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Quantitative analysis of a conceptual system dynamics maintenance performance model using multi-objective optimisation

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  • Gary Linnéusson
  • Amos H. C. Ng
  • Tehseen Aslam

Abstract

This paper presents a quantitative analysis of a conceptual, system dynamics (SD) model by the application of multi-objective optimisation (MOO). The SD model investigates the strategic development of maintenance performance, using a system view of maintenance costs, while the execution of MOO evaluates multiple simulation runs, seeking the simultaneous trade-off solutions of the three conflicting objectives: maximise availability, minimise maintenance costs, and minimise maintenance consequential costs. The study explores three scenarios that represent companies at different states of developed maintenance performance. The application of this integrated, simulation-based optimisation approach reveals multiple analyses of system behaviour of the SD model, which are presented in a compact format to a decision-maker. Actually, notwithstanding the application to a conceptual model, the study results make explicit the nonlinearity between invested maintenance cost and its consequent effects. Furthermore, the approach demonstrates the contribution to the process of strengthening the usefulness of the conceptual maintenance performance model.

Suggested Citation

  • Gary Linnéusson & Amos H. C. Ng & Tehseen Aslam, 2018. "Quantitative analysis of a conceptual system dynamics maintenance performance model using multi-objective optimisation," Journal of Simulation, Taylor & Francis Journals, vol. 12(2), pages 171-189, April.
    • Handle: RePEc:taf:tjsmxx:v:12:y:2018:i:2:p:171-189
    DOI: 10.1080/17477778.2018.1467849
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    Cited by:

    1. Linnéusson, Gary & Ng, Amos H.C. & Aslam, Tehseen, 2020. "A hybrid simulation-based optimization framework supporting strategic maintenance development to improve production performance," European Journal of Operational Research, Elsevier, vol. 281(2), pages 402-414.
    2. Yi Chen & Xiaobing Ma & Fanping Wei & Li Yang & Qingan Qiu, 2022. "Dynamic Scheduling of Intelligent Group Maintenance Planning under Usage Availability Constraint," Mathematics, MDPI, vol. 10(15), pages 1-18, August.
    3. Pinciroli, Luca & Baraldi, Piero & Zio, Enrico, 2023. "Maintenance optimization in industry 4.0," Reliability Engineering and System Safety, Elsevier, vol. 234(C).

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