The text comprehensively focuses on the concepts, implementation, and application of evolutionary algorithms for predicting, modeling, and optimizing the various material removal processes from their origin to the current advancements. This one-of-a-kind book encapsulates all the features related to the application and implementation of evolutionary algorithms for the purpose of predicting and optimizing the process characteristics of different machining methods and their allied processes that will provide comprehensive information. It broadly explains the concepts of employing evolutionary algorithm-based optimization in a broad domain of various material removal processes. Therefore, this book will enable prospective readers to take full advantage of recent findings and advancements in the fields of traditional, advanced, micro, and hybrid machining, among others. Moreover, the simplicity of its writing will keep readers engaged throughout and make it easier for them to understand the advanced topics. The book- • Offers a step-by-step guide to implement evolutionary algorithms for the overall optimization of conventional and contemporary machining processes • Provides in-depth analysis of various material removal processes through evolutionary optimization • Details an overview of different evolutionary optimization techniques • Explores advanced processing of various engineering materials-based case studies It further discusses different nature-inspired algorithms-based modeling, prediction, and modeling of machining responses in attempting advanced machining of the latest materials and related engineering problems along with case studies and practical examples. It will be an ideal reference text for graduate students and academic researchers working in the fields of mechanical engineering, aerospace engineering, industrial engineering, manufacturing engineering, and materials science.

Optimization is central to any problem involving decision-making in engineering. Optimization theory and methods deal with selecting the best option regarding the given objective function or performance index. New algorithmic and theoretical techniques have been developed for this purpose, and have rapidly diffused into other disciplines. As a result, our knowledge of all aspects of the field has grown even more profound. In Optimization for Engineering Problems, eminent researchers in the field present the latest knowledge and techniques on the subject of optimization in engineering. Whereas the majority of work in this area focuses on other applications, this book applies advanced and algorithm-based optimization techniques specifically to problems in engineering.

Continuous improvements in machining practices have created opportunities for businesses to develop more streamlined processes. This not only leads to higher success in day-to-day production, but also increases the overall success of businesses. Non-Conventional Machining in Modern Manufacturing Systems provides emerging research exploring the theoretical and practical aspects of technological advancements in industrial environments and applications in manufacturing. Featuring coverage on a broad range of topics such as optimization techniques, electrical discharge machining, and hot machining, this book is ideally designed for business managers, engineers, business professionals, researchers, and academicians seeking current research on non-conventional and technologically advanced machining processes.

We are delighted to present the proceedings of the 5th International Conference on Advances in Additive Manufacturing Technologies (ICAAMT 2023). This conference serves as a premier forum for researchers, practitioners, and industry experts to share their latest findings, innovations, and insights in the field of additive manufacturing. The rapid advancements and the increasing adoption of these technologies across various sectors underscore the importance of this gathering. The conference was held from November 27-29, 2023, in Chennai, India and organized by the Department of Mechanical Engineering, Chennai Institute of Technology, Chennai, India.

Green manufacturing has developed into an essential aspect of contemporary manufacturing practices, calling for environmentally friendly and sustainable techniques. Implementing successful green manufacturing processes not only improves business efficiency and competitiveness but also reduces harmful production in the environment. The Handbook of Research on Green Engineering Techniques for Modern Manufacturing provides emerging perspectives on the theoretical and practical aspects of green industrial concepts, such as green supply chain management and reverse logistics, for the sustainable utilization of resources and applications within manufacturing and engineering. Featuring coverage on a broad range of topics such as additive manufacturing, integrated manufacturing systems, and machine materials, this publication is ideally designed for engineers, environmental professionals, researchers, academicians, managers, policymakers, and graduate-level students seeking current research on recent and sustainable practices in manufacturing processes.

This volume constitutes the thoroughly refereed post-conference proceedings of the 5th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2014, held in Bhubaneswar, India, in December 2014. The total of 96 papers presented in this volume was carefully reviewed and selected from 250 submissions for inclusion in the proceedings. The papers cover a wide range of topics in swarm, evolutionary, memetic and other intelligent computing algorithms and their real world applications in problems selected from diverse domains of science and engineering.

This book comprises select peer-reviewed papers presented at the International Conference on Advanced Engineering Optimization Through Intelligent Techniques (AEOTIT) 2018. The book combines contributions from academics and industry professionals, and covers advanced optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil, automobile, electrical, chemical, computer and electronics engineering. Different optimization techniques and algorithms such as genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), particle swarm optimization (PSO), artificial bee colony (ABC) algorithm, artificial immune algorithm (AIA), teaching-learning-based optimization (TLBO) algorithm and many other latest meta-heuristic techniques and their applications are discussed. This book will serve as a valuable reference for students, researchers and practitioners and help them in solving a wide range of optimization problems.