Traditional machining has many limitations in today's technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine learning and genetic algorithms has recently transformed the manufacturing industry and created countless opportunities in non-traditional machining methods. Significant research in this area, however, is still considerably lacking. Machine Learning Applications in Non-Conventional Machining Processes is a collection of innovative research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field. While highlighting topics including evolutionary algorithms, micro-machining, and artificial neural networks, this book is ideally designed for researchers, academicians, engineers, managers, developers, practitioners, industrialists, and students seeking current research on intelligence-based machining processes in today's technology-driven market.

Bioengineering is a rapidly expanding interdisciplinary field that encompasses application engineering techniques in the field of mechanical engineering, electrical, electronics and instrumentation engineering, and computer science and engineering to solve the problems of the biological world. With the advent to digital computers and rapidly developing computational techniques, computer simulations are widely used as a predictive tool to supplement the experimental techniques in engineering and technology. Computational biomechanics is a field where the movements biological systems are assessed in the light of computer algorithms describing solid and fluid mechanical principles. This book outlines recent developments in the field of computational biomechanics. It presents a series of computational techniques that are the backbone of the field that includes finite element analysis, multi-scale modelling, fluid-solid interaction, mesh-less techniques and topological optimization. It also presents a series of case studies highlighting applications of these techniques in different biological system and different case studies detailing the application of the principles described earlier and the outcomes. This book gives an overview of the current trends and future directions of research and development in the field of computational biomechanics. Overall, this book gives insight into the current trends of application of intelligent computational techniques used to analyse a multitude of phenomena the field of biomechanics. It elaborates a series of sophisticated techniques used for computer simulation in both solid mechanics, fluid mechanics and fluid-solid interface across different domain of biological world and across various dimensional scales along with relevant case studies. The book elucidates how human locomotion to bacterial swimming, blood flow to sports science, these wide range of phenomena can be analyzed using computational methods to understand their inherent mechanisms of work and predict the behavior of the system. The target audience of the book will be post-graduate students and researchers in the field of Biomedical Engineering. Also industry professionals in biomedical engineering and allied disciplines including but not limited to kinesiologists and clinicians, as well as, computer engineers and applied mathematicians working in algorithm development in biomechanics.

With the advent of digital computers and rapidly developing computational techniques, computer simulations are widely used as predictive tools to supplement experimental techniques in engineering and technology. Computational biomechanics is a field where the movements of biological systems are assessed in the light of computer algorithms describing solid and fluid mechanical principles. This rapidly developing field must be constantly studied and updated as it continues to expand. Advances in Computational Approaches in Biomechanics examines the current trends and applications of intelligent computational techniques used to analyze a multitude of phenomena in the field of biomechanics and elaborates a series of sophisticated techniques used for computer simulation in solid mechanics, fluid mechanics, and fluid-solid interface. Covering a range of topics such as injury prevention, element analysis, and soft tissues, this publication is ideal for industry professionals, practitioners, researchers, academicians, instructors, and students.

Traditional machining has many limitations in today's technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine learning and genetic algorithms has recently transformed the manufacturing industry and created countless opportunities in non-traditional machining methods. Significant research in this area, however, is still considerably lacking. Machine Learning Applications in Non-Conventional Machining Processes is a collection of innovative research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field. While highlighting topics including evolutionary algorithms, micro-machining, and artificial neural networks, this book is ideally designed for researchers, academicians, engineers, managers, developers, practitioners, industrialists, and students seeking current research on intelligence-based machining processes in today's technology-driven market.