Suraj Rao, Andrzej J. Strojwas, John Lehoczky, Schervish
{"title":"监控VLSIC制造过程:贝叶斯方法","authors":"Suraj Rao, Andrzej J. Strojwas, John Lehoczky, Schervish","doi":"10.1109/ASMC.1995.484375","DOIUrl":null,"url":null,"abstract":"We have developed a process monitoring system, in a Bayesian framework, which is designed to be used for monitoring VLSIC and other multi-stage manufacturing processes. For a single step process, the Bayesian monitor is at least as good as the Shewhart-CUSUM combination charts for detecting changes in the distribution of the in-lines collected from the step. For a multi-stage process, however, the Bayesian monitor can significantly reduce the detection time by using in-line correlation information from earlier stages.","PeriodicalId":237741,"journal":{"name":"Proceedings of SEMI Advanced Semiconductor Manufacturing Conference and Workshop","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Monitoring VLSIC fabrication processes: a Bayesian approach\",\"authors\":\"Suraj Rao, Andrzej J. Strojwas, John Lehoczky, Schervish\",\"doi\":\"10.1109/ASMC.1995.484375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have developed a process monitoring system, in a Bayesian framework, which is designed to be used for monitoring VLSIC and other multi-stage manufacturing processes. For a single step process, the Bayesian monitor is at least as good as the Shewhart-CUSUM combination charts for detecting changes in the distribution of the in-lines collected from the step. For a multi-stage process, however, the Bayesian monitor can significantly reduce the detection time by using in-line correlation information from earlier stages.\",\"PeriodicalId\":237741,\"journal\":{\"name\":\"Proceedings of SEMI Advanced Semiconductor Manufacturing Conference and Workshop\",\"volume\":\"112 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of SEMI Advanced Semiconductor Manufacturing Conference and Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASMC.1995.484375\",\"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 SEMI Advanced Semiconductor Manufacturing Conference and Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASMC.1995.484375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Monitoring VLSIC fabrication processes: a Bayesian approach
We have developed a process monitoring system, in a Bayesian framework, which is designed to be used for monitoring VLSIC and other multi-stage manufacturing processes. For a single step process, the Bayesian monitor is at least as good as the Shewhart-CUSUM combination charts for detecting changes in the distribution of the in-lines collected from the step. For a multi-stage process, however, the Bayesian monitor can significantly reduce the detection time by using in-line correlation information from earlier stages.
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