Industry 4.0 Driven Manufacturing Technologies

Preface
Acknowledgements
Contents
Editors and Contributors
Evolution of Digital Twin in Manufacturing Application: Definition, Architecture, Applications, and Tools
	1 Introduction
		1.1 Digital Twin Terminology and History
	2 Digital Twin Definition and Its Scope
		2.1 Comparing DT with Simulation and CPPS
	3 Reference Architecture
		3.1 Reference Architecture Model Industrie 4.0 (RAMI 4.0) (Weber et al. 2017; Beisheim et al. 2020; Park et al. 2021a; Schweichhart 2019)
		3.2 Stuttgart IT-Architecture for Manufacturing (SITAM) (Weber et al. 2017; Gröger et al. 2016)
		3.3 Industrial Internet Reference Architecture (Weber et al. 2017; Lin et al. 2017; Industrial Internet Consortium 2015)
		3.4 ISO 23247 Digital Twin Framework for Manufacturing (Shao and Helu 2020; Digital Manufacturing Working Group (WG15) 2021)
		3.5 Activity-Resource-Type-Instance (ARTI) Architecture (Juarez et al. 2021; Anton et al. 2020; Borangiu et al. 2019)
		3.6 Five-Dimensional Model (Tao et al. 2019c)
	4 Digital Twin Applications in Manufacturing
	5 Tools and Models Used in DT Development
	6 Discussion, Conclusions and Future Research Directions
	7 The Challenges Faced by DT
		7.1 Lack of Unified Framework/Architecture
		7.2 Lack of Interoperability of Data
		7.3 Lack of Connectivity, Data Security, and Communication Protocol
		7.4 Lifecycle Maintenance of DT
	8 Future Research Scope
		8.1 Integration of Human Resource Expertise with Digital Twin
		8.2 Optimization of Communication Methods
		8.3 Cognition in Digital Twin for Better Decision Making
		8.4 Decentralized Manufacturing Application
		8.5 Application of DT in Inspection
		8.6 Development of Data Lake for Digitalization
		8.7 Validation of DT Model
	References
Intelligent Feature Engineering for Monitoring Tool Health in Machining
	1 Introduction
		1.1 Focus of This Study
		1.2 Our Propositions
	2 Materials and Experiments
		2.1 Run-to-Failure Tests
		2.2 Tool Wear Measurements
		2.3 Sensory Data Acquisition
	3 Methods
		3.1 Signal Processing
		3.2 Feature Extraction
		3.3 Feature Explanation to Tool Condition
		3.4 Machine Learning for Tool Wear Prediction
	4 Results
		4.1 Signal Processing
		4.2 Feature Extraction
		4.3 Feature Explanation in Relationship to Tool Condition
		4.4 Tool Wear Prediction
	5 Conclusions
	6 Limitations and Future Scope
	References
Experimental Investigation of Process Parameters Effects on Extrusion Blow Molding Process Using Response Surface Methodology for Industry 4.0
	1 Introduction
	2 Central Composite Design Method and Response Surface Methodology
	3 Experimental Design
	4 Materials and Methods
	5 Results and Discussion
	6 Future Scope
	7 Conclusions
	References
Finite Element Analysis and Experimental Investigation of 3D Printed Biomimetic Structures
	1 Introduction
	2 Materials and Method
		2.1 Modeling the Biomimetic Structures
		2.2 FEA Modeling and 3D Printing
		2.3 Compression Test
	3 Results and Discussion
		3.1 FEA Analysis of Biomimetic Models
		3.2 Selection of the Best Biomimetic Design
		3.3 3D Printing of the Marsh Horsetail Structure
	4 Conclusion
	References
Industry 4.0 in Aircraft Manufacturing: Innovative Use Cases and Patent Landscape
	1 Introduction
	2 Evolution of Industry 4.0 (I4.0)
	3 Enabling Technologies for Industry 4.0
		3.1 Industrial Internet of Things (IIoT)
		3.2 IoT Versus IIOT
		3.3 Big Data and Analytics (BDA)
		3.4 Cloud Computing
		3.5 Additive Manufacturing (AM)
		3.6 Horizontal and Vertical Integration
		3.7 Digital Twins (DT)
		3.8 Autonomous Robots
		3.9 Simulations
		3.10 Cyber Security
		3.11 Cyber Physical System
	4 Industry 4.0 for Aircraft Manufacturing
		4.1 IoT Applications for Aircraft Manufacturing
		4.2 Applications of Digital Twin (DT)
		4.3 Additive Manufacturing for Aircraft Production
		4.4 Autonomous Robots for Aircraft Manufacturing
		4.5 Big Data and Analytics (BDA) in Aircraft Manufacturing
	5 Summary of Use Cases of Industry 4.0 Technologies in Aircraft Manufacturing
	6 Challenges in Adoption of Industry 4.0
		6.1 Skill Gap
		6.2 Legacy Systems
		6.3 Data Security
		6.4 Interoperability and Standardization:
		6.5 Regulatory Compliance
	7 Patent Analytics
		7.1 Patent Family
		7.2 Patent Growth
		7.3 Patent by Jurisdiction
		7.4 Top IPC Classification
		7.5 Key Patent Holders
		7.6 Key Observations Based Patent Analytics
	8 Future Developments
		8.1 Generative AI
		8.2 Digital Twins and Simulation
		8.3 Additive Manufacturing (3D Printing)
		8.4 Artificial Intelligence and Machine Learning
		8.5 Edge Commuting
		8.6 Advanced Robotics and Automation
	9 Discussion
	10 Conclusion
	References
Comparative Multi-criteria-Decision Making Approach for the Optimization of Abrasive Water Jet Machining Process Parameters Using MABAC
	1 Introduction
	2 Methodology
		2.1 MABAC Method
		2.2 Weight Allocation of Responses
	3 Results and Discussion
		3.1 MABAC Analysis
		3.2 Correlation of MCDM Techniques:
	4 Conclusion
	5 Future Scope of the Present Work
	References
An Empirical Analysis of Factors Influencing Industry 4.0 Implementation in Manufacturing SMEs
	1 Introduction
	2 Industry 4.0 Maturity Models and Critical Factors
	3 Theoretical Model
	4 Methodology
		4.1 Research Instrument
		4.2 Data Collection
		4.3 Data Analysis and Results
	5 Findings and Discussion
	6 Conclusion and Future Work
	References
A Cost-Minimization Approach to Production and Maintenance Planning Considering Imperfect Repairs and Human Resource Constraints
	1 Introduction
	2 Review of Literature
		2.1 Production and Maintenance Planning with Imperfect Repairs
		2.2 Production and Maintenance Operations with Limitations in Human Resources
	3 Problem Description and Mathematical Modeling
		3.1 Mathematical Modeling
	4 Computational Results
	5 Sensitivity Analyses
	6 Conclusion
	7 Future Research
	Appendix
	References
Environment-Friendly Practices for Integrating Green Business with Green Supply Chain Management: Industry 4.0 Perspectives and Beyond
	1 Introduction
	2 Green Marketing
	3 Green Finance
	4 Green Design
	5 Green Procurement
	6 Green Logistics
	7 Green Manufacturing
	8 Product Recovery
		8.1 Re-manufacturing
		8.2 Recycling
		8.3 Refurbishment
		8.4 Repair
		8.5 Scavenging
	9 Conclusion and Summary
	10 Future Scope of Work
	References
Barrier Analysis for the Sustainable Business Practice of a Textile and Apparel Industry in Fiji Using an ISM Approach
	1 Introduction
	2 Literature Research
		2.1 Sustainable Business Practice (SBP)
		2.2 Small and Medium-Sized Enterprises (SMEs) and Their Importance to SBP
		2.3 Textile and Apparel (TA) Industry in SBP
		2.4 Multi-criteria Decision Approach in SBP of TA Industry
		2.5 Barriers to SBP in the TA Industry
		2.6 Gap Analysis and Research Importance
	3 Research Methodology
		3.1 ISM Approach
	4 Methods Application
		4.1 Data Collection
		4.2 Reachability Matrix and Level Partitions
		4.3 ISM Model and MICMAC Analysis
	5 Results Discussion
	6 Conclusion and Scope for Future Work
	References
Strategic Design Optimization of Cutting Tools for Enhanced Manufacturing Efficiency
	1 Introduction
		1.1 Texturing Techniques and Their Impact
		1.2 Advanced Texturing Patterns
		1.3 Dual Texture Geometries
		1.4 Tool Wear and Machinability
		1.5 Micro-grooved PCD Tools
		1.6 Texturing for Composite Machining
	2 Methodology
	3 Results and Discussion
	4 Conclusion
	5 Future Scope
	References
Exploring the Challenges of Integrating Lean Green Practices in Industry 4.0 Manufacturing Frameworks: An Empirical Study
	1 Introduction
	2 Literature Review
	3 Research Framework and Methodology
	4 Results and Discussion
		4.1 Analytical Hierarchy Process (MCDM Technique)
	5 Conclusions and Limitations
	6 Future Scope
	References
Robotic Arm 3D Printing: Technological Advancements and Applications
	1 Introduction
		1.1 Working Principle and Process of Robotic Arm 3D Printing
	2 Advantages of Robotic Arm 3D Printing
	3 Limitation of Robotic Arm 3D Printing
	4 Leading Companies and Technologies in Robotic Arm 3D Printing
		4.1 ABB Robotics
		4.2 CEAD
		4.3 Kuka
		4.4 Bloom Robotics
		4.5 Branch Technology
	5 Applications of RA3DP
	6 Challenges and Future Perspectives
	7 Conclusion
	References
Elephant Swarm Water Search Algorithm-Based Optimization of a Laser Beam Machining Process
	1 Introduction
	2 Literature Review
	3 Elephant Swarm Water Search Algorithm
	4 Parametric Optimization of an LBM Process
	5 Results and Discussions
	6 Conclusions
	7 Future Scope
	References
Progressive Automation: Mapping the Horizon of Smart Manufacturing with RoboDK Workstations and Industry 4.0
	1 Introduction
		1.1 Overview of Industry 4.0
		1.2 Introduction to RoboDK Workstations
	2 Understanding the Concept of Industry 4.0
	3 The Evolution of Automation in Manufacturing
	4 RoboDK Workstations: Enabling Smart Manufacturing
	5 Implementing RoboDK in Smart Manufacturing
		5.1 Optimizing Production Line with RoboDK Simulations
		5.2 Implementing Collaborative Robots with RoboDK Workstations
		5.3 Pseudo Code Used During Simulation
	6 Challenges and Future Directions
		6.1 Key Challenges in Adopting RoboDK and Industry 4.0 in Manufacturing
		6.2 Strategies for Overcoming Barriers to Implementation
		6.3 Future Trends and Advancements in Smart Manufacturing with RoboDK
	7 Conclusions
	References
Improvising the Quality of Manifold Production Using Six-Sigma Technique for Implementation in Automobile Manufacturing Industries: A Case Study
	1 Introduction
	2 Problem Formulation
	3 Dmaic Analysis and Case Discussion
		3.1 Define
		3.2 Measure
		3.3 Analysis
		3.4 Improve
		3.5 Control
	4 Conclusions and Future Scope
	References
Digital Twin Integration for Enhanced Control in FDM 3D Printing
	1 Introduction
	2 Methodology
		2.1 Modelling Approach
		2.2 Parameterization and Initialization
		2.3 Thermal Simulation Methodology
		2.4 Extrusion and Deposition Modelling
		2.5 Time-Stepping Loop for Simulation
		2.6 Dynamic Adjustment of Extrusion Parameters
	3 Results
	4 Digital Twin Integration for Enhanced Control
	5 Conclusion
	6 Future Scope of Digital Twin Technology in FDM 3D Printing
	References
Intelligent Manufacturing in Aerospace: Integrating Industry 4.0 Technologies for Operational Excellence and Digital Transformation
	1 Introduction
	2 Industry 4.0: A Journey of Transformation
		2.1 The First Industrial Revolution (1760–1840)
		2.2 The Second Industrial Revolution (1870–1914)
		2.3 The Third Industrial Revolution (1960–1990)
		2.4 The Emergence of Cyber-Physical Systems (CPS) (2006–2011)
		2.5 The Advent of the Internet of Things (IoT) (2012–2014)
		2.6 The Rise of Artificial Intelligence (AI) and Machine Learning (ML) (2015–2017)
		2.7 The Integration of Additive Manufacturing (2018–Present)
		2.8 The Future of Industry 4.0 (2022 and Beyond)
	3 Technologies for Industry 4.0
		3.1 Internet of Things
		3.2 Big Data and Analytics (BDA)
		3.3 Additive Manufacturing (AM)
		3.4 Horizontal and Vertical Integration
		3.5 Digital Twins (DT)
		3.6 Autonomous Robots
	4 Industry 4.0 for Aircraft Manufacturing
		4.1 IoT Applications for Aircraft Manufacturing
		4.2 Cyber-Physical Systems
		4.3 Big Data and Analytics (BDA)
		4.4 Cloud Computing
		4.5 Additive Manufacturing (AM)
		4.6 Robotics and Automation
		4.7 Augmented Reality (AR)
		4.8 Simulation and Modeling
		4.9 Cybersecurity
		4.10 Horizontal and Vertical System Integration
		4.11 Digital Twin (DT)
	5 Real Life Examples of Usages of I4.0 Technologies in Aerospace Domain
	6 Challenges in Adoption of Industry 4.0
	7 Future Work
	8 Conclusion
	References