Mathematical Engineering, Manufacturing, and Management Sciences Advances in Sustainable Machining Manufacturing Processes

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Bol This text provides an in-depth overview of sustainability in machining processes, challenges during machining of difficult-to-cut materials and different ways of green machining in achieving sustainability. It discusses important topics including green and sustainable machining, dry machining, textured cutting coated tools for machining, solid lubricants-based machining, gas-cooled machining, cryogenic cooling for intelligent machining, artificial neural network for machining, big data based machining, and hybrid intelligent machining. This book- Covers advances in sustainable machining such as gas-cooled machining, near dry machining, and minimum quantity lubrication. Explores use of big data, machine learning and artificial intelligence for machining processes. Provides case studies and experimental design as well as results with analysis focusing on achieving sustainability. Discusses artificial intelligence and machine learning based machining processes. Cover the latest applications of sustainable manufacturing for a better understanding of the concepts. The text is primarily written for senior undergraduate, graduate students, and researchers in the fields of mechanical, manufacturing, industrial, production engineering and materials science.

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This text provides an in-depth overview of sustainability in machining processes, challenges during machining of difficult-to-cut materials and different ways of green machining in achieving sustainability. It discusses important topics including green and sustainable machining, dry machining, textured cutting coated tools for machining, solid lubricants-based machining, gas-cooled machining, cryogenic cooling for intelligent machining, artificial neural network for machining, big data based machining, and hybrid intelligent machining. This book- Covers advances in sustainable machining such as gas-cooled machining, near dry machining, and minimum quantity lubrication. Explores use of big data, machine learning and artificial intelligence for machining processes. Provides case studies and experimental design as well as results with analysis focusing on achieving sustainability. Discusses artificial intelligence and machine learning based machining processes. Cover the latest applications of sustainable manufacturing for a better understanding of the concepts. The text is primarily written for senior undergraduate, graduate students, and researchers in the fields of mechanical, manufacturing, industrial, production engineering and materials science.


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  • 9781000586251
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