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Computational Intelligence in Remanufacturing

Book Description

In attempts to reduce greenhouse gas emissions, many alternatives to manufacturing have been recommended from a number of international organizations. Although challenges will arise, remanufacturing has the ability to transform ecological and business value. Computational Intelligence in Remanufacturing introduces various computational intelligence techniques that are applied to remanufacturing-related issues, results, and lessons from specific applications while highlighting future development and research. This book is an essential reference for students, researchers, and practitioners in mechanical, industrial, and electrical engineering.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
  5. Dedication
  6. Foreword
  7. Preface
    1. INITIATION
    2. THE CHALLENGES IN IMPLEMENTING REMANUFACTURING
    3. SEARCHING FOR A SOLUTION
    4. ORGANIZATION OF THE BOOK
    5. TARGET AUDIENCE OF THIS BOOK
  8. Acknowledgment
  9. Section 1: Introduction
    1. Chapter 1: Introduction to Remanufacturing and Reverse Logistics
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND: REMANUFACTURING
      4. BACKGROUND: REVERSE LOGISTICS
      5. CONCLUSION
    2. Chapter 2: Overview of Computational Intelligence
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. THE USE OF CI IN REMANUFACTURING
      5. CONCLUSION
  10. Section 2: Retrieval
    1. Chapter 3: Used Products Return Pattern Analysis Using Agent-Based Modelling and Simulation
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
    2. Chapter 4: Used Product Collection Optimization Using Genetic Algorithms
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
    3. Chapter 5: Used Product Remanufacturability Evaluation Using Fuzzy Logic
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
    4. Chapter 6: Used Product Pre-Sorting System Optimization Using Teaching-Learning-Based Optimization
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. TEACHING–LEARNING-BASED OPTIMIZATION ALGORITHM
      7. EXPERIMENTAL STUDY
      8. FUTURE TRENDS
      9. CONCLUSION
    5. Chapter 7: Used Product Delivery Optimization Using Agent-Based Modelling and Simulation
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
  11. Section 3: Reproduction
    1. Chapter 8: Post-Disassembly Part-Machine Clustering Using Artificial Neural Networks and Ant Colony Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
    2. Chapter 9: Reprocessing Operations Scheduling Using Fuzzy Logic and Fuzzy MAX-MIN Ant Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
    3. Chapter 10: Reprocessing Cell Layout Optimization Using Hybrid Ant Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
    4. Chapter 11: Re-Machining Parameter Optimization Using Firefly Algorithms
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
  12. Section 4: Redistribution
    1. Chapter 12: Batch Order Picking Optimization Using Ant System
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
    2. Chapter 13: Complex Adaptive Logistics System Optimization Using Agent-Based Modelling and Simulation
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROBLEM STATEMENT
      5. PROPOSED METHODOLOGY
      6. EXPERIMENTAL STUDY
      7. FUTURE TRENDS
      8. CONCLUSION
  13. Section 5: Epilogue
    1. Chapter 14: Conclusions and Emerging Topics
      1. ABSTRACT
      2. INTRODUCTION
      3. OVERVIEW OF THE PREVIOUS CHAPTERS
      4. EMERGING TOPICS IN CI
      5. EMERGING TOPICS IN REMANUFACTURING
  14. Nomenclature
  15. Compilation of References
  16. About the Contributors