Disassembly Sequence Planning Considering Fuzzy Component Quality and Varying Operational Cost

Guangdong Tian, Meng Chu Zhou, Peigen Li

Research output: Contribution to journalArticlepeer-review

118 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)748-760
Number of pages13
JournalIEEE Transactions on Automation Science and Engineering
Volume15
Issue number2
DOIs
StatePublished - Apr 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Disassembly
  • disassembly planning
  • fuzzy simulation
  • modeling and simulation

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