Kumar / Kakandikar / Davim | Computational Intelligence in Manufacturing | Buch | 978-0-323-91854-1 | sack.de

Buch, Englisch, 224 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 1000 g

Kumar / Kakandikar / Davim

Computational Intelligence in Manufacturing


Erscheinungsjahr 2022
ISBN: 978-0-323-91854-1
Verlag: William Andrew Publishing

Buch, Englisch, 224 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 1000 g

ISBN: 978-0-323-91854-1
Verlag: William Andrew Publishing


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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Weitere Infos & Material


1. Multiverse multiobjective optimization of thinning and wrinkling in automotive connector 2. An approach for machining curve cooling hole in plastic injection mold 3. Experimental and numerical investigation of deformation and forming behavior of dual-phase steel (DP 590) at elevated temperatures 4. Optimization of thermal efficiency of Scheffler solar concentrator receiver using slime mold algorithm 5. Study on drilling behavior of polymer nanocomposites modified by carbon nanomaterial with fiber: A case study 6. Machining performance analysis of micro-ED milling process of titanium alloy (Ti-6Al-4V) 7. Computational analysis of provisional study on white layer properties by EDM vs. WEDM of aluminum metal matrix composites 8. Scope of industry 4.0 components in manufacturing SMEs 9. Process parameter optimization in manufacturing of root canal device using gorilla troops optimization algorithm 10. A comprehensive review of agriculture irrigation using artificial intelligence for crop production


Kakandikar, Ganesh M.
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.

Davim, J. Paulo
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 an h-index of 99+ on Google Scholar and 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.

Kumar, Kaushik
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.


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