{"title":"An iterative Bayes procedure for reliability assessment","authors":"R. Prairie, W. Zimmer","doi":"10.1109/ARMS.1990.67922","DOIUrl":null,"url":null,"abstract":"A method of reliability assessment is suggested. It is Bayesian in that the uncertainty about the unreliability is expressed by means of a prior distribution with a specified upper limit. The method is a hierarchical Bayesian one in that the uncertainty about the limit of prior distribution is also expressed by means of a prior distribution. The data from the development program are incorporated with the prior on the unreliability and with the prior on the upper limit of the prior to obtain a new prior on unreliability. The production data are then used to obtain a revised estimate of the unreliability as well as a modified value for the limit of the prior distribution. This same concept will be carried through when the field data are obtained. The result is a final Bayesian reliability assessment that is iterative in nature and sequentially incorporates data from each of the three stages common to a component development, production, and surveillance program.<<ETX>>","PeriodicalId":383597,"journal":{"name":"Annual Proceedings on Reliability and Maintainability Symposium","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Proceedings on Reliability and Maintainability Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARMS.1990.67922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A method of reliability assessment is suggested. It is Bayesian in that the uncertainty about the unreliability is expressed by means of a prior distribution with a specified upper limit. The method is a hierarchical Bayesian one in that the uncertainty about the limit of prior distribution is also expressed by means of a prior distribution. The data from the development program are incorporated with the prior on the unreliability and with the prior on the upper limit of the prior to obtain a new prior on unreliability. The production data are then used to obtain a revised estimate of the unreliability as well as a modified value for the limit of the prior distribution. This same concept will be carried through when the field data are obtained. The result is a final Bayesian reliability assessment that is iterative in nature and sequentially incorporates data from each of the three stages common to a component development, production, and surveillance program.<>