Operations Management and Data Analytics Modelling Economic Crises Perspective 1st Edition By Lalit Kumar Awasthi, Sushendra Kumar Misra, Dilbagh Panchal, Mohit Tyagi 1032020598 9781032020594

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ISBN 10: 1032020598

ISBN 13: 9781032020594

Author: Lalit Kumar Awasthi, Sushendra Kumar Misra, Dilbagh Panchal, Mohit Tyagi

Operations Management and Data Analytics Modelling: Economic Crises Perspective addresses real operation management problems in thrust areas like the healthcare and energy management sectors and Industry 4.0. It discusses recent advances and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling and Lean Six Sigma. Features Discusses the importance of data analytics in industrial operations to improve economy Provides step-by-step implementation of operation management models to identify best practices Covers in-depth analysis using data-based operation management tools and techniques Discusses mathematical modelling for novel operation management models to solve industrial problems This book is aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering and materials science.

Operations Management and Data Analytics Modelling Economic Crises Perspective 1st Table of contents:

1 Measuring Banking Sector Efficiency: A Malmquist Approach

Introduction

1.2 Review of Studies and Research to Measure Performance and Efficiency Levels of Banking Organizations

1.3 Objectives of the Study

1.4 Hypothesis of the Study

1.5 Research Methodology

1.5.1 Technological Change and Technical Efficiency Change

Statistical Analysis Using R package

1.5.2 Index for Measuring Total Factor Productivity Change and its Disaggregated Components

1.6 Results and Discussion

1.7 Conclusion

References

2 A Hybrid MCDM Model Combining Entropy Weight Method with Range of Value (ROV) Method and Evaluation Based on Distance from Average Solution (EDAS) Method for Supplier Selection in Supply Chain Management

Introduction

2.2 Literature

2.2.1 Entropy Weight Method

2.2.2 Evaluation Based on Distance from Average Solution Method

2.2.3 Range of Value Method

2.3 Illustrative Example

2.3.1 Implementation of EWM Method

2.3.2 Implementation of EDAS Method for Ranking of Supplier

2.3.3 Implementation of ROV Method for Ranking of Supplier

2.4 Results

2.5 Conclusion

References

3 Quality Loss Function Deployment in Fused Deposition Modelling

Introduction

3.2 Research Background

3.3 Research Methods

3.3.1 Quality Loss Function

3.3.2 Response Surface Methodology

3.4 Research Gap

3.5 Methodology

3.5.1 Experimentation Details

3.5.2 Design of Test Specimen

3.5.3 Process Details

3.5.4 Testing

3.5.5 Data Processing

3.5.5.1 Loss Function

3.5.5.2 Response Surface Methodology

3.6 Results and Discussion

3.7 Conclusion

References

4 Effect of Physical Attributes of Coconut on Effective Husk Separation: A Review

Introduction

4.1.1 Background

4.1.2 Research Objectives

4.2 Methods

4.2.1 Review Strategy

4.2.2 Screening

4.2.3 Data Extraction

4.3 Results and Discussion

4.3.1 Search Results

4.3.2 Physical Attributes of Coconut

4.3.3 Analysis of Coconut Husking Mechanisms

4.3.4 Implementation of Coconut Physical Attributes Into Husking Mechanisms

4.4 Conclusion

References

5 Selection of Features and Classifier for Controlling Prosthetic Devices

Introduction

5.2 Methodology

5.2.1 Data acquisition

5.2.1.1 Electrodes

5.2.1.2 Rectifier and Filter

5.2.2 Feature Extraction

5.3 Results

5.3.1 Result of ANOVA Techniques

5.3.2 Result of Classifier

5.4 Conclusion

References

6 An Intelligent Solution for E-Waste Collection: Vehicle Routing Optimization

Introduction

6.2 Problem Description and Modelling

6.2.1 Hybrid GA-ACO Algorithm

6.3 Simulation

6.4 Results and Discussion

6.5 Conclusion

6.6 Acknowledgement

References

7 Identification of Most Significant Parameter in Estimation of Solar Irradiance at Any Location: A Review

Introduction

7.2 ANN Methods of Estimation of Solar Energy

7.3 Parameters and Data Collection

7.3.1 Pressure

7.3.2 Air Quality Index

7.3.2.1 National Air Quality Index in India

7.4 Linear Model of GSR Estimation

7.5 Conclusion and Future Scope

References

8 Assessment of Sustainable Product Returns and Recovery Practices in Indian Textile Industries

Introduction

8.2 Literature Review

8.3 Research Methodology

8.4 Analysis and Discussion

8.5 Conclusion

References

9 Integrating Reliability-Based Preventive Maintenance in Job Shop Scheduling: A Simulation Study

Introduction

9.2 Research Background

9.3 Job Shop Configuration

9.3.1 Job Data

9.3.2 Reliability-Centered Preventive Maintenance Approach

Notation

9.3.3 Mean Inter-Arrival Time

9.3.4 Due Date of Jobs

9.4 Simulation Model Configuration

9.4.1 Performance Measures

9.5 Experimental Design for a Simulation Study

9.6 Simulation Results and Analysis

9.7 Conclusions

References

10 Prioritizing Circular Economy Performance Measures: A Case of Indian Rubber Industries

Introduction

10.2 Literature Survey

10.3 Methodology

10.4 Results and Discussion

10.5 Conclusion and Future Scope

References

11 Fuzzy FMEA Application in the Healthcare Industry

Introduction

11.2 Notion of Fuzzy Set

11.2.1 Fuzzy and Crisp Numbers

11.2.2 Membership Function

11.3 FMEA Approach

11.4 Case Study

11.4.1 Application of FMEA and Fuzzy FMEA

11.5 Results and Discussions

11.6 Conclusion

References

12 Drivers of Industry 4.0 in a Circular Economy Initiative in the Context of Emerging Markets

Introduction

12.2 Literature Review

12.3 Solution Methodology

12.3.1 Structural Self-Interaction Matrix (SSIM)

12.3.2 Reachability Matrix

12.3.3 Partition of Drivers in Levels

12.3.4 Formation of ISM Model

12.3.5 MicMac Analysis

12.4 Results and Discussion

12.5 Implications of the Study

12.6 Conclusion

References

13 Strategies to Manage Perishability in a Perishable Food Supply Chain

Introduction

13.2 Literature Review

13.2.1 Descriptive Analytics

13.2.2 Bibliometric Analysis

13.3 Theoretical Background

13.4 Case Study

13.4.1 Managing the PFSC

13.5 Conclusion

References

14 Six Sigma: Integration with Lean and Green

Introduction

14.2 Definitions of Lean and Six Sigma

14.2.1 Lean

14.2.1.1 Lean Integration with Green

14.2.2 Six Sigma

14.2.2.1 Definitions of Six Sigma

14.2.2.2 Six Sigma Integration with Lean

14.3 Methodologies for Six Sigma

14.3.1 DMAIC (Define, Measure, Analyze, Improve and Control)

14.3.1.1 Define

14.3.1.2 Measure

14.3.1.3 Analyze

14.3.1.4 Improve

14.3.1.5 Control

14.4 Organization of Six Sigma Project Members

14.5 Integration of Green, Lean and Six Sigma (GLSS)

14.5.1 Integration of Lean and Six Sigma

14.5.2 Integration of Green Lean Six Sigma

14.5.3 Conceptual Frameworks of GLSS

14.5.3.1 Automobile Sector

14.5.3.2 Jute Industry

14.5.3.3 Construction Sector

14.6 Conclusion

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