Overview
- Discusses several advanced manufacturing processes along with mathematical formulations, and includes numerous illustrations
- Offers solutions to the complex parameter optimization of these advanced manufacturing processes using several variants of AI-based, socio-cultural inspired methodology, referred to as cohort intelligence
- Explains variants of the cohort intelligence method and their mathematical formulation, and presents illustrative examples
- Describes the solutions using over 50 experimentally achieved plots, figures, and illustrations, along with over 25 tables
Part of the book series: Springer Series in Advanced Manufacturing (SSAM)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book discusses comprehensively the advanced manufacturing processes, including illustrative examples of the processes, mathematical modeling, and the need to optimize associated parameter problems. In addition, it describes in detail the cohort intelligence methodology and its variants along with illustrations, to help readers gain a better understanding of the framework. The theoretical and statistical rigor is validated by comparing the solutions with evolutionary algorithms, simulation annealing, response surface methodology, the firefly algorithm, and experimental work. Lastly, the book critically reviews several socio-inspired optimization methods.
Authors and Affiliations
About the authors
Aniket Nargundkar holds a Master of Technology (MTech) in Manufacturing Technology from National Institute of Technology, Tiruchirappalli, India, and a Bachelor of Engineering from Shivaji University, India. He has worked as Manufacturing Technologist with Danfoss Industries Pvt Ltd, providing technological and process innovation solutions and executing it with an aim to improve market competitiveness and achieve operational excellence. He has worked in Denmark, Poland, and Mexico over a span of two years, together with professionals from Technology and Innovation, Lean Manufacturing, Production, Procurement & Quality in cross-functional teams, on Manufacturing, Supply Chain Problems & opportunities at Danfoss plants. Currently, he is an Assistant Professor at the Mechanical Engineering Department at Symbiosis Institute of Technology, Symbiosis International (Deemed University) (SIU). He is also pursuing a PhD in Optimization Algorithms and Applications from SIU. His research interests include optimization algorithms and applications, multi-objective optimization, continuous, discrete and combinatorial optimization, multi-agent systems, complex systems, Manufacturing Processes and Technology, Supply Chain Analytics, Mechatronics, and Automation. Aniket has published numerous research papers in top quality peer-reviewed journals, chapters, and international conferences.
Anand J Kulkarni holds a PhD in Distributed Optimization from Nanyang Technological University, Singapore, MS in Artificial Intelligence from University of Regina, Canada, Bachelor of Engineering from Shivaji University, India and Diploma from the Board of Technical Education, Mumbai. He worked as a Research Fellow on a Cross-border Supply-chain Disruption project at Odette School of Business, University of Windsor, Canada. Anand was Head of the Mechanical Engineering Department at Symbiosis International (Deemed University) (SIU), Pune, India for three years. Currently, he is Associate Professor at the Symbiosis Center for Research and Innovation, SIU. His research interests include optimization algorithms, multi-objective optimization, continuous, discrete and combinatorial optimization, multi-agent systems, complex systems, probability collectives, swarm optimization, game theory, self-organizing systems and fault-tolerant systems. Anand pioneered socio-inspired optimization methodologies such as Cohort Intelligence, Ideology Algorithm, Expectation Algorithm, Socio Evolution & Learning Optimization algorithm. He is the founder and chairman of the Optimization and Agent Technology (OAT) Research Lab and has published over 50 research papers in peer-reviewed journals, chapters and conferences along with 3 authored and 5 edited books.
Bibliographic Information
Book Title: Socio-Inspired Optimization Methods for Advanced Manufacturing Processes
Authors: Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni
Series Title: Springer Series in Advanced Manufacturing
DOI: https://doi.org/10.1007/978-981-15-7797-0
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
Hardcover ISBN: 978-981-15-7796-3Published: 12 August 2020
Softcover ISBN: 978-981-15-7799-4Published: 13 August 2021
eBook ISBN: 978-981-15-7797-0Published: 11 August 2020
Series ISSN: 1860-5168
Series E-ISSN: 2196-1735
Edition Number: 1
Number of Pages: X, 128
Number of Illustrations: 23 b/w illustrations, 22 illustrations in colour
Topics: Manufacturing, Machines, Tools, Processes, Artificial Intelligence, Computational Intelligence, Optimization