{"title":"一类支持向量机在半导体制造中的失控检测","authors":"Ilham Rabhi, A. Roussy, F. Pasqualini, C. Alegret","doi":"10.1109/CASE49439.2021.9551477","DOIUrl":null,"url":null,"abstract":"Semiconductor manufacturing is a continuously challenging and competitive industry. It is important to detect any anomalies in the production facilities, or fabs, as they occur to avoid defect accumulations and loss of performance. In this paper we present a literature review of classification methods and detailed the chosen method which is One Class-Support Vector Machine (OC-SVM). This method is used for out-of-control detection in semiconductor manufacturing. The method is tested via an application using industrial data of the studied fab.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"254 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Out-Of-Control Detection In Semiconductor Manufacturing using One-Class Support Vector Machines\",\"authors\":\"Ilham Rabhi, A. Roussy, F. Pasqualini, C. Alegret\",\"doi\":\"10.1109/CASE49439.2021.9551477\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Semiconductor manufacturing is a continuously challenging and competitive industry. It is important to detect any anomalies in the production facilities, or fabs, as they occur to avoid defect accumulations and loss of performance. In this paper we present a literature review of classification methods and detailed the chosen method which is One Class-Support Vector Machine (OC-SVM). This method is used for out-of-control detection in semiconductor manufacturing. The method is tested via an application using industrial data of the studied fab.\",\"PeriodicalId\":232083,\"journal\":{\"name\":\"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)\",\"volume\":\"254 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASE49439.2021.9551477\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE49439.2021.9551477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Out-Of-Control Detection In Semiconductor Manufacturing using One-Class Support Vector Machines
Semiconductor manufacturing is a continuously challenging and competitive industry. It is important to detect any anomalies in the production facilities, or fabs, as they occur to avoid defect accumulations and loss of performance. In this paper we present a literature review of classification methods and detailed the chosen method which is One Class-Support Vector Machine (OC-SVM). This method is used for out-of-control detection in semiconductor manufacturing. The method is tested via an application using industrial data of the studied fab.