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Submit a ProposalDigital Manufacturing
 | Processes and Applications Edited by Sandip Kunar, Jagadeesha T. and Gurudas Mandal Series: Advances in Production Engineering Copyright: 2025 | Expected Pub Date:20025/08/30 ISBN: 9781394365340 | Hardcover | 664 pages |
One Line Description
Drive innovation and efficiency in your manufacturing processes with this comprehensive guide that explores the transformative impact of digital manufacturing technologies, from robotics to Industry 4.0.
Audience
Engineers, researchers, academics, and industry professionals invested in digital manufacturing technologies
Engineers, researchers, academics, and industry professionals invested in digital manufacturing technologies
Description
Digital manufacturing refers to the use of a computer-based system consisting of various tools and software for simulation, analytics, 3D visualization, and business and manufacturing collaboration. Often, these tools and software programs are cloud-based. They enable a manufacturer to connect and integrate manufacturing operations into a streamlined whole. With this centralized computer system, manufacturers have a seamless, connected flow of data related to all their processes and products. This comprehensive volume explores the transformative impact of digital technologies on the manufacturing industry. It delves into the core concepts of digital manufacturing, including automation, additive manufacturing, robotics, digital twins, and Industry 4.0. Covering both the theoretical foundations and practical applications of these technologies, this book provides a detailed understanding of how these technologies are reshaping production processes, improving efficiency, and driving innovation. It highlights the challenges and opportunities of adopting these advancements in the context of modern manufacturing environments. With real-world case studies and insights from industry experts, this book serves as an essential resource for professionals, students, and researchers aiming to understand and implement digital manufacturing solutions.
Readers will find the volume:
• Introduces technologies for successful improvement in advanced processes and applications of digital manufacturing;
• Explores recently developed digital manufacturing technologies;
• Discusses the successful fabrication of multipurpose digital manufacturing technologies, the sustainability of digital manufacturing technologies, and the future scope and challenges presented by digital manufacturing technologies.
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Digital manufacturing refers to the use of a computer-based system consisting of various tools and software for simulation, analytics, 3D visualization, and business and manufacturing collaboration. Often, these tools and software programs are cloud-based. They enable a manufacturer to connect and integrate manufacturing operations into a streamlined whole. With this centralized computer system, manufacturers have a seamless, connected flow of data related to all their processes and products. This comprehensive volume explores the transformative impact of digital technologies on the manufacturing industry. It delves into the core concepts of digital manufacturing, including automation, additive manufacturing, robotics, digital twins, and Industry 4.0. Covering both the theoretical foundations and practical applications of these technologies, this book provides a detailed understanding of how these technologies are reshaping production processes, improving efficiency, and driving innovation. It highlights the challenges and opportunities of adopting these advancements in the context of modern manufacturing environments. With real-world case studies and insights from industry experts, this book serves as an essential resource for professionals, students, and researchers aiming to understand and implement digital manufacturing solutions.
Readers will find the volume:
• Introduces technologies for successful improvement in advanced processes and applications of digital manufacturing;
• Explores recently developed digital manufacturing technologies;
• Discusses the successful fabrication of multipurpose digital manufacturing technologies, the sustainability of digital manufacturing technologies, and the future scope and challenges presented by digital manufacturing technologies.
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Author / Editor Details
Sandip Kunar, PhD, is an Associate Professor in the Department of Mechanical Engineering, Aditya Engineering College, Surampalem, Andhra Pradesh, India. He has published 12 books, 35 book chapters, one patent, and more than 50 research papers in reputed international journals and conferences. His research interests include non-conventional machining processes, micromachining processes, advanced manufacturing technology, and industrial engineering.
Sandip Kunar, PhD, is an Associate Professor in the Department of Mechanical Engineering, Aditya Engineering College, Surampalem, Andhra Pradesh, India. He has published 12 books, 35 book chapters, one patent, and more than 50 research papers in reputed international journals and conferences. His research interests include non-conventional machining processes, micromachining processes, advanced manufacturing technology, and industrial engineering.
Jagadeesha T., PhD is an Associate Professor in the Mechanical Engineering Department at the National Institute of Technology Calicut, Kerala, India with more than 25 years of experience. He has published seven textbooks, four patents, and more than 75 articles in international journals and conferences. His research interests include advanced machining, additive manufacturing, fluid power control, advanced materials, and vibration and noise control.
Gurudas Mandal, PhD is an Assistant Professor in the Department of Metallurgical Engineering at Kazi Nazrul University, West Bengal, India. He has published nine book chapters, one patent, and more than 20 articles in international journals and conferences. His research focus is on alloy steel and cast iron, composite materials, magnetic materials, hydrogen energy, and archaeometallurgy.
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Table of Contents
Preface
Acknowledgement
Part I: Overview
1. Introduction to Digital Manufacturing System
Sandip Kunar and Gurudas Mandal
1.1 Introduction
1.2 Manufacturing as Craft and Technique
1.3 Manufacturing Becoming a Science
1.3.1 Engineering Science in Manufacturing
1.3.2 Organizational Science in Manufacturing
1.3.3 Multi-Crossed Disciplines in Manufacturing
1.4 Concepts and Research and Development Status of Digital Manufacturing
1.5 Definition of Digital Manufacturing
1.5.1 Digital Manufacturing Concept Used as Control
1.5.2 Digital Manufacturing Concept Used as Design
1.5.3 Digital Manufacturing Concept Used as Management
1.5.4 Digital Manufacturing Concept Used as Manufacturing
1.6 Features and Developments of Digital Manufacturing
1.7 Digital Manufacturing Science: Significance and Research Approach
1.7.1 Fundamental Idea and Significance
1.7.2 Research Aspects
1.8 Conclusion
References
2. Industrial Production through the Ages: A Historical Analysis and Forecast
Sameeha Khan, Juveiria Khan, Abdul Ahad, Zehra Fatima and Faisal Talib
2.1 Introduction
2.1.1 Industry 1.0 (1740–1840): Mechanization
2.1.1.1 Technological Advancements Leading to Industrial Revolution
2.1.1.2 Technological Advancements during the Industrial Revolution
2.1.2 Industry 2.0: Electrification
2.1.2.1 Steel, Electricity, and Chemical Innovations
2.1.2.2 Transportation and Communication Progress
2.1.3 Industry 3.0: Automation and Globalization
2.1.3.1 3D Printing
2.1.3.2 Robotics
2.1.4 Industry 4.0: Personalization
2.1.4.1 Key Technologies and Concepts
2.1.4.2 4D Printing
2.1.5 Industry 5.0: Humanization
2.2 Industrial Production
2.2.1 Manufacturing Systems
2.2.1.1 Lean Manufacturing
2.2.1.2 Agile Manufacturing
2.2.1.3 Green Manufacturing
2.2.1.4 Sustainable Manufacturing
2.3 Discussion
2.4 Conclusion
References
3. Technology Management in Digital Manufacturing Science
D.V.S.S.S.V. Prasad, M. Sreenivasa Reddy and A. Ramesh
3.1 Introduction
3.1.1 Overview of Digital Manufacturing
3.1.2 Importance of Technology Management in Manufacturing
3.2 Technological Landscape of Digital Manufacturing
3.2.1 Core Technologies in Digital Manufacturing
3.2.2 Emerging Trends
3.2.3 Challenges in Adopting Digital Manufacturing Technologies
3.3 Strategic Management of Technology
3.3.1 Technology Strategy Development
3.3.2 Technology Forecasting and Road-Mapping
3.3.3 Innovation Management
3.4 Operational Management of Digital Manufacturing Technologies
3.4.1 Digital Transformation and Change Management
3.4.2 Resource Allocation and Investment
3.4.3 Supply Chain Integration
3.5 Technology Integration and Interoperability
3.5.1 System Integration Challenges
3.5.2 Data Management and Analytics
3.5.3 Role of AI and ML in Optimizing Operations
3.5.4 Cybersecurity Considerations in Digital Manufacturing
3.6 Human Capital and Skills Management
3.6.1 Workforce Transformation
3.6.2 Collaborative Human-Robot Workflows
3.6.3 Leadership and Organizational Structure
3.7 Case Studies and Best Practices
3.7.1 Successful Examples of Technology Management
3.7.2 Benchmarking Best Practices
3.7.3 Successful Strategies for Digital Manufacturing Implementation
3.8 Conclusion and Future Directions
3.8.1 Conclusion
3.8.2 Future Directions
References
4. Design Methodologies and Approaches in Traditional and Additive Manufacturing Systems: A Comparative Study
Noor Yamshi, Fiza Siddiqui, Sabih Ahmad Khan and Faisal Talib
4.1 Introduction
4.1.1 Background
4.1.2 Problem Statement
4.1.3 Concern toward AM
4.1.4 Current Status
4.1.5 Objectives
4.2 Conventional Manufacturing Design Methodologies
4.2.1 Overview of Conventional Manufacturing
4.2.2 Design for Manufacturability
4.2.3 Key Design Considerations
4.2.4 Case Studies
4.3 AM Design Methodologies
4.3.1 Overview of AM
4.3.2 Different Types of AM
4.4 Comparative Analysis of Design Methodologies
4.4.1 Design Flexibility
4.4.2 Cost and Time Efficiency
4.4.3 Material Usage and Sustainability
4.4.4 Quality and Performance
4.5 Challenges and Limitations
4.6 Future Trends and Opportunities
4.6.1 Industry 4.0
4.6.2 Hybrid Manufacturing
4.7 Conclusions
References
5. Simulation and Process Optimization in Wire Arc Additive Manufacturing: A Review
Ajithkumar Sitharaj, Arulmurugan B., M.D. Barath Kumar, Ganesh N., Dharani Kumar S. and Gokulkumar S.
5.1 Introduction
5.2 Heat Source Modeling for Numerical Simulation in WAAM
5.2.1 Gaussian Distribution Heat Source Model
5.2.2 Double Ellipsoidal Heat Source (Goldak’s Model)
5.2.3 Conical Heat Source Model
5.2.4 Parameters Influencing the Heat Source Model in Numerical Simulations
5.2.5 Dynamic Heat Source Coupling in WAAM
5.2.6 Impact of Process Parameters on the Heat Source Model
5.2.7 Influence of Shielding Gas Composition on the Heat Source Model
5.3 Thermal and Mechanical Analysis in FEA for WAAM
5.3.1 Temperature Distribution
5.3.2 Cooling Rate
5.3.3 Heat Input
5.3.4 Anisotropy
5.3.5 Residual Stress and Distortion
5.4 Future Scope
5.5 Conclusion
References
6. The Role of Polymer Materials and Their Properties in Shaping the Future of Additive Manufacturing
Ganesh Nataraj, Ramesh Babu S., Ramu Murugan, Senthil Kumar A.P. and Ajithkumar Sitharaj
6.1 Introduction
6.2 Types of Polymer Materials Used in AM
6.2.1 Thermoplastics
6.2.2 Thermosetting Polymers
6.2.3 Composite Materials
6.3 Material Properties and Their Influence on AM
6.3.1 Mechanical Properties (Tensile Strength, Flexibility, Impact Resistance)
6.3.2 Thermal Properties (Heat Resistance, Melting Points, Thermal Expansion)
6.3.3 Chemical Resistance and Stability
6.3.4 Surface Finish and Printability
6.4 Processing Techniques in Polymer AM
6.4.1 Fused Deposition Modeling
6.4.2 Stereolithography
6.4.3 Selective Laser Sintering
6.4.4 Material Jetting
6.4.5 Direct Ink Writing
6.5 Design Considerations for Polymer AM
6.6 Advanced Polymer Materials for AM
6.6.1 Biodegradable Polymers
6.6.2 High-Performance Polymers
6.6.3 Elastomeric Polymers
6.6.4 Conductive Polymers
6.7 Applications of Polymer Materials in AM
6.7.1 Aerospace and Automotive
6.7.2 Medical and Healthcare
6.7.3 Consumer Goods
6.7.4 Fashion and Textiles
6.8 Challenges and Limitations
6.9 Future Trends in Polymer Materials for AM
6.10 Conclusion
References
7. Metal Additive Manufacturing
Nebechi Kate Obiora, Chika Oliver Ujah, Sandip Kunar, Peter Apata Olubambi and Daramy Vandi Von Kallon
7.1 Introduction
7.1.1 Historical Trend for AM
7.1.2 Classifications of AM
7.1.2.1 Material Extrusion
7.1.2.2 Powder Bed Fusion
7.1.2.3 VAT Polymerization
7.1.2.4 Binder Jetting
7.1.2.5 Material Jetting
7.1.2.6 Lamination of Sheets
7.1.2.7 Directed Energy Deposition
7.2 Basic Principles of MAM
7.2.1 Process Flow of AM
7.2.2 Properties of Metal Powders Used in MAM
7.2.3 Metal Solidification in MAM
7.3 MAM Processes
7.3.1 Pretreatment
7.3.2 Manufacturing
7.3.2.1 Solid Process
7.3.2.2 Liquid Process
7.3.3 Post-Treatment
7.3.3.1 Hot Isostatic Pressing
7.3.3.2 Heat Treatment
7.3.3.3 Surface Treatments
7.3.3.4 Friction Stir Engineering
7.4 Metals Used in AM
7.4.1 Alloys
7.4.2 Pure Metals
7.4.3 Precious Metals
7.4.4 MAM Applications
7.5 Recent Advances and Future Outlook
7.6 Conclusion and Recommendation
7.7 Recommendations
Acknowledgement
References
8. Advancement in Materials for Functional Three-Dimensional Printing
Arhaan Nawab, Waquar Alam, Wasim Alam, Mohd. Hamza and Faisal Talib
8.1 Introduction
8.2 Materials and Methods
8.2.1 Introduction to Material Innovation
8.2.2 Polymers
8.2.3 Metals
8.2.4 Composite Materials
8.2.5 Biomaterials
8.2.6 Smart Materials
8.2.7 Self-Healing Materials
8.2.8 Multi-Materials for Additive Manufacturing
8.2.9 Shape Memory Material
8.3 Applications of Materials
8.4 Conclusions
8.4.1 Future Research Directions
References
9. Cross-Country Comparative Analysis of Digital Manufacturing Systems
Sunita Routray, Rudra Narayan Mohapatro and Ranjita Swain
9.1 Introduction
9.1.1 Additive Manufacturing
9.1.1.1 WAAM Digital Techniques
9.1.1.2 SLA Digital Techniques
9.1.1.3 FDM Digital Techniques
9.1.1.4 LPBF Digital Techniques
9.1.1.5 Cyber-Physical Production Digital System
9.2 Digital Technological Review for the Manufacturing Process
9.3 Cross-Country Comparative Analysis of DMS
9.3.1 How India is Embracing DMS
9.3.2 About Digital Twin Technology
9.3.2.1 Importance of Digital Twin Technology in India
9.3.2.2 Types of Digital Twin Technology
9.3.2.3 Opportunities for Digital Twin Technology in India
9.3.3 Challenges in Implementing Digital Twin Technology in India
9.3.4 Implementation of Digital Twin Technology by Industries in India
9.3.5 Future of Digital Twin Technology in India
9.3.6 Impact of Digital Technologies in Developed Countries
9.3.7 Dark Side of DMS
9.4 Advances in DMS in Today’s World
9.4.1 Digitalization’s Role in SMEs and Innovation
9.4.2 AR in Manufacturing
9.4.3 DT and Sustainability
9.4.4 DT for SMEs
9.4.5 Collaborative Robots in Automotive Production
9.4.6 Mass Customization in Industry 4.0
9.4.7 Digital Twin Technology Across Industries
9.4.8 Digital Manufacturing and Cost Management
9.5 Future Prospects in the Manufacturing Industry
9.5.1 DT and SME Innovation
9.5.2 Digitalization’s Role in Sustainable Manufacturing
9.5.3 Advancements in AM
9.5.4 Globalization and the Fourth Industrial Revolution
9.5.5 Cloud Computing in Manufacturing
9.5.6 CPS and Industry 4.0
9.5.7 The Convergence of Digital, Built, and Natural Environments
9.5.8 Educational Challenges in Smart Manufacturing
9.5.9 Future Directions in Digital Manufacturing
9.6 Conclusion
References
10. A Review and Analysis from Industry 4.0 Toward Industry 5.0
Sandip Kunar, Jagadeesha T., Chika Oliver Ujah, Norfazillah Talib, Gurudas Mandal, K. Nagasuresh, N. Naresh, S. Rama Sree and M. Sreenivas Reddy
10.1 Introduction
10.2 Historical Overview
10.3 Basic Driving Concepts of Industry 4.0 and Industry 5.0
10.4 Review of Key Enablers in Practical Context of Industry 4.0 and Industry 5.0
10.4.1 Toward Human-Centricity
10.4.2 Toward Sustainability
10.4.3 Toward Resilience
10.5 Discussion
10.6 Are We Fear of Technology? The Role of Regulations
10.7 Controlling AI
10.8 Conclusions
10.9 The Future
References
11. Envisioning Industry 4.0: A Review
Sumanta Banerjee and Anindita Kundu
11.1 Introduction and Background
11.2 Changes and Transformation of Manufacturing Ecosystems: A Review
11.3 Smart Manufacturing Systems: Role of AI, IoT, and Big Data
11.3.1 Artificial Intelligence
11.3.2 Smart Manufacturing Systems
11.4 Intelligent Factories
11.5 The Fourth Industrial Revolution (Industry 4.0)
11.6 Industry 3.0 to Industry 4.0: Mapping the Transformation
11.7 Impact of Industry 4.0: Technological Inference
11.8 Impact of Industry 4.0: Socio-Cultural Impacts
11.9 Impact of Industry 4.0: Business Prospects
11.10 Conclusions and Present/Futuristic Trends
References
12. Future Development of Digital Manufacturing Science
Alok Kumar and Sachin Kumar
12.1 Introduction
12.2 Conventional Methodology of the DMS Process
12.2.1 Driving Forces
12.2.2 Manufacturing of SM
12.2.3 Additive Manufacturing
12.3 The Electrical Mechanical (Elec-Mech) System with DMS
12.3.1 Micro Elec-Mech System (MEMS) and Nano Elec-Mech System (NEMS)
12.3.2 MEMS and NEMS with DMS
12.3.3 Micro Nano Equipment of the System
12.3.4 Micro-Nano Manufacturing with DMS Technology
12.4 The Externalization of DMS
12.4.1 Extreme Manufacturing
12.4.2 Elec-Mech System Modeling
12.4.3 Elec-Mech Systems in Ecological Systems
12.5 The Environmental Protection of DMS
12.5.1 The Implementation of Ecology Protection
12.5.2 Conscious Ecological Manufacturing
12.5.2.1 The Overview of Environmentally Conscious Manufacturing
12.5.2.2 Research Content of ECM System
12.5.2.3 Digital Ecological Product Manufacturing (EPM) System
12.5.3 Overview of Re-Engineering of Product Manufacturing
12.5.3.1 The Key Technology Re-EPM
12.5.3.2 DM Technology in Re-EPM
12.6 Applications of DMS
12.6.1 Automobile Sectors
12.6.2 Defense and Aerospace Sectors
12.6.3 Medical Sectors
12.6.4 Food Sectors
12.6.5 Construction Sectors
12.7 Conclusion
References
Part II: Computing Applications
13. Computing Manufacturing in Digital Manufacturing Science
Dasari Madhusudhan, Rupa Srivani and Keerthi Prabhavathi
13.1 Introduction
13.1.1 Digital Manufacturing and Its Significance
13.1.2 Role of Computing in Advancing Manufacturing Processes
13.1.3 Integration of Physical and Digital Components
13.1.4 Impact of Computing on Efficiency, Quality, and Innovation in Manufacturing
13.1.5 Challenges in Digital Manufacturing
13.1.6 Computing Transformed Manufacturing Processes
13.1.7 Key Computing Technologies Used in Digital Manufacturing
13.2 Theoretical Foundations of Computing in Manufacturing
13.2.1 Computing in Manufacturing
13.2.2 Digital Manufacturing Science and Its Components
13.2.3 Evolution of Computing in Manufacturing
13.2.4 Core Computing Concepts in Manufacturing
13.3 Mathematical Methods
13.3.1 Geometric Modelling
13.3.2 Finite Element Analysis (FEA)
13.3.3 Optimization Methods
13.3.4 Computational Fluid Dynamics (CFD)
13.3.5 ML and AI
13.3.6 Statistical Process Control
13.3.7 Operations Research and Supply Chain Optimization
13.4 Key Computing Technologies in Manufacturing
13.4.1 Computer-Aided Design and Engineering
13.4.2 Computer-Aided Manufacturing
13.4.3 Simulation and Modelling
13.4.4 AI and ML
13.4.5 Big Data and Analytics
13.4.6 Cloud Computing
13.5 Applications of Computing in Digital Manufacturing
13.5.1 Smart Factories and Industry 4.0
13.5.2 Additive Manufacturing and 3D Printing
13.5.3 Supply Chain Optimization
13.5.4 Robotics and Automation
13.5.5 Benefits and Challenges of Computing in Manufacturing
13.6 Case Studies
13.6.1 Siemens’ Use of AI and Simulation in Manufacturing
13.6.2 General Electric’s Digital Twin Technology
13.6.3 Tesla’s Smart Manufacturing System
13.6.4 Boeing’s Use of Computational Tools in Aerospace Manufacturing
13.7 Discussion and Analysis
13.7.1 Comparative Analysis of Case Studies
13.7.2 Quantitative and Qualitative Approaches
13.7.3 Impact of Computing on Manufacturing Efficiency
13.7.4 Future Trends in Computing for Manufacturing
13.7.5 Ethical and Policy Considerations
13.8 Conclusion
13.9 Implications for Industry
13.10 Suggestions for Future Research
References
14. Unlocking the Potential of Intelligent Manufacturing Guide to Digital Manufacturing
Adnan Zafar, Imad Ur Rehman, Jamal Abdullah Haider and Faisal Talib
14.1 Introduction
14.1.1 Overview of Digital Manufacturing
14.1.2 Introduction to Intelligent Manufacturing
14.2 Progression of Manufacturing Innovations
14.2.1 Various Technologies of Intelligent Manufacturing
14.3 Case Studies
14.3.1 Case Study of Hero MotoCorp
14.3.2 Case Study of Tesla
14.3.3 Case Study of Siemens
14.4 Challenges and Barriers
14.5 Conclusion
14.5.1 Implications
14.5.2 Future Research Opportunities
References
15. Bionic Manufacturing in Digital Manufacturing Science
Debjani Bhakta, Jyoti Bhattacharjee and Subhasis Roy
15.1 Introduction
15.1.1 Bionic Needs
15.1.2 Bionic Models
15.1.3 Bionic Simulations
15.1.4 Bionic Products
15.2 Digital Technologies Used for Bionic Manufacturing
15.2.1 Artificial Intelligence (AI) and Machine Learning
15.2.2 Simulation and Modelling
15.2.3 Internet of Things (IoT)
15.3 Applications of Bionic Manufacturing
15.3.1 Robot Fish
15.3.2 Bionic Shark Skin
15.3.3 Aircraft and Aerospace
15.3.4 Medical Field
15.3.5 Textile Industry
15.4 Applications of Bionic Manufacturing in Digital Manufacturing Science
15.4.1 Bionic Structures in Aerospace Manufacturing
15.4.2 Bionic Manufacturing in Architecture
15.4.3 Bionic Additive Manufacturing in Consumable Products
15.4.4 Bionic Manufacturing in the Auto Industries
15.4.5 Biomimetic Robotics and Automation
15.4.6 Bionic Agriculture and Food Production
15.4.7 Bionic Packaging Solutions
15.4.8 Bionic Energy Solutions
15.4.9 Bionic Marine and Underwater Engineering
15.4.10 Bionic Manufacturing in Electronics
15.4.11 Bionic Defense and Security Applications
15.4.12 Bionic Innovations in Environmental Restoration
15.4.13 Nature-Inspired Pollution Control
15.5 Challenges and Future Directions
15.5.1 Complexity in Design and Engineering
15.5.2 Drawbacks and Compatibility with Materials
15.5.3 Synthesis of Interdisciplinary
15.5.4 Scaling and Commercialization Issues
15.5.5 High Technology Manufacturing Expense
15.5.6 The Lack of Standardization in Bionic Systems
15.5.7 Ethical and Regulatory Issues
15.6 Case Studies
15.6.1 Nature-Inspired Bionic Design
15.6.2 Bionic Structures for Lightweight Designs
15.6.3 Bionic Soft Robotics by Digital Techniques
15.6.4 Bionic Manufacturing in Biomedical Engineering
15.6.5 Digital Manufacturing of Bionic Exoskeletons
15.6.6 Case Study Production of Digital Design and Manufacturing Customized Exoskeletons for Rehabilitation
15.6.7 BionicANTs by Festo
15.6.8 Octopus-Inspired Soft Robotics in Assembly Lines
15.6.9 Spider-Inspired Agricultural Robots
15.6.10 Bionic Fish and Industrial Fluid Systems
15.6.11 Bionic Arm in Logistics
15.7 Conclusions
Acknowledgement
References
16. Direct Digital Manufacturing for Biomedical Applications: Toward Efficient Healthcare
Amey Dukle and M. Ravi Sankar
16.1 Introduction
16.2 Technological Foundations of DDM for Biomedical Applications
16.2.1 The Design Process in DDM for Personalized Implants
16.2.1.1 Data Acquisition Methods
16.2.1.2 CAD Model Creation
16.2.2 Materials Utilized in DDM for Biomedical Applications
16.2.2.1 Polymers
16.2.2.2 Metals
16.2.2.3 Ceramics
16.2.2.4 Composite Materials
16.2.3 Technologies for DDM
16.2.3.1 Direct Ink Writing
16.2.3.2 Stereolithography
16.2.3.3 Fused Deposition Modelling
16.2.3.4 Selective Laser Sintering
16.2.3.5 3D Bioprinting
16.3 Application of DDM for Biomedical Applications
16.3.1 Tissue Engineering
16.3.2 Custom Implants and Prosthetics Production
16.3.3 Surgical Planning and Training
16.4 Challenges in Adoption of DDM for Biomedical Applications
16.4.1 Acceptance from Medical Professionals
16.4.2 Regulatory Challenges
16.5 Conclusion and Future Outlook
References
17. Digital Manufacturing and the Fifth Industrial Revolution
Alok Kumar and Ravi Shankar Rai
17.1 Digital Manufacturing
17.1.1 Integration Technology of DM
17.1.2 Information Technology in Manufacturing
17.1.3 Computer-Aided Design-Based Technologies
17.1.4 Manufacturing-Based Control
17.1.5 Software-Based Simulation
17.1.6 Enterprise Resource Planning (ERP)
17.2 Development of Industrial Revolutions
17.2.1 Background
17.2.2 The First IR (Industry 1.0)
17.2.3 The Second IR (Industry 2.0)
17.2.4 The Third IR (Industry 3.0)
17.2.5 The Fourth IR (Industry 4.0)
17.2.6 The Fifth IR (Industry 5.0)
17.3 Uses of Digital Manufacturing
17.3.1 Continuous Upgrade of DM Systems
17.3.2 Modification Using DM Systems
17.3.3 Safety Enhancement in the DM Process
17.3.4 Predictive Maintenance in DM
17.3.5 Manufacturing Data Collection
17.4 Characterizing Industry 5.0
17.4.1 Need for Industry 5.0
17.4.2 Solution-Based Methodology
17.4.2.1 Online Instruction
17.4.2.2 Self-Sustained Systems with AI
17.4.2.3 Implementation of ML with Sensor Technologies
17.4.3 Manufacturing System Affected by Industry 5.0
17.5 Applications of DM Sectors
17.5.1 Aeronautical Sector
17.5.2 Automotive Sector
17.5.3 The Renewable Energy-Based Sector
17.5.4 The Telecom Sector
17.6 Conclusion
References
18. Factories of the Future: Digital Manufacturing in the Manufacturing Industry
Rasu Karunanithi, Mohammed Abdur Rahman and Gopal Rajesh
18.1 Introduction
18.2 Advanced Technologies Used in Digital Manufacturing
18.2.1 Industry 4.0 and IoT
18.2.2 Significance for Prototyping, Production, and Customization
18.2.3 Production
18.2.4 Customization
18.2.5 Artificial Intelligence and Machine Learning
18.2.6 AI-Driven Analytics
18.2.7 Predictive Maintenance
18.2.8 Robotics and Automation
18.2.9 Digital Twins: The Ability to Construct “Virtual Twins” Using Holography Technology to Simulate and Optimize
18.2.10 Optimization and Predictive Maintenance
18.2.11 Big Data and Analytics
18.2.12 Cybersecurity in Manufacturing: Protecting Digital Manufacturing Enterprises
18.2.13 The Impact of Digital Manufacturing
18.2.14 Customization and Flexibility
18.2.15 Mass Customization
18.2.16 Sustainability
18.3 Workforce Transformation: Skills Needed for Managing and Operating Digital Manufacturing Systems
18.4 Case Studies
18.4.1 Siemens
18.4.2 General Electric (GE)
18.4.3 Bosch
18.4.4 Tesla
18.4.5 Siemens Gamesa
18.4.6 Daimler AG (Mercedes-Benz)
18.5 Challenges and Barriers to Adoption
18.5.1 Upfront Capital Investment
18.5.2 ROI Uncertainty
18.5.3 Operational Disruptions during Implementation
18.6 Cost of Technology Upgrades and Maintenance
18.7 Conclusion
References
19. Business Models for Additive Manufacturing: A Consulting Services Perspective
Yogeshwaran Kumarasamy, Prases Kumar Mohanty and Shubhajit Das
19.1 Introduction
19.2 Business Background
19.3 Importance of Business Model
19.4 Business Models for Consulting Services
19.4.1 Firm Model
19.4.2 Independent Model
19.4.3 Productized Model
19.5 Requirements for Consulting Services
19.5.1 Collaborations and Partnerships
19.5.2 Core Activities
19.5.3 Key Expedient
19.5.4 Value Scheme
19.5.5 Client Engagement
19.5.6 Customer Niche
19.5.7 Marketing
19.6 Opportunities in Various Segments
19.6.1 Parts Designing for Additive Manufacturing
19.6.2 Training for Additive Manufacturing
19.6.3 At Aerospace, Automotive, Defense, and Tooling
19.6.4 At Construction
19.6.5 At Medical
19.7 Challenges in Additive Manufacturing for Consulting Service
19.8 Conclusion
References
20. Integration of Additive Manufacturing with Digital Technologies for Future Manufacturing
Ganesh Nataraj, Ramesh Babu S., Ramu Murugan, Senthil Kumar A.P. and Ajithkumar Sitharaj
20.1 Introduction
20.2 Understanding Additive Manufacturing
20.3 The Intersection of Additive Manufacturing and Digital Transformation
20.4 Impact of Additive Manufacturing on Supply Chains
20.4.1 Decentralization and On-Demand Production Enabled by AM
20.4.2 Reducing Lead Times and Inventory Costs
20.4.3 Enhancing Supply Chain Resilience and Flexibility Through Digital Networks
20.5 Sustainability in Additive Manufacturing
20.6 Customization and Personalization in Digital Manufacturing
20.7 Challenges and Opportunities
20.7.1 Technical and Economic Challenges in Integrating AM into Existing Workflows
20.7.2 Regulatory and Standardization Issues in Digital Manufacturing
20.7.3 Opportunities for Innovation and Growth in AM Through Digital Transformation
20.8 Future Trends in Additive Manufacturing and Digital Transformation
20.8.1 Emerging Technologies and Materials in AM
20.8.2 The Convergence of AM with Other Industry 4.0 Technologies (e.g., AI, Robotics, Big Data)
20.8.3 Predictions for the Future Impact of AM on Global Manufacturing
20.9 Conclusion
References
21. Computational Approaches to Advanced Digital Manufacturing Practices
D.V.S.S.S.V. Prasad, Akhilesh Kumar Singh, Marxim Rahula Bharathi. B., Yarrapragada K.S.S. Rao and V.V. Kamesh
21.1 Introduction
21.1.1 Overview of Digital Manufacturing Science
21.1.2 Importance of Computing in Modern Manufacturing
21.1.3 Purpose and Scope of the Chapter
21.2 Foundations of Digital Manufacturing
21.2.1 Definition and Evolution of Digital Manufacturing
21.2.2 Key Technologies and Concepts
21.2.2.1 Computer-Aided Design (CAD)
21.2.2.2 Computer-Aided Manufacturing (CAM)
21.2.2.3 Digital Twins
21.2.2.4 Simulation and Modelling
21.3 Overview of Computational Models in Manufacturing
21.3.1 Overview of Computational Models
21.3.2 Types of Computational Models Used in Manufacturing
21.3.2.1 Finite Element Analysis (FEA)
21.3.2.2 Computational Fluid Dynamics (CFD)
21.3.2.3 Multi-Body Dynamics (MBD)
21.3.3 Case Studies and Examples
21.4 Data Management and Analytics
21.4.1 Role of Data in Digital Manufacturing
21.4.2 Data Acquisition and Integration
21.4.3 Data Analytics Techniques
21.4.3.1 Statistical Analysis
21.4.3.2 Machine Learning and AI
21.4.4 Examples of Data-Driven Decision-Making
21.5 Software and Tools
21.5.1 Overview of Key Software Tools
21.5.1.1 CAD Software
21.5.1.2 CAM Software
21.5.1.3 Simulation Software
21.5.2 Integration of Tools and Systems
21.5.3 Emerging Software Trends and Innovations
21.6 Computing Architectures and Systems
21.6.1 High-Performance Computing (HPC) in Manufacturing
21.6.2 Cloud Computing and Its Impact
21.6.3 Edge Computing in Manufacturing Contexts
21.6.4 Examples of Computing Systems in Use
21.7 Challenges and Limitations
21.7.1 Computational Complexity and Resource Constraints
21.7.1.1 Understanding Computational Complexity
21.7.1.2 Data Security and Privacy Issues
21.7.1.3 Integration Challenges
21.7.2 Case Studies of Common Challenges
21.7.2.1 Food and Beverage Industry: Compliance and Safety
21.7.2.2 Electronics Manufacturing: Supply Chain Disruptions
21.7.2.3 Pharmaceutical Industry: Data Integrity Issues
21.8 Future Trends and Innovations
21.8.1 Advancements in Computing Technologies
21.8.1.1 Enhanced Computational Power
21.8.1.2 Innovations in Hardware
21.8.2 The Role of Quantum Computing
21.8.2.1 What is Quantum Computing?
21.8.2.2 Potential Applications in Manufacturing
21.8.3 Current Developments
21.8.3.1 AI and Machine Learning Advancements
21.8.4 Future Trends in Digital Manufacturing and their Implications
21.8.4.1 Digital Twins and Virtual Prototyping
21.8.4.2 Sustainable Manufacturing
21.8.4.3 Personalized Manufacturing
21.8.4.4 Implications for Workforce and Skills
21.9 Conclusion
21.9.1 Summary of Key Points
21.9.2 The Impact of Computing on the Future of Manufacturing
21.9.3 Final Thoughts and Recommendations for Practitioners
References
Index
Back to Top
Preface
Acknowledgement
Part I: Overview
1. Introduction to Digital Manufacturing System
Sandip Kunar and Gurudas Mandal
1.1 Introduction
1.2 Manufacturing as Craft and Technique
1.3 Manufacturing Becoming a Science
1.3.1 Engineering Science in Manufacturing
1.3.2 Organizational Science in Manufacturing
1.3.3 Multi-Crossed Disciplines in Manufacturing
1.4 Concepts and Research and Development Status of Digital Manufacturing
1.5 Definition of Digital Manufacturing
1.5.1 Digital Manufacturing Concept Used as Control
1.5.2 Digital Manufacturing Concept Used as Design
1.5.3 Digital Manufacturing Concept Used as Management
1.5.4 Digital Manufacturing Concept Used as Manufacturing
1.6 Features and Developments of Digital Manufacturing
1.7 Digital Manufacturing Science: Significance and Research Approach
1.7.1 Fundamental Idea and Significance
1.7.2 Research Aspects
1.8 Conclusion
References
2. Industrial Production through the Ages: A Historical Analysis and Forecast
Sameeha Khan, Juveiria Khan, Abdul Ahad, Zehra Fatima and Faisal Talib
2.1 Introduction
2.1.1 Industry 1.0 (1740–1840): Mechanization
2.1.1.1 Technological Advancements Leading to Industrial Revolution
2.1.1.2 Technological Advancements during the Industrial Revolution
2.1.2 Industry 2.0: Electrification
2.1.2.1 Steel, Electricity, and Chemical Innovations
2.1.2.2 Transportation and Communication Progress
2.1.3 Industry 3.0: Automation and Globalization
2.1.3.1 3D Printing
2.1.3.2 Robotics
2.1.4 Industry 4.0: Personalization
2.1.4.1 Key Technologies and Concepts
2.1.4.2 4D Printing
2.1.5 Industry 5.0: Humanization
2.2 Industrial Production
2.2.1 Manufacturing Systems
2.2.1.1 Lean Manufacturing
2.2.1.2 Agile Manufacturing
2.2.1.3 Green Manufacturing
2.2.1.4 Sustainable Manufacturing
2.3 Discussion
2.4 Conclusion
References
3. Technology Management in Digital Manufacturing Science
D.V.S.S.S.V. Prasad, M. Sreenivasa Reddy and A. Ramesh
3.1 Introduction
3.1.1 Overview of Digital Manufacturing
3.1.2 Importance of Technology Management in Manufacturing
3.2 Technological Landscape of Digital Manufacturing
3.2.1 Core Technologies in Digital Manufacturing
3.2.2 Emerging Trends
3.2.3 Challenges in Adopting Digital Manufacturing Technologies
3.3 Strategic Management of Technology
3.3.1 Technology Strategy Development
3.3.2 Technology Forecasting and Road-Mapping
3.3.3 Innovation Management
3.4 Operational Management of Digital Manufacturing Technologies
3.4.1 Digital Transformation and Change Management
3.4.2 Resource Allocation and Investment
3.4.3 Supply Chain Integration
3.5 Technology Integration and Interoperability
3.5.1 System Integration Challenges
3.5.2 Data Management and Analytics
3.5.3 Role of AI and ML in Optimizing Operations
3.5.4 Cybersecurity Considerations in Digital Manufacturing
3.6 Human Capital and Skills Management
3.6.1 Workforce Transformation
3.6.2 Collaborative Human-Robot Workflows
3.6.3 Leadership and Organizational Structure
3.7 Case Studies and Best Practices
3.7.1 Successful Examples of Technology Management
3.7.2 Benchmarking Best Practices
3.7.3 Successful Strategies for Digital Manufacturing Implementation
3.8 Conclusion and Future Directions
3.8.1 Conclusion
3.8.2 Future Directions
References
4. Design Methodologies and Approaches in Traditional and Additive Manufacturing Systems: A Comparative Study
Noor Yamshi, Fiza Siddiqui, Sabih Ahmad Khan and Faisal Talib
4.1 Introduction
4.1.1 Background
4.1.2 Problem Statement
4.1.3 Concern toward AM
4.1.4 Current Status
4.1.5 Objectives
4.2 Conventional Manufacturing Design Methodologies
4.2.1 Overview of Conventional Manufacturing
4.2.2 Design for Manufacturability
4.2.3 Key Design Considerations
4.2.4 Case Studies
4.3 AM Design Methodologies
4.3.1 Overview of AM
4.3.2 Different Types of AM
4.4 Comparative Analysis of Design Methodologies
4.4.1 Design Flexibility
4.4.2 Cost and Time Efficiency
4.4.3 Material Usage and Sustainability
4.4.4 Quality and Performance
4.5 Challenges and Limitations
4.6 Future Trends and Opportunities
4.6.1 Industry 4.0
4.6.2 Hybrid Manufacturing
4.7 Conclusions
References
5. Simulation and Process Optimization in Wire Arc Additive Manufacturing: A Review
Ajithkumar Sitharaj, Arulmurugan B., M.D. Barath Kumar, Ganesh N., Dharani Kumar S. and Gokulkumar S.
5.1 Introduction
5.2 Heat Source Modeling for Numerical Simulation in WAAM
5.2.1 Gaussian Distribution Heat Source Model
5.2.2 Double Ellipsoidal Heat Source (Goldak’s Model)
5.2.3 Conical Heat Source Model
5.2.4 Parameters Influencing the Heat Source Model in Numerical Simulations
5.2.5 Dynamic Heat Source Coupling in WAAM
5.2.6 Impact of Process Parameters on the Heat Source Model
5.2.7 Influence of Shielding Gas Composition on the Heat Source Model
5.3 Thermal and Mechanical Analysis in FEA for WAAM
5.3.1 Temperature Distribution
5.3.2 Cooling Rate
5.3.3 Heat Input
5.3.4 Anisotropy
5.3.5 Residual Stress and Distortion
5.4 Future Scope
5.5 Conclusion
References
6. The Role of Polymer Materials and Their Properties in Shaping the Future of Additive Manufacturing
Ganesh Nataraj, Ramesh Babu S., Ramu Murugan, Senthil Kumar A.P. and Ajithkumar Sitharaj
6.1 Introduction
6.2 Types of Polymer Materials Used in AM
6.2.1 Thermoplastics
6.2.2 Thermosetting Polymers
6.2.3 Composite Materials
6.3 Material Properties and Their Influence on AM
6.3.1 Mechanical Properties (Tensile Strength, Flexibility, Impact Resistance)
6.3.2 Thermal Properties (Heat Resistance, Melting Points, Thermal Expansion)
6.3.3 Chemical Resistance and Stability
6.3.4 Surface Finish and Printability
6.4 Processing Techniques in Polymer AM
6.4.1 Fused Deposition Modeling
6.4.2 Stereolithography
6.4.3 Selective Laser Sintering
6.4.4 Material Jetting
6.4.5 Direct Ink Writing
6.5 Design Considerations for Polymer AM
6.6 Advanced Polymer Materials for AM
6.6.1 Biodegradable Polymers
6.6.2 High-Performance Polymers
6.6.3 Elastomeric Polymers
6.6.4 Conductive Polymers
6.7 Applications of Polymer Materials in AM
6.7.1 Aerospace and Automotive
6.7.2 Medical and Healthcare
6.7.3 Consumer Goods
6.7.4 Fashion and Textiles
6.8 Challenges and Limitations
6.9 Future Trends in Polymer Materials for AM
6.10 Conclusion
References
7. Metal Additive Manufacturing
Nebechi Kate Obiora, Chika Oliver Ujah, Sandip Kunar, Peter Apata Olubambi and Daramy Vandi Von Kallon
7.1 Introduction
7.1.1 Historical Trend for AM
7.1.2 Classifications of AM
7.1.2.1 Material Extrusion
7.1.2.2 Powder Bed Fusion
7.1.2.3 VAT Polymerization
7.1.2.4 Binder Jetting
7.1.2.5 Material Jetting
7.1.2.6 Lamination of Sheets
7.1.2.7 Directed Energy Deposition
7.2 Basic Principles of MAM
7.2.1 Process Flow of AM
7.2.2 Properties of Metal Powders Used in MAM
7.2.3 Metal Solidification in MAM
7.3 MAM Processes
7.3.1 Pretreatment
7.3.2 Manufacturing
7.3.2.1 Solid Process
7.3.2.2 Liquid Process
7.3.3 Post-Treatment
7.3.3.1 Hot Isostatic Pressing
7.3.3.2 Heat Treatment
7.3.3.3 Surface Treatments
7.3.3.4 Friction Stir Engineering
7.4 Metals Used in AM
7.4.1 Alloys
7.4.2 Pure Metals
7.4.3 Precious Metals
7.4.4 MAM Applications
7.5 Recent Advances and Future Outlook
7.6 Conclusion and Recommendation
7.7 Recommendations
Acknowledgement
References
8. Advancement in Materials for Functional Three-Dimensional Printing
Arhaan Nawab, Waquar Alam, Wasim Alam, Mohd. Hamza and Faisal Talib
8.1 Introduction
8.2 Materials and Methods
8.2.1 Introduction to Material Innovation
8.2.2 Polymers
8.2.3 Metals
8.2.4 Composite Materials
8.2.5 Biomaterials
8.2.6 Smart Materials
8.2.7 Self-Healing Materials
8.2.8 Multi-Materials for Additive Manufacturing
8.2.9 Shape Memory Material
8.3 Applications of Materials
8.4 Conclusions
8.4.1 Future Research Directions
References
9. Cross-Country Comparative Analysis of Digital Manufacturing Systems
Sunita Routray, Rudra Narayan Mohapatro and Ranjita Swain
9.1 Introduction
9.1.1 Additive Manufacturing
9.1.1.1 WAAM Digital Techniques
9.1.1.2 SLA Digital Techniques
9.1.1.3 FDM Digital Techniques
9.1.1.4 LPBF Digital Techniques
9.1.1.5 Cyber-Physical Production Digital System
9.2 Digital Technological Review for the Manufacturing Process
9.3 Cross-Country Comparative Analysis of DMS
9.3.1 How India is Embracing DMS
9.3.2 About Digital Twin Technology
9.3.2.1 Importance of Digital Twin Technology in India
9.3.2.2 Types of Digital Twin Technology
9.3.2.3 Opportunities for Digital Twin Technology in India
9.3.3 Challenges in Implementing Digital Twin Technology in India
9.3.4 Implementation of Digital Twin Technology by Industries in India
9.3.5 Future of Digital Twin Technology in India
9.3.6 Impact of Digital Technologies in Developed Countries
9.3.7 Dark Side of DMS
9.4 Advances in DMS in Today’s World
9.4.1 Digitalization’s Role in SMEs and Innovation
9.4.2 AR in Manufacturing
9.4.3 DT and Sustainability
9.4.4 DT for SMEs
9.4.5 Collaborative Robots in Automotive Production
9.4.6 Mass Customization in Industry 4.0
9.4.7 Digital Twin Technology Across Industries
9.4.8 Digital Manufacturing and Cost Management
9.5 Future Prospects in the Manufacturing Industry
9.5.1 DT and SME Innovation
9.5.2 Digitalization’s Role in Sustainable Manufacturing
9.5.3 Advancements in AM
9.5.4 Globalization and the Fourth Industrial Revolution
9.5.5 Cloud Computing in Manufacturing
9.5.6 CPS and Industry 4.0
9.5.7 The Convergence of Digital, Built, and Natural Environments
9.5.8 Educational Challenges in Smart Manufacturing
9.5.9 Future Directions in Digital Manufacturing
9.6 Conclusion
References
10. A Review and Analysis from Industry 4.0 Toward Industry 5.0
Sandip Kunar, Jagadeesha T., Chika Oliver Ujah, Norfazillah Talib, Gurudas Mandal, K. Nagasuresh, N. Naresh, S. Rama Sree and M. Sreenivas Reddy
10.1 Introduction
10.2 Historical Overview
10.3 Basic Driving Concepts of Industry 4.0 and Industry 5.0
10.4 Review of Key Enablers in Practical Context of Industry 4.0 and Industry 5.0
10.4.1 Toward Human-Centricity
10.4.2 Toward Sustainability
10.4.3 Toward Resilience
10.5 Discussion
10.6 Are We Fear of Technology? The Role of Regulations
10.7 Controlling AI
10.8 Conclusions
10.9 The Future
References
11. Envisioning Industry 4.0: A Review
Sumanta Banerjee and Anindita Kundu
11.1 Introduction and Background
11.2 Changes and Transformation of Manufacturing Ecosystems: A Review
11.3 Smart Manufacturing Systems: Role of AI, IoT, and Big Data
11.3.1 Artificial Intelligence
11.3.2 Smart Manufacturing Systems
11.4 Intelligent Factories
11.5 The Fourth Industrial Revolution (Industry 4.0)
11.6 Industry 3.0 to Industry 4.0: Mapping the Transformation
11.7 Impact of Industry 4.0: Technological Inference
11.8 Impact of Industry 4.0: Socio-Cultural Impacts
11.9 Impact of Industry 4.0: Business Prospects
11.10 Conclusions and Present/Futuristic Trends
References
12. Future Development of Digital Manufacturing Science
Alok Kumar and Sachin Kumar
12.1 Introduction
12.2 Conventional Methodology of the DMS Process
12.2.1 Driving Forces
12.2.2 Manufacturing of SM
12.2.3 Additive Manufacturing
12.3 The Electrical Mechanical (Elec-Mech) System with DMS
12.3.1 Micro Elec-Mech System (MEMS) and Nano Elec-Mech System (NEMS)
12.3.2 MEMS and NEMS with DMS
12.3.3 Micro Nano Equipment of the System
12.3.4 Micro-Nano Manufacturing with DMS Technology
12.4 The Externalization of DMS
12.4.1 Extreme Manufacturing
12.4.2 Elec-Mech System Modeling
12.4.3 Elec-Mech Systems in Ecological Systems
12.5 The Environmental Protection of DMS
12.5.1 The Implementation of Ecology Protection
12.5.2 Conscious Ecological Manufacturing
12.5.2.1 The Overview of Environmentally Conscious Manufacturing
12.5.2.2 Research Content of ECM System
12.5.2.3 Digital Ecological Product Manufacturing (EPM) System
12.5.3 Overview of Re-Engineering of Product Manufacturing
12.5.3.1 The Key Technology Re-EPM
12.5.3.2 DM Technology in Re-EPM
12.6 Applications of DMS
12.6.1 Automobile Sectors
12.6.2 Defense and Aerospace Sectors
12.6.3 Medical Sectors
12.6.4 Food Sectors
12.6.5 Construction Sectors
12.7 Conclusion
References
Part II: Computing Applications
13. Computing Manufacturing in Digital Manufacturing Science
Dasari Madhusudhan, Rupa Srivani and Keerthi Prabhavathi
13.1 Introduction
13.1.1 Digital Manufacturing and Its Significance
13.1.2 Role of Computing in Advancing Manufacturing Processes
13.1.3 Integration of Physical and Digital Components
13.1.4 Impact of Computing on Efficiency, Quality, and Innovation in Manufacturing
13.1.5 Challenges in Digital Manufacturing
13.1.6 Computing Transformed Manufacturing Processes
13.1.7 Key Computing Technologies Used in Digital Manufacturing
13.2 Theoretical Foundations of Computing in Manufacturing
13.2.1 Computing in Manufacturing
13.2.2 Digital Manufacturing Science and Its Components
13.2.3 Evolution of Computing in Manufacturing
13.2.4 Core Computing Concepts in Manufacturing
13.3 Mathematical Methods
13.3.1 Geometric Modelling
13.3.2 Finite Element Analysis (FEA)
13.3.3 Optimization Methods
13.3.4 Computational Fluid Dynamics (CFD)
13.3.5 ML and AI
13.3.6 Statistical Process Control
13.3.7 Operations Research and Supply Chain Optimization
13.4 Key Computing Technologies in Manufacturing
13.4.1 Computer-Aided Design and Engineering
13.4.2 Computer-Aided Manufacturing
13.4.3 Simulation and Modelling
13.4.4 AI and ML
13.4.5 Big Data and Analytics
13.4.6 Cloud Computing
13.5 Applications of Computing in Digital Manufacturing
13.5.1 Smart Factories and Industry 4.0
13.5.2 Additive Manufacturing and 3D Printing
13.5.3 Supply Chain Optimization
13.5.4 Robotics and Automation
13.5.5 Benefits and Challenges of Computing in Manufacturing
13.6 Case Studies
13.6.1 Siemens’ Use of AI and Simulation in Manufacturing
13.6.2 General Electric’s Digital Twin Technology
13.6.3 Tesla’s Smart Manufacturing System
13.6.4 Boeing’s Use of Computational Tools in Aerospace Manufacturing
13.7 Discussion and Analysis
13.7.1 Comparative Analysis of Case Studies
13.7.2 Quantitative and Qualitative Approaches
13.7.3 Impact of Computing on Manufacturing Efficiency
13.7.4 Future Trends in Computing for Manufacturing
13.7.5 Ethical and Policy Considerations
13.8 Conclusion
13.9 Implications for Industry
13.10 Suggestions for Future Research
References
14. Unlocking the Potential of Intelligent Manufacturing Guide to Digital Manufacturing
Adnan Zafar, Imad Ur Rehman, Jamal Abdullah Haider and Faisal Talib
14.1 Introduction
14.1.1 Overview of Digital Manufacturing
14.1.2 Introduction to Intelligent Manufacturing
14.2 Progression of Manufacturing Innovations
14.2.1 Various Technologies of Intelligent Manufacturing
14.3 Case Studies
14.3.1 Case Study of Hero MotoCorp
14.3.2 Case Study of Tesla
14.3.3 Case Study of Siemens
14.4 Challenges and Barriers
14.5 Conclusion
14.5.1 Implications
14.5.2 Future Research Opportunities
References
15. Bionic Manufacturing in Digital Manufacturing Science
Debjani Bhakta, Jyoti Bhattacharjee and Subhasis Roy
15.1 Introduction
15.1.1 Bionic Needs
15.1.2 Bionic Models
15.1.3 Bionic Simulations
15.1.4 Bionic Products
15.2 Digital Technologies Used for Bionic Manufacturing
15.2.1 Artificial Intelligence (AI) and Machine Learning
15.2.2 Simulation and Modelling
15.2.3 Internet of Things (IoT)
15.3 Applications of Bionic Manufacturing
15.3.1 Robot Fish
15.3.2 Bionic Shark Skin
15.3.3 Aircraft and Aerospace
15.3.4 Medical Field
15.3.5 Textile Industry
15.4 Applications of Bionic Manufacturing in Digital Manufacturing Science
15.4.1 Bionic Structures in Aerospace Manufacturing
15.4.2 Bionic Manufacturing in Architecture
15.4.3 Bionic Additive Manufacturing in Consumable Products
15.4.4 Bionic Manufacturing in the Auto Industries
15.4.5 Biomimetic Robotics and Automation
15.4.6 Bionic Agriculture and Food Production
15.4.7 Bionic Packaging Solutions
15.4.8 Bionic Energy Solutions
15.4.9 Bionic Marine and Underwater Engineering
15.4.10 Bionic Manufacturing in Electronics
15.4.11 Bionic Defense and Security Applications
15.4.12 Bionic Innovations in Environmental Restoration
15.4.13 Nature-Inspired Pollution Control
15.5 Challenges and Future Directions
15.5.1 Complexity in Design and Engineering
15.5.2 Drawbacks and Compatibility with Materials
15.5.3 Synthesis of Interdisciplinary
15.5.4 Scaling and Commercialization Issues
15.5.5 High Technology Manufacturing Expense
15.5.6 The Lack of Standardization in Bionic Systems
15.5.7 Ethical and Regulatory Issues
15.6 Case Studies
15.6.1 Nature-Inspired Bionic Design
15.6.2 Bionic Structures for Lightweight Designs
15.6.3 Bionic Soft Robotics by Digital Techniques
15.6.4 Bionic Manufacturing in Biomedical Engineering
15.6.5 Digital Manufacturing of Bionic Exoskeletons
15.6.6 Case Study Production of Digital Design and Manufacturing Customized Exoskeletons for Rehabilitation
15.6.7 BionicANTs by Festo
15.6.8 Octopus-Inspired Soft Robotics in Assembly Lines
15.6.9 Spider-Inspired Agricultural Robots
15.6.10 Bionic Fish and Industrial Fluid Systems
15.6.11 Bionic Arm in Logistics
15.7 Conclusions
Acknowledgement
References
16. Direct Digital Manufacturing for Biomedical Applications: Toward Efficient Healthcare
Amey Dukle and M. Ravi Sankar
16.1 Introduction
16.2 Technological Foundations of DDM for Biomedical Applications
16.2.1 The Design Process in DDM for Personalized Implants
16.2.1.1 Data Acquisition Methods
16.2.1.2 CAD Model Creation
16.2.2 Materials Utilized in DDM for Biomedical Applications
16.2.2.1 Polymers
16.2.2.2 Metals
16.2.2.3 Ceramics
16.2.2.4 Composite Materials
16.2.3 Technologies for DDM
16.2.3.1 Direct Ink Writing
16.2.3.2 Stereolithography
16.2.3.3 Fused Deposition Modelling
16.2.3.4 Selective Laser Sintering
16.2.3.5 3D Bioprinting
16.3 Application of DDM for Biomedical Applications
16.3.1 Tissue Engineering
16.3.2 Custom Implants and Prosthetics Production
16.3.3 Surgical Planning and Training
16.4 Challenges in Adoption of DDM for Biomedical Applications
16.4.1 Acceptance from Medical Professionals
16.4.2 Regulatory Challenges
16.5 Conclusion and Future Outlook
References
17. Digital Manufacturing and the Fifth Industrial Revolution
Alok Kumar and Ravi Shankar Rai
17.1 Digital Manufacturing
17.1.1 Integration Technology of DM
17.1.2 Information Technology in Manufacturing
17.1.3 Computer-Aided Design-Based Technologies
17.1.4 Manufacturing-Based Control
17.1.5 Software-Based Simulation
17.1.6 Enterprise Resource Planning (ERP)
17.2 Development of Industrial Revolutions
17.2.1 Background
17.2.2 The First IR (Industry 1.0)
17.2.3 The Second IR (Industry 2.0)
17.2.4 The Third IR (Industry 3.0)
17.2.5 The Fourth IR (Industry 4.0)
17.2.6 The Fifth IR (Industry 5.0)
17.3 Uses of Digital Manufacturing
17.3.1 Continuous Upgrade of DM Systems
17.3.2 Modification Using DM Systems
17.3.3 Safety Enhancement in the DM Process
17.3.4 Predictive Maintenance in DM
17.3.5 Manufacturing Data Collection
17.4 Characterizing Industry 5.0
17.4.1 Need for Industry 5.0
17.4.2 Solution-Based Methodology
17.4.2.1 Online Instruction
17.4.2.2 Self-Sustained Systems with AI
17.4.2.3 Implementation of ML with Sensor Technologies
17.4.3 Manufacturing System Affected by Industry 5.0
17.5 Applications of DM Sectors
17.5.1 Aeronautical Sector
17.5.2 Automotive Sector
17.5.3 The Renewable Energy-Based Sector
17.5.4 The Telecom Sector
17.6 Conclusion
References
18. Factories of the Future: Digital Manufacturing in the Manufacturing Industry
Rasu Karunanithi, Mohammed Abdur Rahman and Gopal Rajesh
18.1 Introduction
18.2 Advanced Technologies Used in Digital Manufacturing
18.2.1 Industry 4.0 and IoT
18.2.2 Significance for Prototyping, Production, and Customization
18.2.3 Production
18.2.4 Customization
18.2.5 Artificial Intelligence and Machine Learning
18.2.6 AI-Driven Analytics
18.2.7 Predictive Maintenance
18.2.8 Robotics and Automation
18.2.9 Digital Twins: The Ability to Construct “Virtual Twins” Using Holography Technology to Simulate and Optimize
18.2.10 Optimization and Predictive Maintenance
18.2.11 Big Data and Analytics
18.2.12 Cybersecurity in Manufacturing: Protecting Digital Manufacturing Enterprises
18.2.13 The Impact of Digital Manufacturing
18.2.14 Customization and Flexibility
18.2.15 Mass Customization
18.2.16 Sustainability
18.3 Workforce Transformation: Skills Needed for Managing and Operating Digital Manufacturing Systems
18.4 Case Studies
18.4.1 Siemens
18.4.2 General Electric (GE)
18.4.3 Bosch
18.4.4 Tesla
18.4.5 Siemens Gamesa
18.4.6 Daimler AG (Mercedes-Benz)
18.5 Challenges and Barriers to Adoption
18.5.1 Upfront Capital Investment
18.5.2 ROI Uncertainty
18.5.3 Operational Disruptions during Implementation
18.6 Cost of Technology Upgrades and Maintenance
18.7 Conclusion
References
19. Business Models for Additive Manufacturing: A Consulting Services Perspective
Yogeshwaran Kumarasamy, Prases Kumar Mohanty and Shubhajit Das
19.1 Introduction
19.2 Business Background
19.3 Importance of Business Model
19.4 Business Models for Consulting Services
19.4.1 Firm Model
19.4.2 Independent Model
19.4.3 Productized Model
19.5 Requirements for Consulting Services
19.5.1 Collaborations and Partnerships
19.5.2 Core Activities
19.5.3 Key Expedient
19.5.4 Value Scheme
19.5.5 Client Engagement
19.5.6 Customer Niche
19.5.7 Marketing
19.6 Opportunities in Various Segments
19.6.1 Parts Designing for Additive Manufacturing
19.6.2 Training for Additive Manufacturing
19.6.3 At Aerospace, Automotive, Defense, and Tooling
19.6.4 At Construction
19.6.5 At Medical
19.7 Challenges in Additive Manufacturing for Consulting Service
19.8 Conclusion
References
20. Integration of Additive Manufacturing with Digital Technologies for Future Manufacturing
Ganesh Nataraj, Ramesh Babu S., Ramu Murugan, Senthil Kumar A.P. and Ajithkumar Sitharaj
20.1 Introduction
20.2 Understanding Additive Manufacturing
20.3 The Intersection of Additive Manufacturing and Digital Transformation
20.4 Impact of Additive Manufacturing on Supply Chains
20.4.1 Decentralization and On-Demand Production Enabled by AM
20.4.2 Reducing Lead Times and Inventory Costs
20.4.3 Enhancing Supply Chain Resilience and Flexibility Through Digital Networks
20.5 Sustainability in Additive Manufacturing
20.6 Customization and Personalization in Digital Manufacturing
20.7 Challenges and Opportunities
20.7.1 Technical and Economic Challenges in Integrating AM into Existing Workflows
20.7.2 Regulatory and Standardization Issues in Digital Manufacturing
20.7.3 Opportunities for Innovation and Growth in AM Through Digital Transformation
20.8 Future Trends in Additive Manufacturing and Digital Transformation
20.8.1 Emerging Technologies and Materials in AM
20.8.2 The Convergence of AM with Other Industry 4.0 Technologies (e.g., AI, Robotics, Big Data)
20.8.3 Predictions for the Future Impact of AM on Global Manufacturing
20.9 Conclusion
References
21. Computational Approaches to Advanced Digital Manufacturing Practices
D.V.S.S.S.V. Prasad, Akhilesh Kumar Singh, Marxim Rahula Bharathi. B., Yarrapragada K.S.S. Rao and V.V. Kamesh
21.1 Introduction
21.1.1 Overview of Digital Manufacturing Science
21.1.2 Importance of Computing in Modern Manufacturing
21.1.3 Purpose and Scope of the Chapter
21.2 Foundations of Digital Manufacturing
21.2.1 Definition and Evolution of Digital Manufacturing
21.2.2 Key Technologies and Concepts
21.2.2.1 Computer-Aided Design (CAD)
21.2.2.2 Computer-Aided Manufacturing (CAM)
21.2.2.3 Digital Twins
21.2.2.4 Simulation and Modelling
21.3 Overview of Computational Models in Manufacturing
21.3.1 Overview of Computational Models
21.3.2 Types of Computational Models Used in Manufacturing
21.3.2.1 Finite Element Analysis (FEA)
21.3.2.2 Computational Fluid Dynamics (CFD)
21.3.2.3 Multi-Body Dynamics (MBD)
21.3.3 Case Studies and Examples
21.4 Data Management and Analytics
21.4.1 Role of Data in Digital Manufacturing
21.4.2 Data Acquisition and Integration
21.4.3 Data Analytics Techniques
21.4.3.1 Statistical Analysis
21.4.3.2 Machine Learning and AI
21.4.4 Examples of Data-Driven Decision-Making
21.5 Software and Tools
21.5.1 Overview of Key Software Tools
21.5.1.1 CAD Software
21.5.1.2 CAM Software
21.5.1.3 Simulation Software
21.5.2 Integration of Tools and Systems
21.5.3 Emerging Software Trends and Innovations
21.6 Computing Architectures and Systems
21.6.1 High-Performance Computing (HPC) in Manufacturing
21.6.2 Cloud Computing and Its Impact
21.6.3 Edge Computing in Manufacturing Contexts
21.6.4 Examples of Computing Systems in Use
21.7 Challenges and Limitations
21.7.1 Computational Complexity and Resource Constraints
21.7.1.1 Understanding Computational Complexity
21.7.1.2 Data Security and Privacy Issues
21.7.1.3 Integration Challenges
21.7.2 Case Studies of Common Challenges
21.7.2.1 Food and Beverage Industry: Compliance and Safety
21.7.2.2 Electronics Manufacturing: Supply Chain Disruptions
21.7.2.3 Pharmaceutical Industry: Data Integrity Issues
21.8 Future Trends and Innovations
21.8.1 Advancements in Computing Technologies
21.8.1.1 Enhanced Computational Power
21.8.1.2 Innovations in Hardware
21.8.2 The Role of Quantum Computing
21.8.2.1 What is Quantum Computing?
21.8.2.2 Potential Applications in Manufacturing
21.8.3 Current Developments
21.8.3.1 AI and Machine Learning Advancements
21.8.4 Future Trends in Digital Manufacturing and their Implications
21.8.4.1 Digital Twins and Virtual Prototyping
21.8.4.2 Sustainable Manufacturing
21.8.4.3 Personalized Manufacturing
21.8.4.4 Implications for Workforce and Skills
21.9 Conclusion
21.9.1 Summary of Key Points
21.9.2 The Impact of Computing on the Future of Manufacturing
21.9.3 Final Thoughts and Recommendations for Practitioners
References
Index
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