{"title":"基于半马尔可夫的生产系统维修决策","authors":"Jianlong Wu, B. Xiao, Liying Yang, Zhonghao Zhao","doi":"10.1109/ICSRS.2018.8688830","DOIUrl":null,"url":null,"abstract":"In order to improve the capacity of production system, a maintenance decision method based on Semi-Markov Model was provided. Firstly the model for the production system was described. Then, the state probability and universal generating function were combined to analyze the reliability of the system. Based upon the imperfect maintenance decision model, a maintenance decision method combining imperfect preventive maintenance and imperfect repair maintenance was proposed, which ensured that the production system could obtain maximum production availability within the specified time. And a case was taken as an example to verify the effectiveness of the proposed model and the analysis method.","PeriodicalId":166131,"journal":{"name":"2018 3rd International Conference on System Reliability and Safety (ICSRS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Semi-Markov Based Maintenance Decision for Production System\",\"authors\":\"Jianlong Wu, B. Xiao, Liying Yang, Zhonghao Zhao\",\"doi\":\"10.1109/ICSRS.2018.8688830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the capacity of production system, a maintenance decision method based on Semi-Markov Model was provided. Firstly the model for the production system was described. Then, the state probability and universal generating function were combined to analyze the reliability of the system. Based upon the imperfect maintenance decision model, a maintenance decision method combining imperfect preventive maintenance and imperfect repair maintenance was proposed, which ensured that the production system could obtain maximum production availability within the specified time. And a case was taken as an example to verify the effectiveness of the proposed model and the analysis method.\",\"PeriodicalId\":166131,\"journal\":{\"name\":\"2018 3rd International Conference on System Reliability and Safety (ICSRS)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 3rd International Conference on System Reliability and Safety (ICSRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSRS.2018.8688830\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 3rd International Conference on System Reliability and Safety (ICSRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSRS.2018.8688830","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Semi-Markov Based Maintenance Decision for Production System
In order to improve the capacity of production system, a maintenance decision method based on Semi-Markov Model was provided. Firstly the model for the production system was described. Then, the state probability and universal generating function were combined to analyze the reliability of the system. Based upon the imperfect maintenance decision model, a maintenance decision method combining imperfect preventive maintenance and imperfect repair maintenance was proposed, which ensured that the production system could obtain maximum production availability within the specified time. And a case was taken as an example to verify the effectiveness of the proposed model and the analysis method.