{"title":"The human factors impact of an expert system based reliability centered maintenance program","authors":"R. Klein, G. Klopp","doi":"10.1109/HFPP.1992.283403","DOIUrl":null,"url":null,"abstract":"Reliability centered maintenance (RCM) is a program that addresses the nuclear utility need and the regulatory pressure for improved maintenance practices. A wide variety of system inputs are required to successfully perform RCM. Expert systems are a tool to reduce workload, facilitate the process and improve the performance of an RCM program. Predictive maintenance, using data trending to monitor system performance and identify impending failures, is an alternative input to RCM. Artifical neural networks, embedded in traditional expert systems, can be used to perform predictive maintenance functions. Human factors should be included in an RCM program from the beginning. Maintainability factors related to human error should be identified and input to the RCM process to affect maintenance decisions. Human factors issues are also essential to the development and integration of an RCM expert system.<<ETX>>","PeriodicalId":150946,"journal":{"name":"Conference Record for 1992 Fifth Conference on Human Factors and Power Plants","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record for 1992 Fifth Conference on Human Factors and Power Plants","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HFPP.1992.283403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Reliability centered maintenance (RCM) is a program that addresses the nuclear utility need and the regulatory pressure for improved maintenance practices. A wide variety of system inputs are required to successfully perform RCM. Expert systems are a tool to reduce workload, facilitate the process and improve the performance of an RCM program. Predictive maintenance, using data trending to monitor system performance and identify impending failures, is an alternative input to RCM. Artifical neural networks, embedded in traditional expert systems, can be used to perform predictive maintenance functions. Human factors should be included in an RCM program from the beginning. Maintainability factors related to human error should be identified and input to the RCM process to affect maintenance decisions. Human factors issues are also essential to the development and integration of an RCM expert system.<>
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