ENGLISH

Machine Learning Applications in Non-Conventional Machining Processes (Advances in Computational Intelligence and Robotics, 1)

By Pritam Pain (editor)

Book information

Publisher
IGI Global
ISBN
9781799836247, 9781799836254, 9781799836261, 9781799832386, 9781799847038, 9781799848738, 9781799866909, 9781799838418, 9781799866978, 9781799833352, 179983624X
Language
english
Format
PDF
Filesize
21 MB (21684330 bytes)
Pages
313\339
Library
Mobilism
Time added
2023-07-11 03:42:07

Description

Traditional machining has many limitations in todays 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. Machine Learning Applications in Non-Conventional Machining Processes is a collection of innovative research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field. While highlighting topics including evolutionary algorithms, micro-machining, and artificial neural networks, this book is ideally designed for researchers, academicians, engineers, managers, developers, practitioners, industrialists, and students seeking current research on intelligence-based machining processes in todays technology-driven market. Title Page Copyright Page Book Series Editorial Advisory Board Table of Contents Detailed Table of Contents Foreword Preface Acknowledgment Chapter 1: Parametric Optimization of Dry Laser Cleaning Using Metaheuristics Processes 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 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 Compilation of References About the Contributors Index Пустая страница

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