Sustainable Manufacturing in Industry 4.0: Pathways and Practices

Preface
Contents
About the Editors
A Review of Global Research Trends on Sustainable Manufacturing
1 Introduction
2 Methods
2.1 Criteria for the Review
2.2 Search Approaches for the Selection
3 Results and Discussion
3.1 Past and Present Progress of Research Interest
3.2 Core Contributing Countries
3.3 Core Contributing Journals
3.4 Core Contributing Academic Institutions
3.5 Core Contributing Authors
3.6 Common Terminology, Research Topics and In-Depth Insights
4 Conclusion
References
An Analysis of the Literature on Industry 4.0 and the Major Technologies
1 Introduction
2 Methods
2.1 Search Strategy and Data Collection
2.2 Bibliometric Maps and Analysis
3 Results and Discussion
3.1 Historical and Cumulative Growth Trend
3.2 Contributing Countries on the Topic of Concern
3.3 Core Journals, Articles, and Academic Institutions
3.4 Author's Contribution to the Development of the Topic
3.5 Common Terminology and Distribution of I4.0 Publications Based on Major Technologies
4 Limitations and Conclusion
References
Smart Laser Welding: A Strategic Roadmap Toward Sustainable Manufacturing in Industry 4.0
1 Introduction
2 Real-Time Monitoring for Smart Welding
2.1 Intelligent Laser Welding Monitoring
2.2 In-Process Monitoring for Sustainable Manufacturing
3 Robots in Welding
4 Smart Decisions in Manufacturing
5 Digital Twins, Big Data, and Connection Interfaces in Laser Welding 4.0
6 Intelligent Manufacturing
7 Sustainable Manufacturing and Laser Welding
8 Conclusion and Future Research Opportunities
References
The Role of Additive Manufacturing in the Age of Sustainable Manufacturing 4.0
1 Introduction
2 Additive Manufacturing Materials
2.1 Shape Memory Alloys
2.2 Shape Memory Polymers
2.3 Other AM Materials
3 Advanced Additive Manufacturing Processes
3.1 FDM
3.2 Powder Bed Fusion
3.3 Inkjet Printing and Contour Crafting
3.4 SLA
3.5 DED
4 Interrelationship Between Additive Manufacturing and Industry 4.0 Components
4.1 The Relationship Between IoT and AM
4.2 The Role of Big Data Analytics in Additive Manufacturing
4.3 The Use of Cloud Computing in Additive Manufacturing
4.4 Industrial Autonomous Robots and Additive Manufacturing
5 Sustainable Manufacturing
6 Challenges, Drawbacks, and Limitations of AM
7 Summary and Future Expectations
References
The Impact of the Fourth Industrial Revolution on the Transitory Stage of the Automotive Industry
1 Introduction
2 Evolution of Embedded Systems to Cyber-Physical Systems in the Automotive Industry Through Industry 4.0
2.1 Robots in the Automotive Manufacturing
2.2 The Value of Additive Manufacturing/3D Printing in the Automotive Industry
2.3 The Internet of Things (IoT) Trends in the Automotive Industry
2.4 Impact of Big Data and Analytics on Automotive Industry
2.5 Blockchain and the Automotive Industry
2.6 How Virtual and Augmented Reality Are Changing the Automotive Industry
2.7 Artificial Intelligence and Deep Learning in the Automotive Industry
3 Sustainable Development in the Automotive Industry
4 Challenges of the Digital Transformation of the Automotive Industry
5 Summary
References
Advances in Smart Maintenance for Sustainable Manufacturing in Industry 4.0
1 Introduction
2 Time-Based and Condition-Based Maintenance
2.1 Time-Based Maintenance (TBM) «Systematic Maintenance»
2.2 Condition-Based Maintenance (CBM)
3 Preventive Versus Predictive Maintenance
3.1 Preventive Maintenance (PM)
3.2 Predictive Maintenance (PdM)
4 Prognostics and Health Management (PHM)
4.1 PHM Concept
4.2 PHM for the Manufacturing Industry
5 Maintenance 4.0 Tools
5.1 Cyber-Physical Systems (CPS)
5.2 Internet of Things (IoT)
5.3 Big Data
5.4 Artificial Intelligence (AI)
5.5 Connection Interfaces
6 Digital Twins and Real-Time Monitoring, Tools of Efficient Production Management
6.1 Digital Twin's History
6.2 Digital Twins Concept
6.3 Advantages of Digital Twins s for Manufacturing Industries
7 Manufacturing and Maintenance at the Heart of Sustainability
7.1 Sustainable Manufacturing
7.2 Sustainable Maintenance as Part of Sustainable Manufacturing
8 Challenges and Future Directions
References
Smart Inspection; Conceptual Framework, Industrial Scenarios, and Sustainability Perspectives
1 Introduction
2 Data Acquisition Methods
3 Quality Control Based on 3D Geometrical Inspection
4 CAD Model and Scan Data Registrations
4.1 Rigid Registration
4.2 Non-rigid Registration
5 Intelligent Factory Based on Computer-Aided Inspection (CAI)
5.1 Digital Twins (DT)
5.2 The Internet of Things (IoT)
5.3 Sustainable Inspection
6 Conclusion
References
Sustainability Implications of Adopting Industry 4.0 at Different Scales in the Poultry Processing Industry
1 Introduction
2 Traditional Poultry Processing
2.1 Transportation of Bird
2.2 Unloading and Pre-slaughter
2.3 Slaughtering and Processing
2.4 Carcass Processing
2.5 Packaging
3 Industry 4.0 Advances in Poultry Processing
3.1 Transportation of Birds
3.2 Automated Killing and Evisceration Lines
3.3 Portioning and Cutting
3.4 Automated Hyperspectral-Based Inspection System with Smart Sensors
3.5 Packaging
4 Sustainability Implications for Transition to Industry 4.0
4.1 Overview and Scenario Selections
4.2 Techno-Environmental Impact Assessment
4.3 Techno-Economic Sustainability Analysis
4.4 Discussion
5 Conclusion
References
Horizontal Collaboration Business Model Towards a Sustainable I4.0 Value Creation
1 Introduction
2 Supply Chain Horizontal Collaboration
3 Business Model Research Framework
3.1 Content Component
3.2 Structure Component
3.3 Governance Component
4 Multi-criteria Decision-Making Techniques (MCDM)
4.1 Criterion Weight
4.2 Analytic Hierarchical Process (AHP)
4.3 Hesitant Fuzzy Linguistic Sets (HFTLS)
4.4 Combinative Distance-Based Assessment (CODAS)
4.5 Distance Measures Between Two Sets
5 CODAS-HFTLS-Mahalanobis Framework
5.1 CODAS-HFLTS for Identifying Hierarchical HC Factors with Proposed Mahalanobis Distance
5.2 Mahalanobis Distance
5.3 Sensitivity Analysis
6 COHRV Business Model for a Value Creation Network
6.1 Content Component
6.2 Structure Component
6.3 Governance Component
7 Conclusions
References
Assessment of Industry 4.0 Adoption for Sustainability in Small and Medium Enterprises: A Fermatean Approach
1 Introduction
2 Industry 4.0 Adoption Indicators for Sustainability
2.1 Profitability
2.2 Emissions Reduction
2.3 Economic Development
2.4 Business Model Innovation
2.5 Human Resource Development
2.6 Sustainable Resources Development
2.7 Efficiency and Productivity
2.8 Ecological Responsibility
2.9 Flexible and Agile Production
2.10 Social Welfare Improvement
2.11 Job Creation
2.12 Manufacturing Cost Reduction
2.13 Modularized Production
2.14 Security Improvement
2.15 Personalization
2.16 Supply Chain Digitization and Integration
3 Methodology
3.1 Preliminaries
3.2 Proposed FF-CRITIC-TOPSIS
4 Results
5 Sensitivity Analysis
6 Discussion
7 Conclusions
References