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The use of Bayesian network modelling for maintenance planning in a manufacturing industry

Author

Listed:
  • Jones, B.
  • Jenkinson, I.
  • Yang, Z.
  • Wang, J.

Abstract

This paper has been written in order to apply Bayesian network modelling to a maintenance and inspection department. The primary aim of this paper is to establish and model the various parameters responsible for the failure rate of a system, using Bayesian network modelling, in order to apply it to a delay-time analysis study. The use of Bayesian network modelling allows certain influencing events to be considered which can affect parameters relating to the failure rate of a system. Bayesian network modelling also allows these influencing events to change and update depending on the influencing data available at any given time, thus changing the failure rate or probability of failure. A methodology has been developed and applied to a case study in order to demonstrate the process involved.

Suggested Citation

  • Jones, B. & Jenkinson, I. & Yang, Z. & Wang, J., 2010. "The use of Bayesian network modelling for maintenance planning in a manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 267-277.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:3:p:267-277
    DOI: 10.1016/j.ress.2009.10.007
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    References listed on IDEAS

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    1. Nadkarni, Sucheta & Shenoy, Prakash P., 2001. "A Bayesian network approach to making inferences in causal maps," European Journal of Operational Research, Elsevier, vol. 128(3), pages 479-498, February.
    2. Jones, B. & Jenkinson, I. & Wang, J., 2009. "Methodology of using delay-time analysis for a manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 111-124.
    3. Wang, Wenbin, 2009. "An inspection model for a process with two types of inspections and repairs," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 526-533.
    Full references (including those not matched with items on IDEAS)

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