Computational Intelligence in Manufacturing Woodhead Publishing Reviews: Mechanical Engineering Series
Coordonnateurs : Kumar Kaushik, Kakandikar Ganesh M., Davim J. Paulo
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.
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
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.
J. Paulo Davim is a full professor at the University of Aveiro, Portugal. He is also distinguished as an honorary professor in several universities and colleges in China, India, and Spain. He is the series editor of Elsevier’s Woodhead Publishing Reviews: Mechanical Engineering Series.
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
- Includes hot topics such as augmented and virtual reality applications in manufacturing
- Provides details of computational techniques, such as nature inspired algorithms for manufacturing process modeling
- Gives practical technical advice on how to calibrate processes and tools to work efficiently in an industry 4.0 system
Date de parution : 06-2022
Ouvrage de 224 p.
15.2x22.8 cm
