Disassembly Sequence Planning Considering Fuzzy Component Quality and Varying Operational Cost
Document Type
Article
Publication Date
4-1-2018
Abstract
Disassembly planning aims to search the best disassembly sequences of a given obsolete/used product in terms of economic and environmental performances. A practical disassembly process may face great uncertainty owing to various unpredictable factors. To handle it, researchers have addressed the stochastic cost and time problems of product disassembly. In reality, the uncertain environment of product disassembly is associated with both randomness and fuzziness. Besides uncertain disassembly cost and time, the quality of disassembled components/parts in a process has uncertainty and thus needs to be assessed via expert opinions/subjects. To do so, this paper presents a new AND/OR-graph-based disassembly sequence planning problem by considering uncertain component quality and varying disassembly operational cost. Important disassembly planning models are built on the basis of different disassembly criteria. A novel hybrid intelligent algorithm integrating fuzzy simulation and artificial bee colony is proposed to solve them. Its effectiveness is well illustrated through several numerical cases and comparison with a prior method, i.e., fuzzy-simulation-based genetic algorithm.
Identifier
85019038644 (Scopus)
Publication Title
IEEE Transactions on Automation Science and Engineering
External Full Text Location
https://doi.org/10.1109/TASE.2017.2690802
ISSN
15455955
First Page
748
Last Page
760
Issue
2
Volume
15
Grant
51405075
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Tian, Guangdong; Zhou, Meng Chu; and Li, Peigen, "Disassembly Sequence Planning Considering Fuzzy Component Quality and Varying Operational Cost" (2018). Faculty Publications. 8760.
https://digitalcommons.njit.edu/fac_pubs/8760
