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Condition-based release of maintenance jobs in a decentralised production-maintenance system – An analysis of alternative stochastic approaches

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  • Gössinger, Ralf
  • Helmke, Hanna
  • Kaluzny, Michael

Abstract

A condition-based release of preventive maintenance jobs is analysed for a single-stage production/maintenance system where maintenance is performed by a separate unit. It is assumed, that the conditions of the machine deteriorate as a function of multiple production parameters. The task of maintenance is to keep up a predefined operational reliability. In this context the problem of determining the optimal machine condition that triggers the release of a preventive maintenance job arises. Existing approaches to solve this problem either assume a monolithic production/maintenance system or focus on a decentralised system in which information flow and resource transfer do not cause delays. In our paper we derive a triggering mechanism that is not based on these assumptions. It is built on a specific continuous condition monitoring and a suitable information exchange. On this basis the factors determining the delay between the release and completion of a maintenance job are operationalised and alternative stochastic approaches to calculate the triggering condition are formulated. Finally, based on simulations the performance of the approaches is analysed. Thereby, relevant characteristics of the production/maintenance system and the maintenance task are varied systematically. This research contributes answers to the questions on how the exchange of local information can be structured, and the parameters of condition-based maintenance can be calculated and set in case of incomplete information about deterioration in a decentralised production/maintenance system.

Suggested Citation

  • Gössinger, Ralf & Helmke, Hanna & Kaluzny, Michael, 2017. "Condition-based release of maintenance jobs in a decentralised production-maintenance system – An analysis of alternative stochastic approaches," International Journal of Production Economics, Elsevier, vol. 193(C), pages 528-537.
    • Handle: RePEc:eee:proeco:v:193:y:2017:i:c:p:528-537
    DOI: 10.1016/j.ijpe.2017.08.009
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