
Socio-Inspired Optimization Methods for Advanced Manufacturing Processes by Apoorva Shastri
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.
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Industry 4.0 Driven Manufacturing Technologies
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Precision Forging Technology and Equipment for Aluminum Alloy
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Cooperating Robots for Flexible Manufacturing
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Optimization of Manufacturing Processes
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Digital Twins in Manufacturing
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Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods
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Theories, Methods and Numerical Technology of Sheet Metal Cold and Hot Forming
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Re-engineering of Products and Processes
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Technology and Manufacturing Process Selection
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Mass Customization
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Smart Machining Systems
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Cloud Manufacturing
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Changeable and Reconfigurable Manufacturing Systems
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Metal Cutting Theory
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Additive and Subtractive Manufacturing of Composites
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Advanced Design and Manufacturing Based on STEP
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Value Networks in Manufacturing
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Social Manufacturing: Fundamentals and Applications
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Electrically Assisted Forming
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Cybersecurity for Industry 4.0
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Optimisation of Robotic Disassembly for Remanufacturing
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A Practical Guide to Design for Additive Manufacturing
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Intelligent Optimisation with the Bees Algorithm
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Ductile Mode Cutting of Brittle Materials
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Smart Manufacturing Blueprint: Navigating Industry 4.0 Across Diverse Sectors
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Simulation for Industry 4.0
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DigiTwin: An Approach for Production Process Optimization in a Built Environment
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Hybrid Manufacturing Processes
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Analytics for Smart Energy Management
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Machining Dynamics
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The Management of Additive Manufacturing
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Frontiers in Computing Technologies for Manufacturing Applications
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ANEMONA
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Industry 4.0: Managing The Digital Transformation
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Configurable Intelligent Optimization Algorithm
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A Distributed Coordination Approach to Reconfigurable Process Control
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.
| SKU | Unavailable |
| ISBN 13 | 9789811577963 |
| ISBN 10 | 981157796X |
| Title | Socio-Inspired Optimization Methods for Advanced Manufacturing Processes |
| Author | Apoorva Shastri |
| Series | Springer Series In Advanced Manufacturing |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer Verlag, Singapore |
| Year published | 2020-08-12 |
| Number of pages | 128 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |



































