E-raamat: Manufacturing in the Digital Age [Taylor & Francis e-raamat]

Preface, Acknowledgment, Editors 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 Nikes Digital Innovation 3.7.3 Fords
Electrification Strategy 3.7.4 Adobes Creative Cloud 3.7.5 Samsungs 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
LevenbergMarquardt 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 HumanMachine 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
HumanMachine 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 Markets Future is
Fueled by Hyper Automation 12.8 Conclusion References. Index.

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.