Optimal Replacement in the Proportional Hazards Model with Semi-Markovian Covariate Process and Continuous Monitoring

dc.contributor.author Wu, Xiang
dc.contributor.author Ryan, Sarah
dc.contributor.author Ryan, Sarah
dc.contributor.department Industrial and Manufacturing Systems Engineering
dc.date 2018-02-16T09:41:56.000
dc.date.accessioned 2020-06-30T04:48:09Z
dc.date.available 2020-06-30T04:48:09Z
dc.date.copyright Sat Jan 01 00:00:00 UTC 2011
dc.date.issued 2011-07-01
dc.description.abstract <p>Motivated by the increasing use of condition monitoring technology for electrical transformers, this paper deals with the optimal replacement of a system having a hazard function that follows the proportional hazards model with a semi-Markovian covariate process, which we assume is under continuous monitoring. Although the optimality of a threshold replacement policy to minimize the long-run average cost per unit time was established previously in a more general setting, the policy evaluation step in an iterative algorithm to identify optimal threshold values poses computational challenges. To overcome them, we use conditioning to derive an explicit expression of the objective in terms of the set of state-dependent threshold ages for replacement. The iterative algorithm is customized for our model to find the optimal threshold ages. A three-state example illustrates the computational procedure, as well as the effects of different sojourn time distributions of the covariate process on the optimal policy and cost. Numerical examples and sensitivity analysis provide some insights into the suitability of a Markov approximation, and the sources of variability in the cost. The optimization method developed here is much more efficient than the approach that approximates continuous monitoring as periodic, and then optimizes the periodic monitoring parameters.</p>
dc.description.comments <p>This is a manuscript of an article from <em>IEEE Transactions on Reliability</em> 60 (2011): 580, doi: <a href="http://dx.doi.org/10.1109/TR.2011.2161049" target="_blank">10.1109/TR.2011.2161049</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/imse_pubs/17/
dc.identifier.articleid 1008
dc.identifier.contextkey 7125494
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath imse_pubs/17
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/44463
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/imse_pubs/17/2011_RyanSM_OptimalReplacementProportional_manuscript_.pdf|||Fri Jan 14 21:10:20 UTC 2022
dc.source.uri 10.1109/TR.2011.2161049
dc.subject.disciplines Industrial Engineering
dc.subject.disciplines Systems Engineering
dc.subject.keywords optimal replacement
dc.subject.keywords proportional hazards model
dc.subject.keywords semi-Markov process
dc.subject.keywords sensitivity analysis
dc.subject.keywords threshold replacement policy
dc.title Optimal Replacement in the Proportional Hazards Model with Semi-Markovian Covariate Process and Continuous Monitoring
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 22d808f1-c309-4cb1-8d3e-14c57a6b96a9
relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
Original bundle
Now showing 1 - 1 of 1
585.25 KB
Adobe Portable Document Format