Computational Modelling in Industry 4.0: A Sustainable Resource Management Perspective

Preface
Acknowledgements
Contents
About the Editors
1 A Systematic Review on the Emergence and Applications of Industry 4.0
1 Introduction
2 Industry 4.0 Technologies
2.1 Cyber-Physical Systems
2.2 Internet of Things
2.3 Big Data and Analytics
2.4 Artificial Intelligence
2.5 Cybernetics and Human–Machine Interactions
2.6 Blockchain Technology
2.7 Visualization Technology
2.8 Automation and Industrial Robot System
3 Conclusion
References
2 The Implementation Challenges to Circular Economy Via-Sectoral Exploration
1 Introduction
2 Mapping Approach and Themes Identification
3 Food Sector and Its Associated Waste
4 Chemicals Sector
5 Metals and Minerals Sector
6 Electronics Sector and Its E-Waste
7 Buildings and Infrastructure Sector
8 Conclusion
References
3 Challenges in the Virtual Workspace by the Inception of Industry 4.0: A Conceptual Frame Work
1 Introduction
2 Challenges
2.1 Geographic Factors
2.2 Temporal Factors
2.3 Cultural Factors
2.4 Communication Factors
2.5 Technological Factors
2.6 Leadership Factors
2.7 Team-Related Factors
3 Ideas for Future Research
4 Conclusion
References
4 A Cost-Based Optimization Modelling of Solar Power Generation in India for Sustainable Development
1 Introduction
2 Literature Review
3 An Overview on Electricity Energy Demand of India
3.1 Electricity Generation Costs and Data
4 Methodology
4.1 Levelized Cost of Energy Model
4.2 The Goal Programming Approach
5 Optimization Modelling
6 Results and Discussion
7 Conclusion
References
5 The Impact of Carbon Tax Policy in a Multi-Objective Green Solid Logistics Modelling Under Sustainable Development
1 Introduction and Prior-Related Research
2 Mathematical Formulation
2.1 Model Background
2.2 Nomenclature
2.3 Assumption
2.4 Mathematical Model
3 Solution Procedure
3.1 GCM
4 Numerical Experiment
5 Experimental Result and Exploration
5.1 Comparative Study
6 Concluding Remark and Outlook
References
6 Sustainable Connectivity Management via e-SIM Multi Licence-Based Billing
1 Introduction
2 Technical Background
3 Solution Approach
4 Conclusion
References
7 A Sustainable Production Inventory Model with Variable Demand Dependent on Time, Selling Price, and Electricity Consumption Reduction Level
1 Introduction
2 Problem Description
2.1 Notation
2.2 Assumptions
3 Mathematical Representation of the Model
4 Numerical Experiment
5 Sensitivity Analyses and Result Discussion
6 Conclusions
References
8 A Review on Cleaner Technology for Sustainable Industrial Practices: Global and Indian Scenario Genesis of Technologies to Control Pollution
1 Introduction
2 Materials and Methods
3 Classification of Cleaner Production/Technologies
3.1 Processes Reduction–Modification
3.2 Eco-Friendly Products
3.3 Cleaner Production (CP)
3.4 UNIDO-National Cleaner Production Centre (NCPC)
3.5 European Union Directives
3.6 Pollution Prevention (P2)
4 A Scenario of Cleaner Technology in Developing Countries
4.1 Road Map and Diffusion of Cleaner Technology in India
4.2 The Scenario of Cleaner Technology Adoption in Large Scale Industry in India
4.3 The Scenario of Water Pollution Industries in India
4.4 The Scenario of High Energy Consumption and Air Pollution Industry in India
4.5 Air Pollution Control Technology
4.6 Documentation and Reporting
5 Findings and Remarks
6 Future Scope
7 Conclusion
References
9 Big Data Applications in Smart Sustainable Energy Systems and E-Mobility: Review and Case Study
1 Introduction
2 Background
2.1 Scenario of Global Sustainability
2.2 Green Renewable Energy
2.3 Big Data
2.4 The Analytics Procedure
2.5 E—Mobility
3 Literature Review
3.1 Smart Cities
3.2 Power Systems and Smart Grids
3.3 Smart Buildings
3.4 Transport Systems
3.5 Electric Vehicles
3.6 Traffic Flow Predictions
3.7 Smart Manufacturing
3.8 Renewable Power Generation and Forecasting
4 Summary
5 Limitations of Existing Research
6 Scope of Future Work
7 Case Study
7.1 Test System
7.2 Route Selection
7.3 Selection of Time Frames
7.4 Route Congestion Analysis
7.5 Charging Data Assumption
7.6 Route -Wise Charging Data Analysis
7.7 Region Wise Charging Data Analysis
7.8 Predication of Congestion Data—Without Pandemic Conditions
7.9 Route-Wise Congestion Analysis for Without Pandemic Conditions
7.10 Charging Data Assumption—Without Pandemic Conditions
8 Discussion and Conclusion
References
10 Inventory Models with Lot-Size Dependent Discount for Deteriorating Items: Pricing and Inventory Policies
1 Introduction
1.1 Literature Review
2 Assumptions and Notations
3 Problem Definition
4 Mathematical Modeling
4.1 Case I: Inventory Model for Without Ending Inventory
4.2 Case II: Inventory Model with Full Backorder
5 Solution Algorithm
5.1 Algorithm to Achieve Optimal Price and Inventory Policy for Case I
5.2 Algorithm to Achieve Optimal Price and Inventory Policy for Case II
6 Numerical Illustration
7 Sensitivity Inspection
8 Conclusion
Appendix 1
Appendix 2
Appendix 3
References
11 Intuitionistic Fuzzy Inventory Model with Pre-payment Scheme for Damageable Item
1 Introduction
1.1 Identification of Research Gaps
1.2 Objectives of This Chapter
1.3 Outcomes of the Chapter
2 Nomenclatures and Assumptions
2.1 Nomenclatures
2.2 Assumptions
3 Some Important Definitions
3.1 Intuitionistic Fuzzy Number (IFN)
3.2 Triangular Intuitionistic Fuzzy Number (TIFN)
4 Signed Distance Method of Crispification (Chiang et al. 2005)
5 Model Formulation
5.1 Crisp Model
5.2 Concavity Analysis
5.3 Optimality Analysis
5.4 Intuitionistic Fuzzy Model
5.5 Crispified Model
6 Numerical Examples and Result Analysis
6.1 Numerical Examples
6.2 Result Analysis
7 Managerial Insights
8 Conclusions and Future Scopes
References
12 Impact of Blockchain on Retail Supply Chain
1 Introduction
2 Blockchain Technology
3 Blockchain in Retail Supply Chain
3.1 Traceability, Transparency, and Auditability of the Product/ Material
3.2 Enhancing Supply Chain Visibility
3.3 Eliminates High Costs of 3rd Party Payment Processors
3.4 Building Trust Among Supply Chain Participants
4 Conclusion
References
13 Optimization of System Reliability with Time-Dependent Reliability Components in Imprecise Environment Using Hybridized QPSO
1 Introduction
2 Research Gaps
3 Notation and Assumptions
3.1 Notation
3.2 Assumptions
4 Mathematical Foundations
4.1 Relevant Definitions
4.2 Method of Defuzzification of Fuzzy Number
5 Problem Formulation
5.1 The Crisp Model
5.2 The Fuzzy Models
6 Solution Procedure
6.1 Particle Swarm Optimization (PSO)
6.2 Quantum Behaved Particle Swarm Optimization (QPSO)
6.3 Proposed Hybridized QPSO (HQPSO)
7 Numerical Experiments
8 Result Discussions
9 Conclusions and Future Directions
References
14 Mediative Fuzzy Pythagorean Algorithm to Multi-criteria Decision-Making and Its Application in Medical Diagnostic
1 Introduction
2 Basic Notions
2.1 Mediative Fuzzy Logic (MFL)
2.2 Compositional Mediative Fuzzy Medical Knowledge Representation Among (Symptoms, Patient, and Disease)
2.3 Mediative Pythagorean Fuzzy Set
3 Subsisting Approaches to Quantify Correlation Coefficients Designated Over [0, 1]
3.1 Gerstenkorn and Manko Approach
3.2 Xu et al. Approach
3.3 Zeng and Li Approach
3.4 Garg Approach
3.5 Ejegwa et al. Approach
4 Mathematical Formulation of Proposed Method (Correlation Measurement Based on a Mediative Fuzzy Algorithm)
5 Theorem and Properties
6 Comparison of Our Approach With Previous Approaches
7 Illustration of the Proposed Technique in Multi-criteria Decision-Making of Medical Diagnostic
7.1 Algorithm
8 Conclusion
References
15 On the Parametric Representation of Type-2 Interval and Ranking: Its Application in the Unconstrained Non-linear Programming Problem Under Type-2 Interval Uncertainty
1 Introduction
2 The Concept of Type-2 Interval
2.1 Type-2 Interval in Parametric Form:
2.2 Order Relation of Type-2 Intervals:
3 Optimality of Unconstrained Type-2 Interval-Valued Optimization Problem
3.1 Type-2 Interval-Valued Function and Its Parametrized Form
3.2 Standard Form Type-2 Interval-Valued Optimization Problem
4 Optimality Conditions of Unconstrained Type-2 Interval-Valued Optimization Problem
4.1 Necessary Condition
4.2 Sufficient Conditions
5 Application
5.1 Notations
5.2 Assumptions
5.3 Model Formulation
5.4 Numerical Illustration
6 Conclusion
References
16 State of Energy Estimation of Li-Ion Batteries Using Deep Neural Network and Support Vector Regression
1 Introduction
2 Proposed Methodology for SOE Estimation
2.1 DNN Architecture
2.2 SVR Architecture
3 Processing of Data for Training and Validation
3.1 Data Collection
3.2 Training and Validation Dataset
3.3 Evaluation Metrics
4 Results and Discussion
4.1 Case Study 1
4.2 Case Study 2
5 Conclusion
Appendix A
A.1 Modified DNN Algorithm With the Optimization Technique
A.2 Modified υ—SVR Algorithm With the Optimization Technique
Appendix B
B.1 US06 Drive Cycle Velocity Profile
B.2 UDDS Drive Cycle Velocity Profile
B.3 HWFET Drive Cycle Velocity Profile
B.4 LA92 Drive Cycle Velocity Profile
References
17 Transportation and Parking Framework for Pollution-Free AMU Campus: A Case Study
1 Introduction
2 Estimation of Pollutants Emission
2.1 The Campus Map
2.2 Potential Effects of Relocating Parking Lots
3 Smart Parking System Framework
4 Conclusion
References
18 Levelized Cost of Sustainable Electricity Production and Storage in India
1 Introduction
1.1 Current Scenario of the Electricity Sector in India
2 Methodology
3 Levelized Cost of Electricity
3.1 Cost and Technical Parameters of Conventional Sources
3.2 Cost and Technical Parameters of Non-Conventional Sources
4 Levelized Cost of Energy Storage
4.1 Battery Storage
4.2 Levelized Cost of Electricity from Pumped Hydro Storage (PHS)
5 Conclusion and Recommendations
References
19 Application of Principal Component Analysis and Analytical Hierarchical Process in Surface Water Quality Assessment in Hatta Catchment, Emirate of Dubai, UAE
1 Introduction
2 Materials and Methods
2.1 Description of the Study Area
2.2 Water Resources
2.3 Sampling and Analytical Techniques
3 Results and Discussions
3.1 Surface Water Quality Evaluation
3.2 Principal Component Analysis/Factor Analysis
3.3 Cluster Analysis
4 Developing Irrigation Water Quality Index
4.1 Analytical Hierarchical Process
5 Conclusions and Recommendations
References