{"title":"半导体制造系统的统计分析与设计","authors":"A. Chen, P.-S. Guo, P. Lin","doi":"10.1109/ISSM.2000.993681","DOIUrl":null,"url":null,"abstract":"The enormous complexity of a semiconductor manufacturing system is the main obstacle for making quality manufacturing control decisions. Conventional methodologies, such as queueing network and simulation analysis, are often too complex to be used effectively. In this paper, we will demonstrate a methodology to build simple statistical models that faithfully characterize the manufacturing system. We then show how these models can help improve the quality of manufacturing control decisions.","PeriodicalId":104122,"journal":{"name":"Proceedings of ISSM2000. Ninth International Symposium on Semiconductor Manufacturing (IEEE Cat. No.00CH37130)","volume":"416 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Statistical analysis and design of semiconductor manufacturing systems\",\"authors\":\"A. Chen, P.-S. Guo, P. Lin\",\"doi\":\"10.1109/ISSM.2000.993681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The enormous complexity of a semiconductor manufacturing system is the main obstacle for making quality manufacturing control decisions. Conventional methodologies, such as queueing network and simulation analysis, are often too complex to be used effectively. In this paper, we will demonstrate a methodology to build simple statistical models that faithfully characterize the manufacturing system. We then show how these models can help improve the quality of manufacturing control decisions.\",\"PeriodicalId\":104122,\"journal\":{\"name\":\"Proceedings of ISSM2000. Ninth International Symposium on Semiconductor Manufacturing (IEEE Cat. No.00CH37130)\",\"volume\":\"416 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of ISSM2000. Ninth International Symposium on Semiconductor Manufacturing (IEEE Cat. No.00CH37130)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSM.2000.993681\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of ISSM2000. Ninth International Symposium on Semiconductor Manufacturing (IEEE Cat. No.00CH37130)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSM.2000.993681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical analysis and design of semiconductor manufacturing systems
The enormous complexity of a semiconductor manufacturing system is the main obstacle for making quality manufacturing control decisions. Conventional methodologies, such as queueing network and simulation analysis, are often too complex to be used effectively. In this paper, we will demonstrate a methodology to build simple statistical models that faithfully characterize the manufacturing system. We then show how these models can help improve the quality of manufacturing control decisions.
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