Computational Intelligence in Manufacturing addresses applications of AI, machine learning and other innovative computational techniques across the manufacturing supply chain. The rapid development of smart or digital manufacturing known as Industry 4.0 has swiftly provided a large number of opportunities for product and manufacturing process improvement. Selecting the appropriate technologies and combining them successfully is a challenge this book helps readers overcome . It explains how to prepare different manufacturing cells for flexibility and enhanced productivity with better supply chain management, e.g., calibrating design machine tools for automation and agility.
Computational intelligence applications for non-conventional manufacturing processes such as ECM and EDM are covered alongside recent advances in traditional processes like casting, welding and metal forming. As well as describing specific applications, this practical guide also explains the computational intelligence paradigm for enhanced supply chain management.
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Dr Kaushik Kumar is an Associate Professor in the Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, India. He has 14 years of experience in teaching and research, and over 11 years of industrial experience working for a global manufacturing company. He has 9 patents, has authored/edited 20 books and has 120 international journal publications, and 18 International and 8 National Conference publications to his credit.
Ganesh Kakandikar is Professor and Associate Head of the School of Mechanical Engineering at Dr. Vishwanath Karad MIT World Peace University, Pune, India. He has an MBA in finance as well as qualifications in production engineering. He has a proven record of Research Publications and Citations, mainly in the areas of advanced manufacturing design and innovation.
Prof. (Dr.) J. Paulo Davim is a Full Professor at the University of Aveiro, Portugal, with over 35 years of experience in Mechanical, Materials, and Industrial Engineering. He holds multiple distinguished academic titles, including a PhD in Mechanical Engineering and a DSc from London Metropolitan University. He has published over 300 books and 600 articles, with more than 36,500 citations. He is ranked among the world's top 2% scientists by Stanford University and holds leadership positions in numerous international journals, conferences, and research projects.
J. Paulo Davim is a Professor in the Department of Mechanical Engineering of the University of Aveiro, Portugal. He has more than 30 years of teaching and research experience in Manufacturing, Materials and Mechanical Engineering with special emphasis in Machining & Tribology. He has also interest in Management & Industrial Engineering and Higher Education for Sustainability & Engineering Education. He has received several scientific awards, has worked as evaluator of projects for international research agencies as well as examiner of Ph.D. thesis for many universities. He is the Editor in Chief of several international journals, Guest Editor of journals, books Editor, book Series Editor and Scientific Advisory for many international journals and conferences. Presently, he is an Editorial Board member of 30 international journals and acts as reviewer for more than 80 prestigious Web of Science journals. In addition, he has also published as editor of more than 100 books and as author of more than 10 books, 60 book chapters and 400 articles in journals and conferences.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational Intelligence in Manufacturing addresses applications of AI, machine learning and other innovative computational techniques across the manufacturing supply chain. The rapid development of smart or digital manufacturing known as Industry 4.0 has swiftly provided a large number of opportunities for product and manufacturing process improvement. Selecting the appropriate technologies and combining them successfully is a challenge this book helps readers overcome . It explains how to prepare different manufacturing cells for flexibility and enhanced productivity with better supply chain management, e.g., calibrating design machine tools for automation and agility. Computational intelligence applications for non-conventional manufacturing processes such as ECM and EDM are covered alongside recent advances in traditional processes like casting, welding and metal forming. As well as describing specific applications, this practical guide also explains the computational intelligence paradigm for enhanced supply chain management. Englisch. Nº de ref. del artículo: 9780323918541
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