Operations Management and Data Analytics Modelling: Economic Crises Perspective

Description

This reference text addresses real operation management problem in the thrust areas like health care sector, energy management sector, and industry 4.0. It discusses recent advances and trends in developing the data driven operation management based methodologies, big data analysis, application of computer in industrial engineering, optimization techniques, development of decision support system for industrial operation, role of multi-criteria-decision-making (MCDM) approach in operation management, fuzzy set theory based operation management modeling and lean six sigma. Aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering, and materials science, this text: Discusses importance of data analytics in industrial operation for improving economy. Provides step-by-step implementation of operation management models for identifying best practices. Covers in-depth analysis using data-based operation management tools and techniques. Discusses mathematical modelling for novel operation management models for solving industrial problems. Cover Half Title Title Page Copyright Page Dedication Table of Contents Preface Contributors Organization of the Book Brief Introduction of Editors 1 Measuring Banking Sector Efficiency: A Malmquist Approach 1.1 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 2.1 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 3.1 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 4.1 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 5.1 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 6.1 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 7.1 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 8.1 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 9.1 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 10.1 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 11.1 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 12.1 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 13.1 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 14.1 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 References Index