1st Edition
Manufacturing in the Digital Age
Preface, Acknowledgment, Editor’s Bibliography, List of Contributors, Foreword
Chapter 1 Introduction to Manufacturing in the Digital Age
1.1 The Order from First Production to the Industrial Revolution
1.1.1 Definition and History of Manufacturing
1.1.2 Traditional Manufacturing Processes
1.1.3 Challenges and Limitations of Traditional Manufacturing
1.2 Revolutionizing Manufacturing with Digital Transformation
1.2.1 Definition of Digital Manufacturing
1.2.2 Key Factors of Digital Transformation in Manufacturing
1.2.3 The Role of Industry 4.0
1.3 Key Technologies in Digital Manufacturing
1.3.1 IoT
1.3.2 Big Data and Analytics
1.3.3 AI and ML
1.3.4 Robotics and Automation
1.3.5 Additive Manufacturing (3D Printing)
1.3.6 Digital Twins
1.3.7 Cloud Computing
1.3.8 Cybersecurity
1.4 Impact of Digital Manufacturing
1.4.1 On Product Development
1.4.2 On Supply Chain Management
1.4.3 On Workforce
1.5 Case Studies and Real-World Examples
1.5.1 Success Stories from Leading Manufacturers
1.5.2 Challenges Faced and Overcome
1.5.3 Lessons Drawn and Leading Practices
1.6 Benefits of Digital Manufacturing
1.6.1 Increased Efficiency and Productivity
1.6.2 Cost Reduction
1.6.3 Improved Quality and Consistency
1.6.4 Enhanced Flexibility and Agility
1.7 Challenges and Barriers to Adoption
1.7.1 Technical Challenges
1.7.2 Cost and Investment Considerations
1.7.3 Workforce Resistance and Cultural Change
1.7.4 Data Privacy and Security Concerns
1.8 Future Trends in Digital Manufacturing
1.8.1 Emerging Technologies
1.8.2 Predictions for the Next Decade
1.8.3 The Role of Sustainability and Green Manufacturing
1.9 Conclusion
Chapter 2 Advancements in Industry 4.0 and Introduction to Industry 5.0
2.1 Introduction
2.1.1 Overview of the Industrial Revolutions
2.1.2 Introduction to I4o and I5o
2.1.3 Chapter Objectives
2.2 Core Technologies of I4o
2.2.1 IoT
2.2.2 AI and ML
2.2.3 CPS
2.2.4 Big Data Analytics
2.2.5 Robotics and Automation
2.3 Applications and Implications of I4o
2.3.1 Smart Factories
2.3.2 SCM
2.3.3 Predictive Maintenance and AI in Manufacturing
2.3.4 Digital Twins
2.4 I5o: A Human-Centric Approach
2.4.1 From Automation to Augmentation
2.4.2 Ethical and Value-Oriented Technology in I5o
2.4.3 Resilience and Sustainability
2.4.4 Customization and Personalization
2.5 Key Technologies Enabling I5o
2.5.1 Advanced AI and Robotics
2.5.2 CPS in I5o
2.5.3 Metaverse and Virtual Collaboration Tools
2.6 Transitioning from I4o to I5o
2.6.1 Evolutionary Path
2.6.2 Overcoming Challenges in the Transition
2.6.3 Collaborative Ecosystem
2.7 Case Studies and Practical Insights
2.7.1 Smart Factories in Action
2.7.2 Personalized Manufacturing
2.8 Conclusion
2.8.1 Summary of Key Innovations Driving I4o and I5o
2.8.2 Outlook on Future Developments in I5o
Chapter 3 Product Design and Development in the Digital Era
3.1 Introduction
3.2 Digital Design and Prototyping
3.2.1 Computer-Aided Design (CAD)
3.2.2 Virtual Reality (VR) and Augmented Reality (AR)
3.3 Collaborative Design and Development
3.3.1 Cloud-Based Collaboration
3.3.2 Integrated Design and Development Tools
3.3.3 Communication and Messaging Platforms
3.3.4 Project Management and Collaboration Tools
3.3.5 User Testing and Feedback
3.3.6 Security and Access Controls
3.4 Data-Driven Decision-Making
3.4.1 User Behavior Analysis
3.4.2 Performance Analytics
3.4.3 Iterative Design and Development
3.4.4 Predictive Analytics
3.4.5 Cost-Benefit Analysis
3.4.6 Security Analytics
3.5 Sustainability and Efficiency
3.5.1 Green Software Engineering
3.5.2 Renewable Energy in Data Centers
3.5.3 Life Cycle Assessment (LCA) for Digital Products
3.5.4 Agile and DevOps for Efficiency
3.5.5 Automation and Efficiency
3.5.6 User Experience (UX) and Performance Optimization
3.5.7 Remote Collaboration and Sustainable Work Practices
3.5.8 Resource Efficiency in Cloud Computing
3.6 Challenges
3.6.1 Data Privacy and Security
3.6.2 Rapid Technological Changes
3.6.3 User Experience (UX) Design Challenges
3.6.4 Artificial Intelligence (AI) Integration Challenges
3.6.5 Positive and Negative Social Effects
3.6.6 Skill Gaps
3.6.7 Reluctance to Change
3.7 Case Studies
3.7.1 Digital Transformation at Siemens
3.7.2 Nike’s Digital Innovation
3.7.3 Ford’s Electrification Strategy
3.7.4 Adobe’s Creative Cloud
3.7.5 Samsung’s Product Innovation
3.7.6 Nike+
3.7.7 Starbucks’ Mobile App
3.7.8 Peloton Interactive Fitness
3.7.9 HelloFresh Meal Kits
3.7.10 Netflix
3.8 Future Trends
3.8.1 Human-Centered and Inclusive Design
3.8.2 Customization and Personalization
3.8.3 Digital Twins
3.8.4 IoT Integration
3.8.5 AR and VR in Product Prototyping
3.8.6 Robotics and Automation
3.8.7 Biometric Integration
3.8.8 Edge Computing in Product Functionality
3.8.9 Voice User Interfaces (VUI)
3.8.10 Blockchain for Supply Chain Transparency
3.8.11 Emphasis on Emotional Design
3.9 Conclusions
Chapter 4 Internet of Things (IoT) in Smart Manufacturing
4.1 Introduction
4.1.1 Manufacturing
4.1.2 IoT
4.2 Application of IOT
4.2.1 Enhanced Operational Efficiency
4.2.2 Predictive Maintenance
4.2.3 Quality Improvement
4.2.4 Supply Chain Optimization
4.2.5 Energy Efficiency
4.2.6 Customization and Flexibility
4.2.7 Innovation and Competitive Advantage
4.2.8 Data Integration and Analytics
4.3 Digitalization of Manufacturing Processes Relies Heavily on Internet of Things (IoT)
4.4 To Enable Real-Time Data Collection
4.5 Predictive Maintenance
4.6 Improved Supply Chain Management
4.7 Industry 4.0 and Industry 5.0 are Integrating IoT
4.8 Sensor
4.9 Devices
4.10 Networks
4.11 Conclusion
Chapter 5 Sustainable Manufacturing Practices in the Digital Age
5.1 Introduction
5.1.1 Sustainable Manufacturing in a Digital Context
5.2 Function of Additive Manufacturing in the Digital Era of Sustainable Manufacturing
5.3 Challenges to Implementing Sustainable Manufacturing Practices in the Digital Age
5.4 Innovation and Technology for Sustainability
5.5 New Developments in Digital Sustainability Trends
5.5.1 Green AI.
5.5.2 Bio-Manufacturing
5.5.3 Edge Computing
5.5.4 Decentralized Energy Grids
5.6 The Digital Transformation of Sustainability
5.6.1 Smart Factories: A Step Toward Zero Waste
5.7 The Benefits of Sustainable Manufacturing Practices in Digital Ages
5.8 Smart Manufacturing: The Path to Sustainability
5.9 The Future of Sustainable Manufacturing in the Digital Age
5.10 Conclusion
Chapter 6 Challenges and Solutions of Industry 4.0 to Industry 5.0
6.1 Introduction to Industry 4.0
6.2 Challenges and Solutions in Adopting Industry 4.0
6.3 Datasets
6.4 Challenges and Solutions in Adopting Industry 5.0
6.5 Conclusions
Chapter 7 Sustainable Industrial Transformation: Exploring Industry 4.0 and 5.0
7.1 Introduction
7.2 Evolution of Industrial Revolutions
7.3 Challenges of Industry 4.0
7.4 A Strategic Method to Meet the Obstacles
7.5 Industry 5.0: A Strategic Solution
7.6 Technological Advancements in Industry 4.0 and 5.0
7.7 Future Research Directions
7.8 Conclusion
Chapter 8 Artificial Neural Networks with Training Algorithms for Prediction of Surface Roughness in Electrical Discharge Machining
8.1 Introduction
8.1.1 Research Novelty
8.2 Experiments and Methods
8.2.1 Experimental Set Up
8.2.2 Design of Experiment
8.2.3 Surface Roughness
8.2.4 Artificial Neural Networks
8.2.5 ANN Training Algorithms
8.2.6 Levenberg–Marquardt Algorithm
8.2.7 Conjugate Gradient Algorithm
8.2.8 Resilient-Backpropagation Algorithm
8.2.9 Evaluation Criteria
8.3 Results and Discussion
8.4 Conclusions
Chapter 9 Effect of Performance Measures on Lean Manufacturing System Considering Industry 4.0
9.1 Introduction
9.2 Lean Manufacturing System: An Overview
9.2.1 Machine-Level Configurations
9.2.2 System Base Configurations
9.3 Process
9.4 Changeover Time
9.5 Conclusion and Future Scope
Chapter 10 Human–Machine Harmony in the Production Sector: How Automation is Transforming Manufacturing 10.1 Introduction
10.2 Fixed Automation
10.2.1 Definition and Characteristics of Fixed Automation
10.2.2 Examples of Fixed Automation
10.2.3 Advantages of Fixed Automation
10.2.4 Limitations of Fixed Automation
10.3 Fluid Automation
10.3.1 Concept and Definition
10.3.2 Key Components of Fluid Automation
10.3.3 Applications of Fluid Automation
10.3.4 Advantages and Challenges of Fluid Automation
10.4 Human–Machine Collaboration
10.4.1 Role of Automation in Repetitive and Advanced Tasks
10.4.2 Workforce Skill Requirements
10.4.3 Designing Workplaces for Safety and Collaboration
10.5 Industry 4.0 Integration
10.5.1 Industry 4.0 Vision and Goals
10.5.2 Importance of Interoperability
10.5.3 Real-Time Information Sharing and Adaptability
10.6 Conclusion
10.6.1 Synergy between Humans and Machines
10.6.2 Fluid Automation as a Path to Flexibility
10.6.3 Future Manufacturing Outlook
Chapter 11 Efficient Automation Solution for Invoice Data Extraction and Compilation: A Streamlined Approach for Enhanced Productivity
11.1 Introduction
11.2 Introduction to Robotic Process Automation (RPA) and its Advantages
11.3 Purpose and Significance of the Study
11.4 Methodology
11.4.1 Overview of Selected RPA Tools (e.g., UiPath, Automation Anywhere)
11.4.2 Step-By-Step Explanation of the Automation Process
11.4.3 Handling Failed Extractions
11.5 Implementation Steps
11.6 Results and Discussion
11.6.1 Performance Metrics (Accuracy, Time Savings)
11.6.2 Sample Outputs (e.g., Processed Invoices, Excel Data)
11.6.3 Comparative Analysis with Manual Processing Methods
11.7 Benefits of Automation
11.8 Challenges and Limitations of Automation Systems
11.9 Challenges in Manufacturing Environments
11.10 Solutions Tailored to Manufacturing
11.11 Conclusion
Chapter 12 Modernizing and Streamlining Vendor Records Using Robotics Process Automation for Uplifting Business
12.1 Introduction
12.1.1 Basics of Robotics Process Automation (RPA)
12.1.2 How it Works
12.1.3 Importance of RPA
12.2 Literature Review
12.2.1 Presence of RPA
12.2.2 History
12.2.3 Features and Main Characteristics
12.2.4 Types of RPA
12.2.5 Artificial Intelligence and RPA
12.3 Use Case Example
12.3.1 Current Process Followed in the Chudekar Agro Pvt. Ltd. Company
12.3.2 Future Changes Can be Done Using RPA
12.4 Advantages of RPA
12.5 Disadvantages Rather Challenges of RPA
12.6 Current RPA Providers
12.7 The RPA Market’s Future is Fueled by Hyper Automation
12.8 Conclusion
References. Index.
Biography
Mohan Kumar Pradhan, M.Tech (Mechanical Engineering, REC (now NIT), Rourkela), and Ph.D. (Engineering, NIT Rourkela), is currently working as an Associate Professor in the Department of Mechanical Engineering, National Institute of Technology (NIT), Raipur – an Institute of National Importance. He previously served as an Assistant Professor in the Department of Mechanical Engineering, Maulana Azad National Institute of Technology (MANIT), Bhopal, – also an Institute of National Importance. Pradhan has over 26 years of teaching and research experience in the field of manufacturing. His areas of teaching and research include Manufacturing Technologies, Additive Manufacturing, Quality Assurance, Metrology, Tool Engineering, Metal Forming, Theory of Plasticity, Design and Manufacturing, Non-Traditional Machining, Micro-Machining, MEMS, Hybrid Machining, Composites, and Process Modelling and Optimization. Pradhan has made significant contributions to his field with over 85 international journal publications and over 80 technical papers published in conference proceedings. He has authored one book, edited two books, and edited over five conference proceedings. Additionally, he has served as a guest editor for more than five journals and contributed over 30 book chapters. He is a member of the editorial board and review panel for more than five renowned international journals. His research achievements have earned him numerous awards and honours. He has been recognised in the Web of Science Core Collection with 200 publications, an h-index of 16+, a SCOPUS h-index of 18+, and a Google Scholar h-index of 25+. Pradhan is a Chartered Engineer, a Life Fellow of the Indian Institution of Production Engineers (IIPE), a Life Member of ISTE, IACSIT, IAENG, and a Fellow (F.I.E.). Pradhan has been featured in the top 2% of world scientists list for 2021, 2022, 2023, and 2024, as prepared by a team of scientists at Stanford University in the United States.
Mahendra U. Gaikwad is currently working as an Assistant Professor in the Department of Mechanical Engineering, Veermata Jijabai Technological Institute (VJTI), Mumbai, (An Autonomous Institute of the Government of Maharashtra), India. He has more than 11 years of teaching experience at UG & PG level. He obtained his B.E. in Mechanical Engineering and M.E. in Mechanical Design Engineering from the Walchand Institute of Technology, Solapur, Maharashtra, India, and Ph.D. in Mechanical Engineering from the Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. His current research interests include advanced manufacturing process, material characterization, surface integrity, machining of smart material alloys and optimization. He has published more than 25 articles, 3 book chapters, and edited 2 books with renowned publishers. He acted as a reviewer in more than three international journals & four international conferences. Being concerned with manufacturing research background he has undertaken industry based research projects for UG & PG students, till date he has guided more than 25 UG project groups and more than 8 PG students in his teaching career. He has received the Best Performer in Education (Teaching & Research Excellence) Award in 2022 year by Savitribai Phule Excellence Award, Pune, Maharashtra, India. He is a member of International Association of Engineers (IAENG) and lifetime member of the Quality Circle Forum of India.
Ragavanantham Shanmugam, Department Chair of Engineering Technology at Fairmont State University, West Virginia, United States, is recognized for his exceptional contributions to engineering education for the underserved communities through innovative teaching, curriculum development, and student mentorship. With over 25 years of global academic experience, Shanmugam has advanced interdisciplinary learning, fostered industry partnerships, and championed diversity, equity, and inclusion in STEM. His scholarly impact includes over 575+ citations, 5 book Chapters in advanced manufacturing and pioneering research in advanced manufacturing and sustainable engineering. Awarded multiple Best Teacher honors, his leadership has inspired countless students and colleagues, embodying the values of excellence and innovation in engineering education.
