Overview
- Explores the issues and optimisation requirements related to the use of robotics in disassembly processes
- Offers a blueprint for modelling problems in robotic disassembly and remanufacturing
- Explains how optimisation and decision making tools improves the efficiency of remanufacturing
Part of the book series: Springer Series in Advanced Manufacturing (SSAM)
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book illustrates the main characteristics, challenges and optimisation requirements of robotic disassembly. It provides a comprehensive insight on two crucial optimisation problems in the areas of robotic disassembly through a group of unified mathematical models. The online and offline optimisation of the operational sequence to dismantle a product, for example, is represented with a list of conflicting objectives and constraints. It allows the decision maker and the robots to match the situation automatically and efficiently.
To identify a generic solution under different circumstances, classical metaheuristics that can be used for the optimisation of robotic disassembly are introduced in detail. A flexible framework is then presented to implement existing metaheuristics for sequence planning and line balancing in the circumstance of robotic disassembly.Optimisation of Robotic Disassembly for Remanufacturing provides practical case studies on typicalproduct instances to help practitioners design efficient robotic disassembly with minimal manual operation, and offers comparisons of the state-of-the-art metaheuristics on solving the key optimisation problems. Therefore, it will be of interest to engineers, researchers, and postgraduate students in the area of remanufacturing.
Authors and Affiliations
About the authors
Yongjing Wang is a scientist and a research engineer at School of Engineering, University of Birmingham, UK, where he has been a key member of Autonomous Remanufacturing Laboratory since its foundation in 2016. He is the designer and manager of the lab and a leading developer of multiple robotic disassembly cells. His has a passion to discover autonomy phenomenon in nature and society, and how to use the knowledge to construct autonomous systems. The experience contributes to his interdisciplinary background in automation, autonomous structures, and control systems. He obtained his PhD and BEng in 2016 and 2013 respectively, through which he became alumni of the University of Birmingham, and Harbin Institute of Technology. His current fellowship is sponsored by The Engineering and Physical Sciences Research Council (EPSRC).
Professor Duc Truong Pham holds theChance Chair of Engineering at the University of Birmingham where he started his career as a lecturer in robotics and control engineering following undergraduate and postgraduate studies at the University of Canterbury in New Zealand. Prior to returning to Birmingham in 2011, he was Professor of Computer-Controlled Manufacture and Director of the Manufacturing Engineering Centre at Cardiff University. His research is in the areas of intelligent systems, robotics and autonomous systems and advanced manufacturing technology.
Bibliographic Information
Book Title: Optimisation of Robotic Disassembly for Remanufacturing
Authors: Yuanjun Laili, Yongjing Wang, Yilin Fang, Duc Truong Pham
Series Title: Springer Series in Advanced Manufacturing
DOI: https://doi.org/10.1007/978-3-030-81799-2
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-81798-5Published: 18 August 2021
Softcover ISBN: 978-3-030-81801-2Published: 19 August 2022
eBook ISBN: 978-3-030-81799-2Published: 17 August 2021
Series ISSN: 1860-5168
Series E-ISSN: 2196-1735
Edition Number: 1
Number of Pages: XX, 183
Number of Illustrations: 38 b/w illustrations, 45 illustrations in colour
Topics: Manufacturing, Machines, Tools, Processes, Robotics and Automation, Industrial and Production Engineering