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Nature-Inspired Optimization in Advanced Manufacturing Processes and Systems: Artificial Intelligence (AI) in Engineering

Editat de Ganesh M. Kakandikar, Dinesh G. Thakur
en Limba Engleză Paperback – 8 oct 2024
The manufacturing system is going through substantial changes and developments in light of Industry 4.0. Newer manufacturing technologies are being developed and applied. There is a need to optimize these techniques when applied in different circumstances with respect to materials, tools, product configurations, and process parameters.
This book covers computational intelligence applied to manufacturing. It discusses nature-inspired optimization of processes and their design and development in manufacturing systems. It explores all manufacturing processes, at both macro and micro levels, and offers manufacturing philosophies. Nonconventional manufacturing, real industry problems and case studies, research on generative processes, and relevance of all this to Industry 4.0 is also included.
Researchers, students, academicians, and industry professionals will find this reference title very useful.
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Specificații

ISBN-13: 9780367532611
ISBN-10: 0367532611
Pagini: 278
Ilustrații: 240
Dimensiuni: 156 x 234 mm
Greutate: 0.51 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Artificial Intelligence (AI) in Engineering

Locul publicării:Boca Raton, United States

Public țintă

Academic, Professional, Undergraduate Advanced, and Undergraduate Core

Cuprins

1. Optimization of Machining Parameters in CNC Turning/Milling. 2. Optimization of Coating Thickness for Single Point Cutting Tools. 3. Optimization of Surface Finish in Machining Operations. 4. Optimization of Forming Load in Stamping/Forming Processes. 5. Optimization of Spring back in Sheet Metal Forming Processes. 6. Preform optimization in Bulk Forming Process. 7. Optimization of Routing on Shop Floor. 8. Optimization Production, Planning and Control. 9. Optimization of Master Schedule in Manufacturing. 10. Computational Intelligence in Line Balancing. 11. Optimization in Flexible Manufacturing System. 12. Optimization of Robot Path Trajectory in Manufacturing. 13. Optimization of Plant Layout. 14. Optimization of Inventory in Manufacturing System. 15. Supply chain Optimization in Manufacturing. 16. Optimization of Welding Process.17. Maintenance Optimization of Production Systems.

Notă biografică

Ganesh M. Kakandikar is Professor Associate Head of School of Mechanical Engineering at Dr. V. D. Karad MIT World Peace University, Pune. He has completed Ph.D. in Mechanical Engineering from Swami Ramanand Teerth Marathwada University, Nanded in 2014. He has 20 years of experience in Teaching, Research and Administration. He has authored 03 books published internationally by Lambert Academic and CRC Press, Taylor and Francis Group and contributed book chapters published by Wiley, Springer, Elsevier. 65+ publications are at his credit in National/International Journals and conferences. He is reviewer of many reputed journals. He has chaired sessions in various national and international conferences and worked on their advisory committees. His publications have been widely cited by researchers. He is professional member of various society’s including International Society on Multiple Criteria Decision Making, International Society for Structural and Multidisciplinary Optimization and Sheet Metal Forming Research Association. He has executed many research projects with industries especially on optimization of automotive components. He has guided several M.Tech. Thesis and adjudicated many of other universities. He is recipient of many academic and industry awards including Indo Global Engineering Excellence Award – 2015 from Indo Global Chamber of Commerce, Industries and Agriculture for Research Work in Engineering, Cooper Engineering Prize for Best Paper in Mechanical Engineering for paper entitled "Thinning Optimization in Punch Plate using Flower Pollination Algorithm at Annual Technical Paper Meet 2015 of The Institution of Engineers (India) at Pune, Appreciation Award in ANSYS Hall of Fame 2017. He is awardee of Young Scientist International Travel Grant by Government of India. He regularly writes columns in India print media on education systems and reforms.
Dinesh G. Thakur is presently working as Professor in Mechanical Engineering at Defence Institute of Advanced Technology, [Deemed to be University, DRDO Ministry of Defence,] Girinagar, Pune since 2011. He has 20+ years of Teaching, Administrative and Research Experience. He completed his masters and doctorate from Indian Institute of Technology, Madras. Prior 2011 he has worked with Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra. His areas of interest are Manufacturing considerations in Design, High Speed Machining/Green Machining, Metal Forming etc. He has organized 15 short term training programs. He has delivered 65 invited talks in various institutes. He is recipient of many awards as Teacher of the Award 2013 at DIAT, Pune, Member of Board of Management, DIAT, Pune, Member, Academic Council, DIAT, Pune. He has received best paper award World Congress on Engineering 2009 at London. He has been listed in Who’s Who in the World 2010. He is member on various academic and management authorities of many universities/institutes. He is life member of Indian Society for Technical Education, Institution of Engineers, American Society of Mechanical Engineers, Indian Institute of Metals, Aeronautical Society of India, MRSI etc. He is reviewer of many reputed journals. He has guided 35 M. Tech. students and 07 are ongoing. 04 research scholars have been awarded doctorate under his guidance and 04 are presently working. He has visited China, Hongkong, Macau, Singapore, Malaysia, Japan, United Kingdom, Switzerland etc. He has 50+ publications in reputed journals.

Descriere

The manufacturing system is going through substantial changes and developments in the light of industry 4.0. Newer manufacturing technologies are being developed and applied. There is need to optimize these techniques when applied in different circumstances with respect to materials, tools, product configurations, and process parameters.