the research results. The comfort zone can be seen in the blue area; whereas, the position of relative air temperature is symbolized by red circle point. The complete results for comfort zone in the ICF make model coaches and LHB make model coaches pantry car can be seen in Fig. 3 and Fig. 4, respectively. Based on the calculation of online psychometric chart, the value of relative air temperature is out of the comfort zone area. Analysis revealed that in position of relative air temperature of the ICF make model coaches and LHB make model coaches, the pantry cars were out of comfort zone of ASHRAE standard. So, working environment is not suitable for both types of railway pantry car.
Fig. 3 ICF make model coaches
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Fig. 4 LHB make model coaches
3.2 Statistical Analysis for Comparing Between Both Types of Pantry Car Using Independent Sample Test The t-test assesses whether the means of two groups, or conditions, are statistically different from one other. In this test, all environmental variables (air temperature, humidity and air speed) were compared between ICF make model and LHB make model of pantry car to understand the preference level of the worker. All measured values (air temperature, humidity and airflow) calculated using IBM SPSS version 20 are given in Table 1, Table 2 and Table 3, respectively. For air temperature case, result of F-test, it is clear that sig. (p-value) is found to be 0.73 which is more than 0.05. So the variances are assumed to be equal, and top row of the t-test will be used for analysis. As p-value (0.000) is less than 0.05, null hypothesis can be rejected and alternative hypothesis can be accepted. Therefore, it can be concluded that there is significant difference between both types of pantry cars. For humidity case, result of F-test, it is clear that sig. (p-value) is found to be 0.40 which is more than 0.05. So the variances are assumed to be equal, and top row of the t-test will be used for analysis. As p-value (0.582) is more than 0.05, null hypothesis can be accepted and alternative hypothesis can be rejected. Therefore, it can be concluded that there is no significant difference between both types of pantry cars. For airflow case, result of F-test, it is clear that sig. (p-value) is found to be 0.007 which is less than 0.05. So the variances are not assumed to be equal, and bottom row of the t-test will be used for analysis. As p-value (0.131) is more than 0.05, null hypothesis can be accepted and alternative hypothesis can be rejected. Therefore, it can be concluded that there is no significant difference between both types of pantry cars.
Equal variances not assumed
Equal variances assumed
0.11
0.73 6.4
6.47 23.89
26
df
t
F
Sig
t-test for equality of means
Levene’s test for equality of variances
Table 1 Independent samples test for air temperature
0
0
Sig. (2-tailed)
7.4
7.4
Mean Difference
1.15
1.14
Std. Error Difference
5.01
5.05
Lower
9.79
9.75
Upper
95% Confidence Interval
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Equal variances assumed
26 25.19
−0.55 −0.56
0.72
df
t
F
0.4
Sig
t-test for equality of means
Levene’s test for equality of variances
Table 2 Independent samples test for humidity
0.576
0.582
Sig. (2-tailed)
−1.64615
−1.64615
Mean Difference
2.90811
2.95217
Std. Error Difference
−7.62
−7.71
Lower
4.33
4.42
Upper
95% Confidence Interval
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Equal variances not assumed
Equal variances assumed
8.14
0.007 1.47
1.55 15.13
26
df
t
F
Sig
t-test for equality of means
Levene’s test for equality of variances
Table 3 Independent samples test for airflow
0.161
0.131
Sig. (2-tailed)
1.132
1.132
Mean Difference
0.89
0.84
Std. Error Difference
Upper 0.3 0.32
Lower −0.04 −0.05
95% Confidence Interval
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Statistical result revealed that there was a significant difference of dry-bulb temperature between both types of pantry cars; whereas, there was no considerable difference in humidity and airflow between these two types of pantry car.
4 Conclusions A pilot study attempts to understand the current situation of the indoor thermal environment of ICF make model and LHB make model coaches’ pantry cars of Indian railway (IR) in the summer season. India has the fourth-largest rail network in the world, and pantry cars occupy an important place in the catering system of the Indian railways by serving the onboard passengers of long-distance train. The analysis of the survey results is as follows: • Psychometric chart analysis revealed that the position of relative air temperature of both the pantry cars was out of comfort zone of ASHRAE standard. • Statistical result revealed the significant difference of dry-bulb temperature between both types of pantry cars; whereas, there was no considerable difference in humidity and airflow between these two types. There is a need to replicate these findings in future prospective studies with adequate sample size and possible design intervention to reduce the problem of thermal discomfort.
References 1. Neeraj, K.: Rolling stock Indian railways year-book 2010–11,Ministry of Railways Government of India, 5–67 (2012). 2. Deb, C., Ramachandraiah, A.: Evaluation of thermal comfort in a rail terminal location in India. Build. Environ. 45(11), 2571–2580 (2010) 3. Vidhale, A.A., Palekar, A.D., Kanchan, A.: Automated pantry car system. Int. J. Adv. Res. Comput. Sci. Soft. Eng. 4(2), 692–699 (2014) 4. Yadav, K.P.: Details of train running with pantry car. Ministry of Railways, Government of India, 1–7 (2015). 5. Poddar, S., Panja, S.C., Gangopadhyaya, M.: Human factors analysis for railway coach and bogie maintenance using AHP. Proceedings of the 2015 International Conference on Operations Excellence and Service Engineering, pp. 87–95. IEOM Society,Orlando, Florida, USA (2015). 6. Simone, A., Bjarne, W.O., John, L.S., Watkins, A.W.: Thermal comfort in commercial kitchens (RP-1469): procedure and physical measurement (Part 1). HVAC&R Res. 19(8), 1001–1015 (2013) 7. Chandra, K.: Maintenance manual for BG coaches of LHB design. Ministry of Railways, Government of India (2002) 8. Bindu, E., Reddy, M.: Perception on work environment stress by cooks in commercial kitchens. Int. J. Sci. Res. 5(10), 1320–1323 (2016)
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9. Singh, A., Kamal, R., Mudiam, M.K.R., Gupta, M.K., Satyanarayana, G.N.V., Bihari, V., Shukla, N., Khan, A.H., Kesavachandran, C.N.: Heat and PAHs emissions in indoor kitchen air and its impact on kidney dysfunctions among kitchen workers in Lucknow. North India. PLoS ONE 11(2), 1–14 (2016) 10. Matsuzuki, H., Ito, A., Ayabe, M., Haruyama, Y., Tomita, S., Katamoto, S., Muto, T.: The effects of work environments on thermal strain on workers in commercial kitchens. Ind. Health 49(5), 605–613 (2011)
Gender Differences in Sleep Apnea—A Questionnaire Study J. Rajeswari, M. Jagannath, and K. Adalarasu
Abstract Sleep disorder is considered as a disturbance during sleep. There are varieties of issues occur in sleep like sleep talking, sleep walking, rapid eye movement (REM), nightmares, etc. Most common type of sleep disorder is sleep apnea that is closely associated to breathing. The objective of the study was to provide an exploratory analysis of gender difference in sleep apnea by self-administered questionnaire. Fifty participants involved in the study. The Berlin questionnaire (BQ) study was performed to identify the levels of sleep disorder of the participants ranging from low risk to high risk. The questionnaire study contains the information about the sleep-related problems like snore, fatigue and blood pressure. To assess the intermediate levels, three categories of questionnaire were used; Category 1 includes the major symptoms of the sleep apnea, i.e., snoring, and Categories 2 and 3 concentrate on the common symptoms of the sleep apnea. The number of positive responses decided the segregation of control group (sleep apnea) and normal. The threshold level was set to 5 for the separation of the groups. Out of 50 participants, 23 (14 female and 9 males; Age: 19–50 years) were identified as control group. There is a significant difference (p < 0.05) in sleep apnea scores between male and female. The sleep apnea scores were found to be high in females as compared to males. The result may be generalized for the population of large quantity by analyzing the power studies in examining the gender differences in sleep apnea clinical manifestations. Keywords Sleep disorder · Rapid eye movement · Sleep apnea · Gender differences
J. Rajeswari · M. Jagannath (B) School of Electronics Engineering, Vellore Institute of Technology (VIT), Chennai, Tamil Nadu, India e-mail: [email protected] K. Adalarasu School of Electrical and Electronics Engineering, SASTRA Deemed To Be University, Thanjavur, Tamil Nadu, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_49
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1 Introduction Sleep disorder is the problem that affects the patients during sleep. There are plenty of problems occur during sleep such as sleep apnea, insomnia, narcolepsy, restless legs syndrome and circadian rhythm sleep disorders [1]. The break of inspiratory airflow for at least 10 s is termed as apnea. Reduced airflow for 10 s or longer is known as hypoapnea. The fragment cessation of airflow during sleep is sleep apnea. It is found the most important cause of daytime sleepiness and eventually leads to cardiovascular disorder. Obstructive sleep apnea (OSA) occurs when the total blockage in upper airway along with snoring [2]. The frequency of sound (20– 300 Hz) is described as a well-known respiratory sound, i.e., snoring. The vibration in the tissues like soft palate, tongue base, uvula, pharyngeal walls, tonsils, etc., from upper airway is the major source of snoring [3]. It stops the airway when the relaxation of pharyngeal muscles. Many researchers have been reported that the polysomnography (PSG) is a difficult procedure to determine the OSA problem. During the lab examination, complete signals respiratory movement, breath airflow, electrocardiography (ECG), electrooculography (EOG), body position, electroencephalography (EEG), electromyography (EMG), oxygen saturation (SpO2) are assessed for monitoring the OSA [4]. In contrast, central sleep apnea (CSA) occurs when there is a presence of irregular breathing in the brainstem respiratory centers. In CSA, the blockage of breathing can last up to 20 s. Hyperventilation, circulatory delay and cerebrovascular reactivity are the common factors that lead to heart failure and in turn affect the respiratory stability [5].
1.1 Risk Factors of Sleep Apnea The various causes of sleep apnea are identified in accordance with Joseph and Costanzo [5]. Age: 20% of the older age adults may be at severe threat of sleep apnea. There is a possibility of sleep apnea in younger age children. Overweight: Sleep apnea occurs in obese people because fat blocks the upper airway breathing. Neck dimensions: Thicker neck people may have blocked upper airway. Smoking and alcohol consumption: Smokers may have the sleep apnea because of the amount of infection and fluid retention in upper airway. Heart failure, high blood pressure and stroke: People who have heart disease, high blood pressure and stroke seem to be major risk of sleep apnea. Multiple questionnaire patterns were available for the evaluation of sleep apnea from the patients. Notably, BQ, STOP-BANG questionnaire and Epworth sleepiness scale seem to be an accurate one for better results. Over the past few years, several researches have focused on the detection techniques of sleep apnea through various
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signals such as electrical activity of the heart, electrical activity of the brain, nasal air flow and oxygen. In our previous published research, we referred various detection and treatment methods for sleep apnea using sensors and electrophysiological signals [6]. In this paper, we focused on gender-based differences in sleep apnea patients. The paper has four sections: Sect. 1 that describes the background and existing literature of the work. Section 2 highlights the methods and materials of proposed work. Section 3 indicates the brief discussion about the results. Finally, conclusions are drawn in Sect. 4.
2 Methods and Materials 2.1 Participants Fifty participants (19 males and 31 females) with mean age of 34.5 years and standard deviation of 21.9 involved in this study. All participants were volunteers whom had the following physical characteristics. Age: 19–50 years, Weight: 45–64 kg. The participants are students, research scholars, working and non-working people.
2.2 Experimental Design and Protocols The qualitative study had been clearly explained to the participants. A selfadministered questionnaire was given to the participants to enumerate the symptoms of sleep apnea. The sources for the typical questions are Berlin questionnaire (BQ) and sleep questionnaire (SQ) [7]. The questionnaire separated into three categories for better understanding. Category 1 includes the most common symptoms of sleep apnea, i.e., snoring. This category is mainly used to identify the symptoms of sleep apnea. Category 2 specifies the common indications of sleep apnea: morning sickness, sleepiness while driving and at daytime, neck perimeter and tiredness during daytime. Category 3 includes some of the symptoms that are occurred in deep sleep only known by bed partner. The typical questions from the questionnaire are depicted in Table 1.
3 Results and Discussion Studies show that OSA is higher in females than males. Still there are high variations in the genders in the clinical population because females are largely false diagnosed. For general population, the male to female ratio of OSA is estimated between 3:1 and
438 Table 1 Typical questions from the questionnaire
J. Rajeswari et al. S.No
Question
1
Do you have any of the following health problems?
2
Do you snore?
3
Have you noticed the pauses in between sleep?
4
How long is the duration of the pauses?
5
Are you feeling tired or fatigued during daytime?
6
Do you have the extreme daytime sleepiness?
7
Do you have the habit of fallen asleep while driving a vehicle?
8
What is your neck size in centimeter? Mention it
9
Do you feel brisk when you start your day?
10
Do you wake up frequently during sleep?
11
Are you taking more time to fall asleep during nighttime?
5:1, whereas for clinical population, it is estimated between 8:1 and 10:1 [8]. Subjective scale tests involving questionnaire studies are distinguished methodologies for analyzing sleep disorders. To identify the threat of sleep apnea from the volunteers, the most significant screening tool was performed that is BQ. The BQ categorized into three sections which are shown in Fig. 1. Category 1 incorporates questions about snoring, Category 2 includes behaviors in daytime, and Category 3 represents the body mass index (BMI) and hypertension [9]. To confirm the accuracy of the patient results, the family members or bed partners should be enquired. The score of the BQ was determined from the positive results from the categories. Two or more categories were positive, and the results should be high risk, while low risk can be indicated, while those who did not scored. On the basis of the BQ, the result shows that there is a prevalence of high risk of sleep apnea, where the female participants out of 31 (p < 0.05), 14 observed the symptoms of sleep apnea. Out of 19 male participants, nine had the symptoms of sleep apnea, and it is shown in Fig. 2. The positive results from Category 1, 2 and 3 represent the symptoms of sleep apnea, where the two points from Category 1 denote the positive result for having sleep apnea. As same as Category 1, Category 2 also assumes two points for positive result. Further, Category 3 assumes one point for positive result. If two or more categories are positive, then it is assumed to get severe threat of sleep apnea. Suppose, only one category is positive, it represents the low danger of sleep apnea. Results of the self-administered questionnaire demonstrate the gender differences in sleep apnea. From previous studies also, it is manifested that the snoring, daytime and nighttime sleepiness, BMI, heart failure, cardiovascular diseases, stroke and age may be the symptoms of sleep apnea [10]. Multiple methods were found to detect the sleep apnea such as physiological signals, smart devices, CPAP devices and surgical methods. The questionnaire evaluated well the patients for detecting
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Fig. 1 Standard Berlin questionnaire with scores
sleep apnea. The contingency table of BQ for estimating patients with sleep apnea is given in Table 2.
4 Conclusions The results of previous and current research declared that the challenges in detection of sleep apnea. The questionnaire includes the typical question that belongs to the symptoms of sleep apnea. Accurate results were established by these questions. In this work, we followed the pattern of BQ and constructed the questions that related to the symptoms of sleep apnea. The self-administered question is helpful to identify
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Fig. 2 Gender differences in sleep apnea
Table 2 Summary of control and normal group from Berlin questionnaire (BQ)
Gender
Number Control
Normal
Female
14
17
9
10
Male
the differences between men and women, whom had sleep apnea. The segregation of three categories manifests the enhanced evaluation of sleep apnea. The threshold value for identifying control group and normal from out 50 participants is set as 5, where (p < 0.05) seem to have severe risk of sleep apnea. Qualitative results show that the 23 participants had sleep apnea, where 14 are female and remaining 9 are male participants. Followed by this qualitative study, the experimental study will be carried out as future research for objective detection of sleep apnea.
References 1. Varon, C., Caicedo, A., Testelmans, D., Buyse, B., Van Huffel, S.: A novel algorithm for the automatic detection of sleep apnea from a single-lead ECG. IEEE Trans. Biomed. Eng. 62(9), 2269–2278 (2015) 2. Javaheri, S., Barbe, F., Campos-Rodriguez, F., Dempsey, J.A., Khayat, R., Javaheri, S., Malhotra, A., Martinez-Garcia, M.A., Mehra, R., Pack, A.I., Polotsky, V.Y., Redline, S., Somers, V.K.: Sleep apnea types, mechanisms, and clinical cardiovascular consequences. J. Am. Coll. Cardiol. 69(7), 841–858 (2017) 3. Alencar, A.M., Vaz da Silva, D.G., Oliveira, C.B., Vieira, A.P., Moriya, H.T. and Lorenzi-Filho, G.: Dynamics of snoring sounds and its connection with obstructive sleep apnea. Physica A: Statistic. Mech. Appl. 392(1), 271–277 (2013)
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4. Chung, F., Subramanyam, R., Liao, P., Sasaki, E., Shapiro, C., Sun, Y.: High STOP-Bang score indicates a high probability of obstructive sleep apnoea. Br. J. Anesth. 108(5), 768–775 (2012) 5. Joseph, S., Costanzo, M.R.: A novel therapeutic approach for central sleep apnea: Phrenicnerve stimulation by the remede system. Int. J. Cardiol. 206, 28–34 (2016) 6. Rajeswari, J., Jagannath, M. and Adalarasu, K.: A review on detection and treatment methods of sleep apnea. J. Clin. Diag. Res. 11(3), VE01--VE03 (2017) 7. Martin, R.C.: Sleep apnea: state of the art. Trends Cardiovasc. Med. 27(4), 280–289 (2017) 8. Young, T., Palta, M., Dempsey, J., Skatrud, J., Weber, S.: The occurrence of sleep-disordered breathing among middle-aged adults. New Engl. J. Med. 328, 1230–1235 (1993) 9. Thurtell, M.J., Bruce, B.B., Rye, D.B., Newman, N.J., Biousse, V.: The Berlin questionnaire screens for obstructive sleep apnea in idiopathic intracranial hypertension. J. Neuroophthalmol. 31(4), 316–319 (2011) 10. Boisteanu, D., Vasiluta, R., Cernomaz, A. and Mucenica, C.: Home monitoring of sleep apnea treatment: benefits of intelligent CPAP devices. At-Equal 2009: Ecsis Symposium on Advanced Technologies for Enhanced Quality of Life: Lab-Rs and Artiped 2009, ed. A. Stoica, T. Arslan, T. Huntsberger, P. Botez, A.T. Erdogan, and A.O. ElRayis, 77–80 (2009)
Work-Related Musculoskeletal Disorders Among the Metal Craft Workers in Jaipur, India Dipayan Das, Awadhesh Bhardwaj, and Monica Sharma
Abstract The aim of the study was to investigate the prevalence of WMSDs and the association of different risk factors in the genesis of WMSDs among the metal craft manufacturing workers. 96 workers from five different metal craft manufacturing units in Jaipur were selected randomly. A questionnaire study was conducted, and RULA posture evaluation tool was used. Statistical analysis included Chi-square test for independence and calculation of odds ratio. The results showed that there is a high prevalence of WMSDs in the working group. The most affected body region is lower back. Factors such as age, daily working hours, prolonged sitting, uncomfortable working posture, lumbar support, lower arm support, repetitive hand movement and perceived work fatigue were found to be associated with WMSDs in one or more body regions. RULA score was high for the majority of the workers. The absence of proper workstation and high workload put the occupational health of the metal craft workers at risk of developing WMSDs. Keywords Metal craft · Wmsds · Risk factors · RULA
1 Introduction Work-related musculoskeletal disorders (WMSDs) are the painful disorders of muscle, ligaments, nerves, tendons, joints and soft tissues of the body often caused due to awkward working posture and repetitive movements. Constrained work posture and repetitive actions increase demand on the musculoskeletal system of the body. In long run, these lead to painful disorders. From the previous studies, it is well evident that these occupational disorders are highly associated with hand-intensive jobs [1, 2]. Metal artifacts manufacturing units are one of the widespread small-scale industries in India that play an important role in employment generation and economic growth of the country [3]. In India, Jaipur is one of the main artifact manufacturing D. Das (B) · A. Bhardwaj · M. Sharma Malaviya National Institute of Technology, Jaipur 302014, Rajasthan, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 M. Muzammil et al. (eds.), Ergonomics for Improved Productivity, Design Science and Innovation, https://doi.org/10.1007/978-981-15-9054-2_50
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clusters, famous for its rich tradition of metal work. These industries belong to the unorganized sector of the state. In the industry, the artisans are often forced to work for long period of time in non-optimal posture and engage in repetitive works. In long run, this may lead to the growth of musculoskeletal disorders (MSDs). Therefore, it would not be surprising if the metal craft manufacturing workers report musculoskeletal discomfort or pain in different body parts. However, these MSDs not only caused due to work-related factors, and psychosocial factors and worker individual factors also contribute to the occurrence of WMSDs. Since there are several factors that cause these disorders, it is difficult for researchers to understand the epidemiology. In available literature, several authors reported different potential factors for developing WMSDs in craft manufacturing workers [4, 5]. However, more information is needed to have valuable insight into the etiology of this serious problem. A successful investigation of risk factors would pave the way for future research to control different risk factors in the genesis of WMSDs. Hence, the present study aims to investigate the prevalence of WMSDs and to identify association of different worker individual, psychosocial and occupational factors in the genesis of WMSDs among the metal craft manufacturing workers.
2 Materials and Methods 2.1 Sample The present study was conducted based on the work of meenakari on metal artifacts, located in Jaipur, India. Ninety-six male workers from six different manufacturing units were selected randomly. All the selected subjects participated. Workers did not involve in other activities except meenakari was the only inclusion criteria for this study. The objectives of the study were explained, and signed informed consents were obtained from all participants.
2.2 Questionnaire Study For data collection, a questionnaire was prepared. In the first part of the questionnaire, questions related to gender, age, daily working hours, length of employment, marital status, the habit of smoking and drinking were collected. The second part included the modified Nordic musculoskeletal questionnaire [6]. In the final section of the questionnaire, information related to work-related factors such as nature of work, working posture, level of perceived work fatigue, lumbar support, lower arm support and repetitiveness of hand movement was collected.
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2.3 Evaluation of Working Posture For posture evaluation of the workers, rapid upper limb assessment (RULA) tool was used [7]. With the aid of digital photography, posture of each body part was investigated and scored on RULA sheet, and a final score that represented the level of MSD risk was obtained for all participants separately. In RULA sheet, the final score of 1–2 indicates negligible risk of MSD and no action required to change, the score of 3–4 represents low risk and change may be needed, score 5–6 denotes medium risk and recommends further investigation and change soon, score ≥7 indicates very high risk and recommends change now.
2.4 Statistical Analysis The statistical analysis was performed with the Statistical Package for Social Science (SPSS, version 22.0) software. For statistical analysis, all the study variables included in this study were dichotomized, except perceived work fatigue (low, moderate and high). To investigate the association of study variables with the development of WMSDs in the working group univariate analysis, chi-square test for independence was performed. Statistical analysis also included calculation of odds ratio with 95% confidence interval to measure the level of association.
3 Result 3.1 General Information of Sample Ninety-six male workers engaged in meenakari on metal crafts for at least one year participated in this study. The mean age of the participants was 29.47 years (SD = 5.81). The mean work experience of the workers was 7.6 years (SD = 5.38). The mean working hours per day was 7.7 h (SD = 1.5). Among the participants, 61.5% were married, 20.8% had a habit of smoking, and 21.9% had a drinking habit.
3.2 Prevalence of WMSDs Seventy workers had experienced discomfort or pain in one or more body parts in last 12 months. Descriptive statistics showed that the highest frequency of occurrence is accounted for lower back body region, while the least number of workers reported pain or feeling of discomfort in hips/thighs. Figure 1 shows the prevalence of WMSDs in different body regions.
Percentage
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70.83 60.42
64.58
55.21
52.08
25
21.88 14.58
18.75
Body region
Fig. 1 Annual prevalence of WMSDs
3.3 Association of Risk Factors In the current cross-sectional study, the workers who reported perceived discomfort in any body part were considered as the exposed group, and the counterpart was considered as control group. The results of the univariate chi-square test for independence are shown in Table 1.
3.4 RULA Scores Majority of the participants were right-handed (85.4% right-handed, 14.6% left handed). RULA score was obtained for the dominant side of their body. In the working group, the majority of the workers (64.6% right side, 57.1% left side) had final RULA score of 5–6. Figure 2 depicts the distribution of final RULA score.
4 Discussion The results of working posture evaluation revealed that the craftsmen often sustained awkward posture manifested by cross-leg sitting on the ground, arm flexed and neck and back forward inclined for long hours. Sustaining non-optimal posture for prolonging working hours increases demand on the muscles, ligaments and other soft tissues of the musculoskeletal system. It is evident that trunk and neck inclination increases forces on the cervical extensor muscle and the lumbar extensor muscle [8]. In long run, these cause early muscle fatigue and lead to perceived discomfort. In previous research, authors reported that sustaining prolong sitting in a forced nonneutral trunk posture and head or neck is the potential risk factors for low back pain
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Table 1 Association of risk factors Variables
χ2
OR
95% CI
Age