Bi-objective optimisation of remanufacturing decisions with component commonality under different reworking scenarios

Sakraan Sitcharangsie, T. C. Wong, Winifred Ijomah

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
36 Downloads (Pure)

Abstract

Decision-making for remanufacturing is more complicated than that of traditional manufacturing because used or new components can be selected to remanufacture products. It becomes difficult to determine the various options of the components and their subsequent effect on the options at the same time. In fact, all decisions made in one remanufacturing activity will have a direct impact on the decisions taken in subsequent activities and this will affect profitability. Therefore, a decision-making model is proposed to support businesses in each remanufacturing activity by using mixed-integer linear programming to maximise profit and minimise operational time. It remains unknown whether component commonality always benefits remanufacturing. Therefore, this research contributes to the literature by quantifying and controlling the impact of component commonality on the objectives under different reworking scenarios characterised by the percentage of reworked components, reworking time, and reworking cost. When reworking costs and the percentage of reworked components are higher, the effect of component commonality on profit fluctuation increases. The remanufacturer can control these situations by reducing reworking costs, selecting specific patterns of component commonality that generate high profits or choosing the appropriate percentage of reworked components depending on various scenarios.

Original languageEnglish
Pages (from-to)1086-1107
Number of pages22
JournalInternational Journal of Computer Integrated Manufacturing
Volume34
Issue number10
Early online date20 Sept 2021
DOIs
Publication statusPublished - 3 Oct 2021

Keywords

  • remanufacturing
  • decision
  • component commonality
  • optimisation
  • mixedinteger linear programming

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