SpringerBriefs in Computational Intelligence

Modelling and Optimisation of Laser Assisted Oxygen (LASOX) Cutting: A Soft Computing Based Approach

Authors: Chaki, Sudipto, Ghosal, Sujit

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  • Presents the basics, advantages and shortcomings of the LASOX cutting process, together with research on modelling and optimizing it
  • Introduces two integrated soft computing-based models consisting of Artificial Neural Networks
  • Includes a detailed discussion on the basic working algorithms of soft computing tools
  • Illustrates the practical implementation of the proposed models
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  • ISBN 978-3-030-04903-4
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About this book

This book presents the basics of the Laser Assisted Oxygen (LASOX) cutting process, its development, advantages and shortcomings, together with detailed information on the research work carried out to date regarding the modelling and optimization of the process. It introduces two integrated soft computing-based models consisting of Artificial Neural Networks (ANN-GA and ANN SA) for the modelling and optimization of LASOX cutting. It also includes an in-depth discussion on the basic working algorithms of soft computing tools such as Artificial Neural Networks, Genetic Algorithms, Simulated Annealing etc. The book not only provides an approach to optimizing LASOX by means of soft computing-based integrated models, but also illustrates the practical implementation of the proposed models.

About the authors

Sudipto Chaki received his B.Tech. degree in Mechanical Engineering from North Eastern Regional Institute of Science and Technology, Itanagar, India in 2003, his M.Tech. degree in Manufacturing Technology from the National Institute of Technical Teachers’ Training and Research, Kolkata, India in 2007, and his Ph.D. in Engineering from Jadavpur University in 2013. He is presently working as an Associate Professor and Head of the Automobile Engineering Department at MCKV Institute of Engineering, West Bengal, India. He has published 28 research papers so far, in national and international journals and conference proceedings. His research interests include applications of Soft Computing techniques for the modelling and optimization of manufacturing processes.

Sujit Ghosal received his B.Eng. degree in Mechanical Engineering from Jadavpur University, India in 1976, his M.Tech. degree in Mechanical Engineering from the same institute in 1988, and his Ph.D. in Engineering from the Indian Institute of Technology, Kharagpur, India in 1993. He retired as a Professor at the Mechanical Engineering Department of Jadavpur University, India in 2018 and at present working as Professor, Mechanical Engineering Department, Netaji Subhas Engineering College, Garia, Kolkata, India. He has more than 25 years of teaching and research experience and has published large number of research papers in national and international journals and conference proceedings. He is also working as a technical advisor for various Government and multi-national organizations. His research interest includes CFD, droplet combustion, optimization and hydraulic systems.

Table of contents (3 chapters)

Table of contents (3 chapters)
  • LASOX Cutting: Principles and Evolution

    Pages 1-12

    Chaki, Sudipto (et al.)

  • Integrated Soft Computing Based Methodologies for Modelling and Optimisation

    Pages 13-33

    Chaki, Sudipto (et al.)

  • Modelling and Optimisation of LASOX Cutting of Mild Steel: A Case Study

    Pages 35-56

    Chaki, Sudipto (et al.)

Buy this book

eBook $54.99
price for USA in USD
  • ISBN 978-3-030-04903-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • Immediate eBook download after purchase and usable on all devices
  • Bulk discounts available
Softcover $69.99
price for USA in USD
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Bibliographic Information

Bibliographic Information
Book Title
Modelling and Optimisation of Laser Assisted Oxygen (LASOX) Cutting: A Soft Computing Based Approach
Authors
Series Title
SpringerBriefs in Computational Intelligence
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
The Author(s), under exclusive license to Springer Nature Switzerland AG
eBook ISBN
978-3-030-04903-4
DOI
10.1007/978-3-030-04903-4
Softcover ISBN
978-3-030-04902-7
Series ISSN
2625-3704
Edition Number
1
Number of Pages
IX, 56
Topics