 Robustness of maintenance decisions: Uncertainty modelling and value of informationA. Zitrou, T. Bedford and A. Daneshkhah Reliability Engineering and System Safety, 2013, vol. 120, issue C, 60-71 Abstract: In this paper we show how sensitivity analysis for a maintenance optimisation problem can be undertaken by using the concept of expected value of perfect information (EVPI). This concept is important in a decision-theoretic context such as the maintenance problem, as it allows us to explore the effect of parameter uncertainty on the cost and the resulting recommendations. To reduce the computational effort required for the calculation of EVPIs, we have used Gaussian process (GP) emulators to approximate the cost rate model. Results from the analysis allow us to identify the most important parameters in terms of the benefit of ’learning’ by focussing on the partial expected value of perfect information for a parameter. The analysis determines the optimal solution and the expected related cost when the parameters are unknown and partially known. This type of analysis can be used to ensure that both maintenance calculations and resulting recommendations are sufficiently robust. Keywords: Maintenance; Optimisation; Value of information; Emulator; Gaussian process (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:120:y:2013:i:c:p:60-71 DOI: 10.1016/j.ress.2013.03.001 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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