{"title":"预防性维修间隔和工程资产更换决策的决策支持工具","authors":"Madhu Menon, G. Chattopadhyay, R. Beebe","doi":"10.1109/IEEM.2018.8607601","DOIUrl":null,"url":null,"abstract":"Prognostic models for maintenance decisions have inherent limitations due to quality & quantity of historical data, assumptions made, and time required in validating models. In this paper, Preventive Maintenance (PM) Intervals, Failure events, cost and maintenance records from Computerized Maintenance Management System (CMMS) are analyzed for reducing downtimes and Operating Expenditure (OPEX). The proposed methodologies for maintenance intervals and replacements with acceptable level of confidence are articulated to asset maintenance of a City Council of Australian Local Government organisation as a case of improved decision making under limited information.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Decision Support Tools for Preventive Maintenance Intervals and Replacement Decisions of Engineering Assets\",\"authors\":\"Madhu Menon, G. Chattopadhyay, R. Beebe\",\"doi\":\"10.1109/IEEM.2018.8607601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Prognostic models for maintenance decisions have inherent limitations due to quality & quantity of historical data, assumptions made, and time required in validating models. In this paper, Preventive Maintenance (PM) Intervals, Failure events, cost and maintenance records from Computerized Maintenance Management System (CMMS) are analyzed for reducing downtimes and Operating Expenditure (OPEX). The proposed methodologies for maintenance intervals and replacements with acceptable level of confidence are articulated to asset maintenance of a City Council of Australian Local Government organisation as a case of improved decision making under limited information.\",\"PeriodicalId\":119238,\"journal\":{\"name\":\"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM.2018.8607601\",\"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 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2018.8607601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Decision Support Tools for Preventive Maintenance Intervals and Replacement Decisions of Engineering Assets
Prognostic models for maintenance decisions have inherent limitations due to quality & quantity of historical data, assumptions made, and time required in validating models. In this paper, Preventive Maintenance (PM) Intervals, Failure events, cost and maintenance records from Computerized Maintenance Management System (CMMS) are analyzed for reducing downtimes and Operating Expenditure (OPEX). The proposed methodologies for maintenance intervals and replacements with acceptable level of confidence are articulated to asset maintenance of a City Council of Australian Local Government organisation as a case of improved decision making under limited information.