Can models fitted to small data samples lead to maintenance policies with near-optimum cost?

Baker, RD; Scarf, PA

Abstract

In a general context of maintenance modelling, the excess cost of operating at the
estimated optimum value of some decision variable (as opposed to the true unknown
optimum) is related to the sample size of the dataset available for modelling. Although
large sample sizes are required to estimate the optimum value of a decision variable
to a high accuracy, it is shown that the cost which is optimised can be reduced to
near its true minimum value even for small sample sizes. In fact, the expectation of
the excess cost is inversely proportional to sample size. This implies that even modest
sample sizes would be sufficient for the practical use of sensible models for
determining cost-based maintenance policies. An example relating to a simple model
for determining the optimum inspection interval for a repairable system illustrates
these ideas. In particular, some results on the maintenance of medical equipment are
presented.

Citation

Baker, R., & Scarf, P. (1995). Can models fitted to small data samples lead to maintenance policies with near-optimum cost?. IMA Journal of Management Mathematics, 6(1), 3-12. https://doi.org/10.1093/imaman/6.1.3

• Journal Article Type: Article
• Publication Date: Jan 1, 1995
• Deposit Date: Oct 7, 2011
• Journal: IMA Journal of Management Mathematics
• Print ISSN: 1471-678X
• Publisher: Oxford University Press
• Peer Reviewed: Peer Reviewed
• Volume: 6
• Issue: 1
• Pages: 3-12
• DOI: https://doi.org/10.1093/imaman/6.1.3
• Publisher URL: http://dx.doi.org/10.1093/imaman/6.1.3