Optimisation of Robotic Disassembly for Remanufacturing (Paperback, 1st ed. 2022)

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 typical product 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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Series in Advanced Manufacturing
Release date:	August 2022
First published:	2022
Authors:	Yuanjun Laili • Yongjing Wang • Yilin Fang • Duc Truong Pham
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	183
Edition:	1st ed. 2022
ISBN-13:	978-3-03-081801-2
Categories:	Books > Professional & Technical > Mechanical engineering & materials > Production engineering > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics Promotions
LSN:	3-03-081801-2
Barcode:	9783030818012

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