Ganesh M. Kakandikar – författare

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.

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.

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.

Automotive and aerospace components, utensils, and many other products are manufactured by a forming/drawing process on press machines of very thin sheet metal, 0.8 to 1.2 mm. It is imperative to study the effect of all involved parameters on output of this type of manufacturing process. This book offers the readers with application and suitability of various evolutionary, swarm, and bio-inspired optimization algorithms for sheet metal forming processes. Book initiates by presenting basics of metal forming, formability followed by discussion of process parameters in detail, prominent modes of failure, basics of optimization and various bioinspired approaches followed by optimization studies on various industrial components applying bioinspired optimization algorithms.

Key Features:

• Focus on description of basic investigation of metal forming, as well as evolutionary optimization

• Presentation of innovative optimization methodologies to close the gap between those formulations and industrial problems, aimed at industrial professionals

• Includes mathematical modeling of drawing/forming process

• Discusses key performance parameters, such as Thinning, Fracture, and Wrinkling

• Includes both numerical and experimental analysis