{"title":"Bayesian inference for the simple step-stress accelerated life tests under order-restriction","authors":"Crystal Wiedner , David Han","doi":"10.1016/j.promfg.2021.10.021","DOIUrl":null,"url":null,"abstract":"<div><p>In this work, we investigate the order-restricted Bayesian estimation for a simple step-stress accelerated life tests. Based on the three-parameter gamma distribution as a conditional prior, we ensure that the failure rates increase as the stress level increases. In addition, its conjugate-like structure enables us to derive the exact joint posterior distribution of the parameters without a need to perform an expensive MCMC sampling. Upon these distributional results, several Bayesian estimators for the model parameters are suggested along with their individual/joint credible intervals. Through Monte Carlo simulations, the performance of our proposed inferential methods are assessed and compared. Finally, a real engineering case study for analyzing the reliability of a solar lighting device is presented to illustrate the methods developed in this work.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2351978921002183/pdf?md5=e3f66b03ad69103b34c3171de3595054&pid=1-s2.0-S2351978921002183-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2351978921002183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, we investigate the order-restricted Bayesian estimation for a simple step-stress accelerated life tests. Based on the three-parameter gamma distribution as a conditional prior, we ensure that the failure rates increase as the stress level increases. In addition, its conjugate-like structure enables us to derive the exact joint posterior distribution of the parameters without a need to perform an expensive MCMC sampling. Upon these distributional results, several Bayesian estimators for the model parameters are suggested along with their individual/joint credible intervals. Through Monte Carlo simulations, the performance of our proposed inferential methods are assessed and compared. Finally, a real engineering case study for analyzing the reliability of a solar lighting device is presented to illustrate the methods developed in this work.