{"title":"对维修数据进行逻辑回归,建立检查间隔","authors":"K.E. Spezzaferro","doi":"10.1109/RAMS.1996.500678","DOIUrl":null,"url":null,"abstract":"As budgets are decreasing, it is imperative to select maintenance inspection interval lengths that minimize costs without risk of compromising safety or operational effectiveness issues. However, the data required are not always available or conducive to standard analytic techniques. This paper discusses the application of logistic regression to existing maintenance inspection data to establish inspection intervals. Logistic regression response variables are binary or go/no-go, variables which do not lend themselves to analysis with traditional methods. This paper presents the methodology along with pertinent results.","PeriodicalId":393833,"journal":{"name":"Proceedings of 1996 Annual Reliability and Maintainability Symposium","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1996-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Applying logistic regression to maintenance data to establish inspection intervals\",\"authors\":\"K.E. Spezzaferro\",\"doi\":\"10.1109/RAMS.1996.500678\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As budgets are decreasing, it is imperative to select maintenance inspection interval lengths that minimize costs without risk of compromising safety or operational effectiveness issues. However, the data required are not always available or conducive to standard analytic techniques. This paper discusses the application of logistic regression to existing maintenance inspection data to establish inspection intervals. Logistic regression response variables are binary or go/no-go, variables which do not lend themselves to analysis with traditional methods. This paper presents the methodology along with pertinent results.\",\"PeriodicalId\":393833,\"journal\":{\"name\":\"Proceedings of 1996 Annual Reliability and Maintainability Symposium\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-01-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1996 Annual Reliability and Maintainability Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RAMS.1996.500678\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1996 Annual Reliability and Maintainability Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAMS.1996.500678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applying logistic regression to maintenance data to establish inspection intervals
As budgets are decreasing, it is imperative to select maintenance inspection interval lengths that minimize costs without risk of compromising safety or operational effectiveness issues. However, the data required are not always available or conducive to standard analytic techniques. This paper discusses the application of logistic regression to existing maintenance inspection data to establish inspection intervals. Logistic regression response variables are binary or go/no-go, variables which do not lend themselves to analysis with traditional methods. This paper presents the methodology along with pertinent results.