DocumentCode :
2197757
Title :
An Intelligent Product Disassembly Planning Method
Author :
Hui, Wang ; Dong, Xiang ; Guanghong, Duan
Author_Institution :
Dept. of Precision Instruments & Mechanology, Tsinghua Univ., Beijing
fYear :
2006
fDate :
8-11 May 2006
Firstpage :
357
Lastpage :
357
Abstract :
Disassembly sequence planning problem is a NP-hard combinatorial optimization problem. Generally, with the increasing of components number, the computational complexity of searching for good disassembly solution(s) in a large search space of disassembly solutions will be increased more. Therefore, to avoid the exploded combination, heuristic methods are often used for the goal of finding optimum solution(s) at a high efficiency. In the proposed research, we present the disassembly feasibility information graph (DFIG) to describe product´s disassembly operations (sequences) information. In fact, this graph is a model of simulated all possible disassembly operations, and meanwhile, stored relevant information of operations which includes feasibility of operations and disassembly processes if these operations are feasible. Based on this graph, product´s disassembly sequences planning problem could be transformed into this problem: On the DFIG, to find out a path with an optimized sum value, which starts from the start point, and could tour all the components of product just one time, along with the weighed, directed edges
Keywords :
assembly planning; computational complexity; design for disassembly; genetic algorithms; graph theory; NP-hard combinatorial optimization; computational complexity; disassembly feasibility information graph; disassembly sequence planning; genetic algorithm; Biological cells; Computational complexity; Computational intelligence; Encoding; Filling; Genetic algorithms; Instruments; Path planning; Software systems; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics and the Environment, 2006. Proceedings of the 2006 IEEE International Symposium on
Conference_Location :
Scottsdale, AZ
ISSN :
1095-2020
Print_ISBN :
1-4244-0351-0
Type :
conf
DOI :
10.1109/ISEE.2006.1650092
Filename :
1650092
Link To Document :
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