Volume is indexed by Thomson Reuters CPCI-S (WoS). This collection comprises 144 papers which were carefully selected from the over 300 papers submitted for the purposes of this special volume. All of the papers were subjected to peer-review by at least two expert referees.

This volume represents the state-of-the-art knowledge in the area of production and manufacturing engineering and management. The contributions cover such themes as design for manufacture, AMT, manufacturing systems, knowledge-based systems. The text is interspersed with real-life industrial case study experiences, so making explicit the relevance of these research findings to the improvementof current industrial practice.

This book covers the various advanced manufacturing processes employed by manufacturing industries to improve their productivity in terms of socio-economic development. The authors present automated conventional and non-conventional machining techniques as well as virtual machining principles and techniques. Material removal by mechanical, chemical, thermal and electrochemical processes are described in detail. A glossary of key concepts is attached at end of the book.

This collection of 142 papers was carefully selected from the more than 300 papers submitted. All of the papers were subjected to peer-review by at least two expert referees.

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.

Volume is indexed by Thomson Reuters CPCI-S (WoS). This work presents its readers with the most recent advances in the fields of machining and advanced manufacturing technology. It will be of especial valuable to production and research engineers, research students and academics.