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dc.contributor.authorGürler, Ü.en_US
dc.contributor.authorDayanık, S.en_US
dc.date.accessioned2019-01-31T12:59:16Z
dc.date.available2019-01-31T12:59:16Z
dc.date.issued2002en_US
dc.identifier.issn0030-364X
dc.identifier.urihttp://hdl.handle.net/11693/48620
dc.description.abstractIn this study, an adaptive Bayesian decision model is developed to determine the optimal replacement age for the systems maintained according to a general age-replacement policy. It is assumed that when a failure occurs, it is either critical with probability p or noncritical with probability1−p, independently. A maintenance policy is considered where the noncritical failures are corrected with minimal repair and the system is replaced either at the first critical failure or at age , whichever occurs first. The aim is to find the optimal value of that minimizes the expected cost per unit time. Two adaptive Bayesian procedures that utilize different levels of information are proposed for sequentiallyupdating the optimal replacement times. Posterior density/mass functions of the related variables are derived when the time to failure for the system can be expressed as a Weibull random variable. Some simulation results are also presented for illustration purposes.en_US
dc.language.isoEnglishen_US
dc.source.titleOperations Researchen_US
dc.relation.isversionofhttps://doi.org/10.1287/opre.50.3.552.7750en_US
dc.subjectBayesian analysisen_US
dc.subjectStatistical decision makingen_US
dc.subjectReplacement of industrial equipmenten_US
dc.subjectProbability theoryen_US
dc.subjectMaintenanceen_US
dc.subjectVariables (Mathematics)en_US
dc.subjectBusiness expensesen_US
dc.subjectCorporate policiesen_US
dc.subjectCognitive processesen_US
dc.subjectProduction factorsen_US
dc.subjectFinancial accountingen_US
dc.subjectFinancial economicsen_US
dc.titleAn adaptive bayesian replacement policy with minimal repairen_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.citation.spage552en_US
dc.citation.epage558en_US
dc.citation.volumeNumber50en_US
dc.citation.issueNumber3en_US
dc.identifier.doi10.1287/opre.50.3.552.7750en_US
dc.publisherInstitute for Operations Research and the Management Sciences (INFORMS)en_US
dc.identifier.eissn1526-5463


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