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Computational Methods for Optimizing Manufacturing Technology

Book Description

Computational Methods for Optimizing Manufacturing Technology: Models and Techniques contains the latest research developments in manufacturing technology and its optimization, and demonstrates the fundamentals of new computational approaches and the range of their potential application. Including research on topics such as cellular manufacturing systems, evolutionary algorithms, mobile robots, and particle swarm optimization, this book serves as a useful reference for academics, manufacturing and computational science researchers, mechanical, industrial and manufacturing engineers, and professionals in related industries.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  5. Preface
  6. Acknowledgment
  7. Chapter 1: Application of Soft-Computing Methods in Cellular Manufacturing
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. CELL FORMATION PROBLEMS AND SOLUTION METHODOLOGIES
    5. CONCLUSION
    6. FUTURE RESEARCH DIRECTIONS
  8. Chapter 2: Multi-Objective Optimization of Manufacturing Processes Using Evolutionary Algorithms
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. MULTI-OBJECTIVE OPTIMIZATION
    4. 3. EVOLUTIONARY ALGORITHMS
    5. 4. FUTURE DIRECTIONS OF EVOLUTIONARY ALGORITHMS
    6. 5. CONCLUSION
  9. Chapter 3: Self Control and Server-Supervisory Control for Multiple Mobile Robots, and its Applicability to Intelligent DNC System
    1. ABSTRACT
    2. INTRODUCTION
    3. MOBILE ROBOT WITH MULTIPLE PSD SENSORS
    4. BASIC MOTION CONTROL OF MOBILE ROBOT
    5. SELF-CONTROL MODE
    6. EXPERIMENT AND DISCUSSION
    7. SERVER-SUPERVISORY CONTROL MODE
    8. CONCLUSION AND FUTURE WORK
  10. Chapter 4: Online Machining Optimization with Continuous Learning
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. LITERATURE REVIEW
    4. 3. A HEURISTIC BASED ONLINE OPTIMIZATION OF MACHINING PROCESS
    5. 4. OPTIMIZATION PROCEDURE
    6. 5. DESIGN OF VIRTUAL LATHE
    7. 6. ILLUSTRATIVE EXAMPLE
    8. 7. FUZZY SET BASED OPTIMIZATION
    9. 8. OPTIMIZATION WITH CONTINUOUS LEARNING
    10. 9. CONCLUSION
    11. APPENDIX A: SIMPLEX SEARCH ALGORITHM
    12. APPENDIX B: COST EVALUATION FOR CONDUCTING TOOL LIFE TEST
  11. Chapter 5: Computational Techniques in Statistical Analysis and Exploitation of CNC Machining Experimental Data
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BASICS OF DATA GATHERING AND PROCESSING IN CNC MACHINING
    4. 3. STATISTICAL METHODS FOR OBTAINING CNC MACHINING INFORMATION
    5. 4. CONCLUSION AND FUTURE TRENDS
  12. Chapter 6: Application of Particle Swarm Optimization for Achieving Desired Surface Roughness in Tungsten-Copper Alloy Machining
    1. ABSTRACT
    2. INTRODUCTION
    3. PROBLEM FORMULATION
    4. Particle Swarm Optimization
    5. EXPERIMENTAL DETAILS
    6. RESULTS AND DISCUSSION
    7. CONCLUSION
  13. Chapter 7: Models and Optimization Techniques of Machining Parameters in Turning Operations
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. OPTIMIZATION OF MACHINING PARAMETERS IN SINGLE-TOOL TURNING
    5. OPTIMIZATION OF MACHINING PARAMETERS IN PARALLEL TURNING
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. APPENDIX: NOMENCLATURE
  14. Chapter 8: Simulation of Grinding by Means of the Finite Element Method and Artificial Neural Networks
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. MODELING OF GRINDING
    5. FUTURE RESEARCH DIRECTIONS
    6. CONCLUSION
  15. Chapter 9: Application of Taguchi Method with Grey Fuzzy Logic for the Optimization of Machining Parameters in Machining Composites
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. MULTI-RESPONSE OPTIMIZATION USING GREY FUZZY LOGIC
    4. 3. EXPERIMENTAL DETAILS
    5. 4. GREY RELATIONAL ANALYSIS
    6. 5. FUZZY LOGIC
    7. 6. ANALYSIS, RESULTS AND DISCUSSIONS
    8. CONCLUSION
    9. FUTURE RESEARCH DIRECTIONS
  16. Chapter 10: Taguchi, Fuzzy Logic and Grey Relational Analysis Based Optimization of ECSM Process during Micro Machining of E-Glass-Fibre-Epoxy Composite
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. EXPERIMENTAL PLANNING
    4. 3. Results AND DISCUSSIONS
    5. 4. MATHEMATICAL MODELS AND VALIDITY TEST
    6. 5. CONCLUSION
  17. Chapter 11: Modeling and Optimization of Abrasive Water Jet Cutting of Kevlar Fiber-Reinforced Polymer Composites
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. SINGLE-OBJECTIVE OPTIMIZATION
    4. 3. MULTI-OBJECTIVE OPTIMIZATION
    5. 4. DISCUSSION OF RESULTS
    6. 5. CONCLUSION
    7. 6. FUTURE RESEARCH DIRECTIONS
  18. Chapter 12: Developments in Finite Element Technology and Optimization Formulations for Sheet Metal Forming
    1. Abstract
    2. INTRODUCTION
    3. “SOLID-SHELL” FINITE ELEMENT FORMULATIONS
    4. CONCLUSION
  19. Chapter 13: Joining Sheets to Tubular Profiles by Tube Forming
    1. ABSTRACT
    2. INTRODUCTION
    3. EXPERIMENTATION
    4. FINITE ELEMENT SIMULATION
    5. RESULTS AND DISCUSSION
    6. FUTURE RESEARCH DIRECTION
    7. CONCLUSION
  20. Chapter 14: Modeling and Optimization of Gas Metal Arc Welding (GMAW) Process
    1. ABSTRACT
    2. INTRODUCTION
    3. MODELING AND OPTIMIZATION OF GMAW PROCESS PARAMETERS
    4. CONCLUDING REMARKS
  21. Chapter 15: A Tutorial to Developing Statistical Models for Predicting Disqualification Probability
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. ASSUMPTIONS AND DEFINITIONS
    5. THE DATA SETS
    6. THE STEPS OF MODELING
    7. DISCUSSION
    8. CONCLUSION
  22. Compilation of References
  23. About the Contributors
  24. Index