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Condition monitoring: a new perspective

Author

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  • F P A Coolen

    (University of Durham)

  • P Coolen-Schrijner

    (University of Durham)

Abstract

We present a novel approach to support preventive replacement decisions based on condition monitoring. It is assumed that the condition of a technical unit is measured continuously, with the measurement indicating in which of k≥2 states the unit is. A new unit is in state S1, and failure occurs the moment a unit leaves state S k . A unit will only go from state S j to state Sj+1, and these immediately observed transitions occur at random times. At such transition moments a decision is required on preventive replacement of the unit, which would require preparation time. Such a decision needs to be based on inferences about the total residual time till failure. We present a method for such inferences that relies on minimal model assumptions added to data on state transitions. We illustrate the approach via simulated examples, and discuss possible use of the method and related aspects.

Suggested Citation

  • F P A Coolen & P Coolen-Schrijner, 2000. "Condition monitoring: a new perspective," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(3), pages 311-319, March.
    • Handle: RePEc:pal:jorsoc:v:51:y:2000:i:3:d:10.1057_palgrave.jors.2600905
    DOI: 10.1057/palgrave.jors.2600905
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    Citations

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    Cited by:

    1. P Coolen-Schrijner & F P A Coolen, 2004. "Adaptive age replacement strategies based on nonparametric predictive inference," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1281-1297, December.
    2. Percy, David F., 2002. "Bayesian enhanced strategic decision making for reliability," European Journal of Operational Research, Elsevier, vol. 139(1), pages 133-145, May.
    3. Coolen, F. P. A. & Coolen-Schrijner, P., 2003. "A nonparametric predictive method for queues," European Journal of Operational Research, Elsevier, vol. 145(2), pages 425-442, March.

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