Bayesian nonparametric analysis of single item preventive maintenance strategies

Dmitriy Belyi*, Paul Damien, Ernie Kee, David Morton, Elmira Popova, Drew Richards

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

This work addresses the problem of finding the minimal-cost preventive maintenance schedule for a single item. We develop an optimization algorithm that reduces the computational effort to find the optimal schedule. This approach relies on the item having an increasing failure rate, which is typical, and employs a Gibbs sampling algorithm to simulate from the failure rate distribution using real data. We also analyze the case when the item has a "bathtub" failure rate; we develop techniques that lead to an algorithm that finds an optimal schedule for this case as well. We then analyze the effectiveness of our approach on both artificial and real data sets from the South Texas Project nuclear power plant.

Original languageEnglish (US)
Title of host publicationProceedings of the 17th International Conference on Nuclear Engineering 2009, ICONE17
Pages255-261
Number of pages7
Volume1
DOIs
StatePublished - Dec 1 2009
Event17th International Conference on Nuclear Engineering, ICONE17 - Brussels, Belgium
Duration: Jul 12 2009Jul 16 2009

Other

Other17th International Conference on Nuclear Engineering, ICONE17
CountryBelgium
CityBrussels
Period7/12/097/16/09

ASJC Scopus subject areas

  • Nuclear Energy and Engineering

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