Machine Learning Applications in Non-Conventional Machining Processes

Machine Learning Applications in Non-Conventional Machining Processes

Indexed In: SCOPUS
Release Date: February, 2021|Copyright: © 2021 |Pages: 313
DOI: 10.4018/978-1-7998-3624-7
ISBN13: 9781799836247|ISBN10: 179983624X|EISBN13: 9781799836261
Hardcover:
Available
$215.00
TOTAL SAVINGS: $215.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
Hardcover:
Available
$215.00
TOTAL SAVINGS: $215.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
E-Book:
Available
$215.00
TOTAL SAVINGS: $215.00
Benefits
  • Multi-user license (no added fee)
  • Immediate access after purchase
  • No DRM
  • PDF download
E-Book:
Available
$215.00
TOTAL SAVINGS: $215.00
Benefits
  • Immediate access after purchase
  • No DRM
  • PDF download
  • Receive a 10% Discount on eBooks
Hardcover +
E-Book:
Available
$260.00
TOTAL SAVINGS: $260.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
  • Multi-user license (no added fee)
  • Immediate access after purchase
  • No DRM
  • PDF download
Hardcover +
E-Book:
Available
$260.00
TOTAL SAVINGS: $260.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
  • Immediate access after purchase
  • No DRM
  • PDF download
Article Processing Charge:
Available
$1,500.00
TOTAL SAVINGS: $1,500.00
OnDemand:
(Individual Chapters)
Available
$37.50
TOTAL SAVINGS: $37.50
Benefits
  • Purchase individual chapters from this book
  • Immediate PDF download after purchase or access through your personal library
Effective immediately, IGI Global has discontinued softcover book production. The softcover option is no longer available for direct purchase.
Description & Coverage
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.

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 today’s technology-driven market.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Artificial Neural Networks
  • Data Mining
  • Environmental Manufacturing
  • Evolutionary Algorithms
  • Fuzzy Set Theory
  • Hybrid Machining
  • Micro-Machining
  • Optimization Techniques
  • Statistical Learning Algorithms
Table of Contents
Search this Book:
Reset
Editor/Author Biographies

Goutam Kumar Bose is currently working as HOD and Professor in Mechanical Engineering Department, Haldia Institute of Technology, Haldia, India. He obtained his PhD in Production Engineering from the Jadavpur University, Kolkata, India. He has obtained a Master’s in Engineering in Mechanical Engineering from the Bengal Engineering & Science University, Shibpur, India. He has worked as an Assistant Professor in the Department of Mechanical Engineering at the College of Engineering & Management, Kolaghat for ten years. He was an Engineer in R & D Centre of M/s Hindustan Motors Ltd. West Bengal, India. His active areas of interest are Metal Cutting, Non- conventional machining and Industrial and Production Management. He has published research papers in journals of international repute. He has attended several international conferences in India and abroad.

Pritam Pain has completed his B.Tech degree from WBUT in 2014 and then completed his M.Tech degree from Haldia Institute of Technology in 2016. He is currently working as assistant professor in Haldia Institute of Technology. He had several journal papers and book chapters regarding Non-Traditional machining. He is also appointed as a reviewer in many journals. His main interest of research is in nature-inspired modern optimization algorithms.

Abstracting & Indexing
Archiving
All of IGI Global's content is archived via the CLOCKSS and LOCKSS initiative. Additionally, all IGI Global published content is available in IGI Global's InfoSci® platform.