{"title":"客车预防性维修质量评价的改进方法","authors":"Zhigao Chen, R. Jiang, Yi-Rong Teng","doi":"10.1109/phm-qingdao46334.2019.8943061","DOIUrl":null,"url":null,"abstract":"This paper proposes an improved method to evaluate the quality of preventive maintenance. This method evaluates the quality of preventive maintenance by comparing the pseudo-failure rate and the actual failure rate after the maintenance point. When using the weighting method to establish the power-law model to fit the failure data before the maintenance point, we focus on its prediction effect. When the normal function weight and the negative exponential function weight are used to estimate the model parameters, it is found that the model with negative exponential function weight has better predictive ability. To improve the accuracy of the prediction, the parameters of the negative exponential weight function are optimized. When using the power-law model to model the failure data after maintenance, we pay attention to the fitting effect. In the subsequent case study, we used two methods to evaluate the quality of preventive maintenance of a fleet of 26 buses, and the results show that the improved method is more reasonable.","PeriodicalId":259179,"journal":{"name":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","volume":"8 28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An improved method for evaluating the preventive maintenance quality of buses\",\"authors\":\"Zhigao Chen, R. Jiang, Yi-Rong Teng\",\"doi\":\"10.1109/phm-qingdao46334.2019.8943061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an improved method to evaluate the quality of preventive maintenance. This method evaluates the quality of preventive maintenance by comparing the pseudo-failure rate and the actual failure rate after the maintenance point. When using the weighting method to establish the power-law model to fit the failure data before the maintenance point, we focus on its prediction effect. When the normal function weight and the negative exponential function weight are used to estimate the model parameters, it is found that the model with negative exponential function weight has better predictive ability. To improve the accuracy of the prediction, the parameters of the negative exponential weight function are optimized. When using the power-law model to model the failure data after maintenance, we pay attention to the fitting effect. In the subsequent case study, we used two methods to evaluate the quality of preventive maintenance of a fleet of 26 buses, and the results show that the improved method is more reasonable.\",\"PeriodicalId\":259179,\"journal\":{\"name\":\"2019 Prognostics and System Health Management Conference (PHM-Qingdao)\",\"volume\":\"8 28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Prognostics and System Health Management Conference (PHM-Qingdao)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/phm-qingdao46334.2019.8943061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/phm-qingdao46334.2019.8943061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved method for evaluating the preventive maintenance quality of buses
This paper proposes an improved method to evaluate the quality of preventive maintenance. This method evaluates the quality of preventive maintenance by comparing the pseudo-failure rate and the actual failure rate after the maintenance point. When using the weighting method to establish the power-law model to fit the failure data before the maintenance point, we focus on its prediction effect. When the normal function weight and the negative exponential function weight are used to estimate the model parameters, it is found that the model with negative exponential function weight has better predictive ability. To improve the accuracy of the prediction, the parameters of the negative exponential weight function are optimized. When using the power-law model to model the failure data after maintenance, we pay attention to the fitting effect. In the subsequent case study, we used two methods to evaluate the quality of preventive maintenance of a fleet of 26 buses, and the results show that the improved method is more reasonable.