{"title":"基于机器学习的故障分析专家系统综述","authors":"Hongjian Wang, Liyuan Liu, Youliang Wang, Zeya Peng","doi":"10.1109/QR2MSE46217.2019.9021177","DOIUrl":null,"url":null,"abstract":"Machine learning is nowadays one of the most efficient and popular tool and theory which has influenced many of the engineering fields. The traditional failure analysis is also based on statistical learning and reliability data, these methods can be used to assess characteristics over the design life, predict reliability, assess the exchange effect, product life prognosis and help to failure analysis. These two subjects have the natural connection, so this paper presents a very general overview on reliability and machine learning, which will demonstrate how the machine learning tools used for classical reliability system and failure analysis. We especially state some algorithms such as Bayesian networks and its’ method to reliability area. Then we can see how a typical engineering area can benefit from the machine learning.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Overview of Failure Analysis Expert System Based on Machine Learning\",\"authors\":\"Hongjian Wang, Liyuan Liu, Youliang Wang, Zeya Peng\",\"doi\":\"10.1109/QR2MSE46217.2019.9021177\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Machine learning is nowadays one of the most efficient and popular tool and theory which has influenced many of the engineering fields. The traditional failure analysis is also based on statistical learning and reliability data, these methods can be used to assess characteristics over the design life, predict reliability, assess the exchange effect, product life prognosis and help to failure analysis. These two subjects have the natural connection, so this paper presents a very general overview on reliability and machine learning, which will demonstrate how the machine learning tools used for classical reliability system and failure analysis. We especially state some algorithms such as Bayesian networks and its’ method to reliability area. Then we can see how a typical engineering area can benefit from the machine learning.\",\"PeriodicalId\":233855,\"journal\":{\"name\":\"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QR2MSE46217.2019.9021177\",\"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 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QR2MSE46217.2019.9021177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Overview of Failure Analysis Expert System Based on Machine Learning
Machine learning is nowadays one of the most efficient and popular tool and theory which has influenced many of the engineering fields. The traditional failure analysis is also based on statistical learning and reliability data, these methods can be used to assess characteristics over the design life, predict reliability, assess the exchange effect, product life prognosis and help to failure analysis. These two subjects have the natural connection, so this paper presents a very general overview on reliability and machine learning, which will demonstrate how the machine learning tools used for classical reliability system and failure analysis. We especially state some algorithms such as Bayesian networks and its’ method to reliability area. Then we can see how a typical engineering area can benefit from the machine learning.