Machine Learning Applications in Non-conventional Machining Processes

Machine Learning Applications in Non-conventional Machining Processes
  • eBook:
    Machine Learning Applications in Non-conventional Machining Processes
  • Author:
    Goutam Kumar Bose, Pritam Pain
  • Edition:
  • Categories:
  • Data:
    May 22, 2020
  • ISBN:
  • ISBN-13:
  • Language:
  • Pages:
    300 pages
  • Format:

Book Description
Traditional machining has many limitations in today's technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine learning and genetic algorithms has recently transformed the manufacturing industry and created countless opportunities in non-traditional machining methods. Significant research in this area, however, is still considerably lacking.


Chapter 1. Parametric Optimization of Dry Laser Cleaning Using Metaheuristics Processes: To Study the Effect of Laser Cleaning Parameters on Surface Temperature Rise and Thermo-Elastic Force
Chapter 2. MCDM-Based Optimization of Performance Characteristics During µEDMing of SS 304
Chapter 3. Multi-Objective Optimization of EDM Process on AISI P-20 Tool Steel Using Multi-Criteria Decision-Making Technique
Chapter 4. Analysis of Performance Characteristics by Firefly Algorithm-Based Electro Discharge Machining of SS 316
Chapter 5. Programming for Machining in Electrical Discharge Machine: A Non-Conventional Machining Technique
Chapter 6. Multi-Objective Optimization in WEDM of Al 7075 Alloy Using TOPSIS and GRA Method
Chapter 7. Experimental Evaluation on Corner Accuracy in WEDM for Aluminium 6061 Alloy
Chapter 8. Evaluation of Surface Roughness in Wire Electrical Discharge Turning Process
Chapter 9. Laser Trepan Drilling of Monel k-500 Superalloy in Low Power Laser Beam Machining
Chapter 10. Experimental Investigation on Laser Transmission Welding of Polycarbonate and Acrylic
Chapter 11. Application of Evolutionary Optimization Techniques Towards Non-Traditional Machining for Performance Enhancement
Chapter 12. Analysis of Non-Traditional Machining Processes Using Machine Learning 
Chapter 13. Role of Non-Traditional Machining Equipment in Industry 4.0
Chapter 14. Finite Element-Based Optimization of Additive Manufacturing Process Using Statistical Modelling and League of Champion Algorithm
Chapter 15. A Novel Approach Towards Selection of Role Model Cluster Head for Power Management in WSN
Chapter 16. Synthesis and Characterization of Nanocomposites for the Application in Hybrid Solar Cell
Chapter 17. Intelligent Investment Approaches for Mutual Funds: An Evolutionary Model

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