Building on content from the authors’ earlier introductory Process Selection guide, this expanded handbook begins with the challenges and benefits of identifying manufacturing processes in the design phase and appropriate strategies for process selection. The bulk of the book is then dedicated to concise coverage of different manufacturing processes, providing a quick reference guide for easy comparison and informed decision making.
For each process examined, the book considers key factors driving selection decisions, including:
Providing a quick and effective reference for the informed selection of manufacturing processes with suitable characteristics and capabilities, Manufacturing Process Selection Handbook is intended to quickly develop or refresh your experience of selecting optimal processes and costing design alternatives in the context of concurrent engineering. It is an ideal reference for those working in mechanical design across a variety of industries and a valuable learning resource for advanced students undertaking design modules and projects as part of broader engineering programs.
Professor Ken Swift is the Lucas Professor of Manufacturing Systems Engineering at University of Hull, UK. Following decades of research and collaboration with leading manufacturing groups worldwide, his current research interests include capability analysis and probabilistic design, flexible assembly and inspection systems. He has received numerous awards and prizes in the area of design and manufacturing, including the Donald Julius Groen Prize, awarded for a paper on manufacturing process selection in the IMechE Journal of Engineering Manufacture.
Dr Julian Booker is Reader in Design and Manufacture at University of Bristol, UK, and a recognized expert in product design and process engineering. Working closely with industry, his research interests include the development and industrial implementation of design methods for manufacture, assembly, quality and reliability improvement, and the structural integrity of frictional machine elements using simulation and experimental methods.