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Optimal maintenance decisions under imperfect inspection

Author

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  • Kallen, M.J.
  • van Noortwijk, J.M.

Abstract

The process industry is increasingly making use of Risk Based Inspection (RBI) techniques to develop cost and/or safety optimal inspection plans. This paper proposes an adaptive Bayesian decision model to determine these optimal inspection plans under uncertain deterioration. It uses the gamma stochastic process to model the corrosion damage mechanism and Bayes’ theorem to update prior knowledge over the corrosion rate with imperfect wall thickness measurements. This is very important in the process industry as current non-destructive inspection techniques are not capable of measuring the exact material thickness, nor can these inspections cover the total surface area of the component. The decision model finds a periodic inspection and replacement policy, which minimizes the expected average costs per year. The failure condition is assumed to be random and depends on uncertain operation conditions and material properties. The combined deterioration and decision model is illustrated by an example using actual plant data of a pressurized steel vessel.

Suggested Citation

  • Kallen, M.J. & van Noortwijk, J.M., 2005. "Optimal maintenance decisions under imperfect inspection," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 177-185.
    • Handle: RePEc:eee:reensy:v:90:y:2005:i:2:p:177-185
    DOI: 10.1016/j.ress.2004.10.004
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    References listed on IDEAS

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    1. X Jia & A H Christer, 2002. "A prototype cost model of functional check decisions in reliability-centred maintenance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(12), pages 1380-1384, December.
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