{"title":"具有相关组件的系统可靠性评估的贝叶斯方法","authors":"John Yuan","doi":"10.1016/0143-8174(87)90080-1","DOIUrl":null,"url":null,"abstract":"<div><p>In order to establish a feasible and useful reliability evaluation model for a network system of dependent components, the failure of a component is distinguished into many states artificially, according to the causes which bring about such a failure and the effects to the system in such a way that the failure rate of each state can be easily estimated. Such failure state of a component can be grouped into four types, single (stochastical independent), active, passive and common-cause failures.</p></div>","PeriodicalId":101070,"journal":{"name":"Reliability Engineering","volume":"17 1","pages":"Pages 1-8"},"PeriodicalIF":0.0000,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0143-8174(87)90080-1","citationCount":"4","resultStr":"{\"title\":\"A Bayes approach to reliability assessment for systems with dependent components\",\"authors\":\"John Yuan\",\"doi\":\"10.1016/0143-8174(87)90080-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In order to establish a feasible and useful reliability evaluation model for a network system of dependent components, the failure of a component is distinguished into many states artificially, according to the causes which bring about such a failure and the effects to the system in such a way that the failure rate of each state can be easily estimated. Such failure state of a component can be grouped into four types, single (stochastical independent), active, passive and common-cause failures.</p></div>\",\"PeriodicalId\":101070,\"journal\":{\"name\":\"Reliability Engineering\",\"volume\":\"17 1\",\"pages\":\"Pages 1-8\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1987-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0143-8174(87)90080-1\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Reliability Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0143817487900801\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Reliability Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0143817487900801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Bayes approach to reliability assessment for systems with dependent components
In order to establish a feasible and useful reliability evaluation model for a network system of dependent components, the failure of a component is distinguished into many states artificially, according to the causes which bring about such a failure and the effects to the system in such a way that the failure rate of each state can be easily estimated. Such failure state of a component can be grouped into four types, single (stochastical independent), active, passive and common-cause failures.
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