Digital Transformation and Industry 4.0 for Sustainable Supply Chain Performance

Preface
Acknowledgments
Contents
Big Data Analytics for Supply Chain Transformation: A Systematic Literature Review Using SCOR Framework
1 Introduction
2 Review Methodology
2.1 Material Collection
2.2 Descriptive Analysis
2.3 Article Classification
2.3.1 Classification by SCOR Domains
2.3.2 Classification by Level of Analytics
2.3.3 Classification by SCM Resources
3 Results and Discussions
3.1 BDA Applications in Plan Domain
3.1.1 New Product Development and Innovation
3.1.2 Demand Forecasting
3.2 BDA Applications in Source Domain
3.2.1 Procurement
3.2.2 Supplier Selection
3.3 BDA Applications in Make Domain
3.3.1 Manufacturing Systems
3.3.2 Process Improvement
3.3.3 Maintenance Management
3.3.4 Scheduling and Production Control
3.4 BDA Applications in Deliver Domain
3.4.1 SC Network Management
3.4.2 Order Picking
3.4.3 Inventory Management
3.4.4 Transportation and Logistics
4 SC Visibility, BDA Capability and SC Transformation
4.1 SC Visibility Framework
4.1.1 SC Visibility
4.1.2 BDA Capability
4.1.3 SC Transformation
5 Future Research Directions
5.1 Future Investigations on BDA Applications in the SCOR Domains
5.1.1 Plan Domain
5.1.2 Source Domain
5.1.3 Make Domain
5.1.4 Deliver Domain
5.1.5 Return Domain
5.2 Levels of Analytics Across the SCOR Domains
5.3 SCM Resources
6 Conclusions and Limitations
References
Untitled
Unveiling the Role of Evolutionary Technologies for Building Circular Economy-Based Sustainable Manufacturing Supply Chain
1 Introduction
2 Literature Review on Industry 4.0 - Manufacturing and Circular Economy Concept
2.1 Industry 4.0 (Fourth Industrial Revolution)
2.1.1 Industry 4.0 Design Principles
Interoperability
Virtualization
Decentralization
Capability to Operate in Real Time
Providing Excellent Customer Service
2.1.2 Techniques for Enabling Industry 4.0
Cyber-Physical Systems (CPS)
The Internet of Things (IoT)
Analytics and Data on the Internet of Things (IoT)
Internet of Services
Cloud Technology
Blockchain
Additive Manufacturing (AM)
Artificial Intelligence (AI): Robots
2.1.3 Industry 4.0 Characteristics
Vertical Networking of Smart Production Systems
The Horizontal Integration
Through Engineering Across the Whole Value Chain
Acceleration Through Exponential Technologies
2.1.4 The Industry 4.0 Environment
2.1.5 Benefits from the Application of Industry 4.0 Techniques
Optimized Production
Increased Productivity
Customization of Products and Delivering to a Value-Added End User
Improved Control of Data and Operations
Improved Communication and Collaboration in Supply Chain Management
Reduced Costs
Increased Profit and Shareholder Value
Creating Innovations and Opportunities
2.1.6 Industry 4.0 Challenges
Information Security Risk
Capital Costs and Training
Employment
Privacy
2.2 Manufacturing and the Current Position in the Fourth Industrial Revolution (Industry 4.0)
2.2.1 The Purpose of Manufacturing Industries and Current Position
2.2.2 Challenges of Manufacturing Industries in Adopting Industry 4.0
2.2.3 Manufacturing Process
2.2.4 Supply Chain and Management
2.3 Circular Economy Concept
2.3.1 Importance (Benefits) of Circular Economy Concept
2.3.2 Industry 4.0 Enabling Manufacturing Industries in Adopting CEC in Both Developed and Developing Countries
3 Research Method
3.1 Literature Review
3.1.1 Exploring Industry 4.0 Techniques and Their Applications in Manufacturing Industries for Creating a More Promising Circu...
3.1.2 Adoption of Circular Economy Concept by Manufacturing Companies in Both Developed and Developing Countries
3.1.3 Barriers (Challenges) in Adopting Industry 4.0 That Restricts the Adoption of CEC
3.1.4 Industry Focus Group (IFG)
4 Results and Discussions
4.1 Results from Literature Review
4.2 Results from Industry Focused Group (IFG) in PNG
4.3 Discussions
5 Limitations and Recommendations
6 Conclusion
References
Smart Technologies Interventions for Sustainable Agri-Food Supply Chain
1 Introduction
2 Sustainable Agri-Food Supply Chain
3 Role of Smart Technologies in the Sustainable Agri-Food Supply Chain
3.1 Role of Artificial Intelligence in the Sustainable Agri-Food Supply Chain
3.2 Role of Internet of Things in Sustainable Agri-Food Supply Chain
3.3 Role of Blockchain in the Sustainable Agri-Food Supply Chain
3.4 Role of Robotics in Sustainable Agri-Business Supply Chain
3.5 Role of Sensors in Sustainable Agri-Food Supply Chain
3.6 Role of Wearable Technologies in Sustainable Agri-Food Supply Chain
3.7 Role of 3D Food Printing in Agri-Food Sustainable Supply Chain
4 Review of Literature
5 Methodology
6 Results and Discussion
6.1 Perceived Challenges for Adoption of Smart Technologies
6.2 Perceived Benefits from Smart Technologies
6.2.1 Cost-Efficient
6.2.2 Lead Time Reduction
6.2.3 Decrease Inventory Loss
6.2.4 Responsive
6.2.5 Reduce Uncertainty
6.2.6 Proper Coordination
6.2.7 Reduce Bullwhip Effect
6.2.8 Increase in Whole Supply Chain Surplus
6.2.9 Competitive Advantage
6.2.10 Creating Value for the Consumer
6.2.11 Providing the Longevity
6.2.12 Protecting the Environment
6.2.13 Reducing Waste
6.2.14 Society Upliftment
6.3 Strategies for Implementation of Sustainable Agri-Food Supply Chain
6.3.1 Convincing Stakeholders
6.3.2 Recruiting More Technical Staff
6.3.3 Provide Training to Existing Staff
6.3.4 Profit Distribution Based on Revenue Generation
6.3.5 Focus to Secure the Data
6.3.6 Government Approval
7 Conclusion
Annexure
References
Wireless Sensors´ Location for Smart Transportation in the Context of Industry 4.0
1 Introduction
2 Literature Review
3 Wireless Sensor Networks for Transportation
3.1 Single-Commodity Network Flow
3.2 The Flow Formulation Model with Fuzzy Restriction on the Number of Sinks
3.3 The Flow Formulation Model with Fuzzy Restriction on Budget
3.3.1 Overview on Fuzzy Mathematical Programming
3.4 A Parametric Solution Approach
3.4.1 Solving the Flow Formulation with Restriction on the Number of Sinks
3.4.2 Solving the Flow Formulation Model with Fuzzy Restriction on Budget
3.4.3 An Alternative p-Median Formulation
3.5 Locating Sinks Under Fuzzy Constraints
4 Observability and Sensor Location Problem on Highway Segments
4.1 Problem Statement
4.2 Nonlocal Conservation Law Model
4.2.1 The Microscopic Model for Nonlocal Conservation Law
4.3 Observability of the Traffic Flow System
5 Conclusion
References
Barriers in Smart Green Resilient Lean Manufacturing: An ISM Approach
1 Background Literature
1.1 Smart Manufacturing
1.2 Green Manufacturing
1.3 Resilient Manufacturing
1.4 Lean Manufacturing
2 Research Gaps
3 Barriers to SGRLM
3.1 Lack of Expertise and Training Programs (B1)
3.2 Unsupportive Organization Culture and Resistance to Change (B2)
3.3 Lack of Management Involvement (B3)
3.4 Lack of Time and Resources (B4)
3.5 Financial Constraints (B5)
3.6 Lack of Regulations and Government Support (B6)
3.7 Ineffective Communication(B7)
3.8 Lack of Visibility (B8)
3.9 Customer Unawareness and Low Demand (B9)
3.10 Lack of Planning (B10)
3.11 Lack of Metrics for SGRLM (B11)
3.12 Technological Constraints (B12)
4 Research Methodology
5 Interpretive Structural Modelling (ISM)
5.1 SSIM Development
5.2 Initial Reachability Matrix Formation
5.3 Final Reachability Matrix Formation
5.4 Level Partitions
5.5 Formation of ISM-Based Model
6 MICMAC Analysis
7 Results and Discussion
8 Conclusion
References
Secure Model for Records Traceability in Airline Supply Chain Based on Blockchain and Machine Learning
1 Introduction
2 Related Work
3 Proposed Secure Model for Records Traceability in Airline Supply Chain Based on Blockchain
3.1 Authentication Process for ASCM System
3.2 Consensus Process for ASCM System
3.3 Security Modules for Anomaly Detection and Securing Transactions
4 Discussion and Implications
5 Conclusion
References
The Role of IoT and IIoT in Supplier and Customer Continuous Improvement Interface
1 Introduction
2 Scenario and Background with Building the Interface Model
2.1 TQM Process with PDCA Cycle
2.2 Voice of Producer and Voice of Customer
2.3 Industrial Internet of Things (IIoT) and B2B
2.4 Internet of Things (IoT) and B2C
3 Discussion and Conclusions
References
Customer Relationship Management in the Digital Era of Artificial Intelligence
1 Introduction
2 Literature Review
3 Digital Transformation of Organizations and Sustainability
4 Integration of AI with CRM
5 Application of AI in CRM
6 AI Algorithm and Related Data Mining
7 Optimization of Business Operations Using AI-CRM
7.1 Customer Service and Retention of Customers
7.2 Automate the Routine Tasks
7.3 Guidance to the Sales Team
7.4 Virtual Assistance
7.5 Prioritization, Lead Customization, and Appropriate Representation
8 Examples of AI-CRM
9 Implication of This Study
10 Conclusion
References
Efficient Supplier Selection in the Era of Industry 4.0
1 Introduction
2 Literature Review
2.1 Description of Criteria/Features
3 Supplier Selection Methods in the Era of Industry 4.0
3.1 Selection of Intelligent Suppliers by Multi-agent Theory (Ghadimi et al., 2019)
3.2 Selection of the Suppliers Through Adaptive Fuzzy-Neuro Approach (Zekhnini et al., 2020)
3.3 Selection of Suppliers by Hybrid MCDM Approach (Sachdeva et al., 2019)
3.4 Selection of Suppliers by Hybrid Fuzzy MCDM Approach (Kaya & Aycin, 2021)
3.5 Selection of Green Suppliers by Hybrid Fuzzy MCDM Approach (Çalk, 2021)
3.6 Selection of Sustainable Suppliers by Integrating Rough Fuzzy Approach (Chen et al., 2020)
4 Conclusion and Future Scope
References
A Comparative Approach for Sustainable Supply Chain Finance to Implement Industry 4.0 in Micro-, Small-, and Medium-Sized Ente...
1 Introduction
2 Literature Review
2.1 Industry 4.0 and MSMEs
2.1.1 Roadmap to Implement Industry 4.0 in MSMEs
2.2 Supply Chain Financing and Sustainability
2.3 DEA and Decision-Making Units
2.4 Research Gap
3 Research Method
4 Problem Description and Model Formulation
4.1 Problem Description
4.2 Model Formulation
4.2.1 Notations
5 Numerical Illustrations
5.1 Solution Approach
6 Results and Discussions
7 Managerial Implications
8 Conclusions
Appendix: Amortization Schedule of the Loan Amount Over the Years
References
Artificial Intelligence and Data Science in Food Processing Industry
1 Introduction
2 Related Studies
3 Methodology
4 Applications of AI and Data Science in Food Processing Industry
4.1 Sorting and Packaging of Products
4.2 Decision-Making
4.3 Cleaning, Maintenance, and Sanitation
4.4 New Launches
4.5 Management of Demand-Supply Chain
4.6 Food Hygiene and Safety
4.6.1 Next-Generation Sequencing and Electric Noses
4.7 Food Waste Management
5 Conclusion
References
Industry 4.0-Based Agritech Adoption in Farmer Producer Organization: Case Study Approach
1 Introduction
2 Farmer Producer Organization
3 Agritech Companies
4 Literature Review
4.1 Studies on FPOs
4.2 Agritech Adoption
5 Research Methodology
6 Results and Discussion
7 Conclusions and Policy Implications
References
Index