{"title":"半导体生产线信噪比的仿真实验研究","authors":"Jean-Yves Rosaye","doi":"10.1109/ISSM.2007.4446850","DOIUrl":null,"url":null,"abstract":"Recently, competitive semiconductor manufacturing becomes indispensable to satisfy market requirements for failure prevention and process parameter control is of major concern. Mechanism of designing experiments used for process optimization in a large size fab. with Taguchi method or other statistical tool is not often considered. Instead, minimal design of experiment as with L8 orthogonal array is used because of trend to minimal experimentation. However, limits exist in minimal design, which introduced a lack of precision because of only two parameter levels in L8 for example. Simulation of experiment is suggested as to conciliate cost reduction, minimal experimentation with better design to obtain further and adequate information for process optimization.","PeriodicalId":325607,"journal":{"name":"2007 International Symposium on Semiconductor Manufacturing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study of S/N Ratio by simulation of experiment in a semiconductor manufacturing line\",\"authors\":\"Jean-Yves Rosaye\",\"doi\":\"10.1109/ISSM.2007.4446850\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, competitive semiconductor manufacturing becomes indispensable to satisfy market requirements for failure prevention and process parameter control is of major concern. Mechanism of designing experiments used for process optimization in a large size fab. with Taguchi method or other statistical tool is not often considered. Instead, minimal design of experiment as with L8 orthogonal array is used because of trend to minimal experimentation. However, limits exist in minimal design, which introduced a lack of precision because of only two parameter levels in L8 for example. Simulation of experiment is suggested as to conciliate cost reduction, minimal experimentation with better design to obtain further and adequate information for process optimization.\",\"PeriodicalId\":325607,\"journal\":{\"name\":\"2007 International Symposium on Semiconductor Manufacturing\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Symposium on Semiconductor Manufacturing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSM.2007.4446850\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Symposium on Semiconductor Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSM.2007.4446850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study of S/N Ratio by simulation of experiment in a semiconductor manufacturing line
Recently, competitive semiconductor manufacturing becomes indispensable to satisfy market requirements for failure prevention and process parameter control is of major concern. Mechanism of designing experiments used for process optimization in a large size fab. with Taguchi method or other statistical tool is not often considered. Instead, minimal design of experiment as with L8 orthogonal array is used because of trend to minimal experimentation. However, limits exist in minimal design, which introduced a lack of precision because of only two parameter levels in L8 for example. Simulation of experiment is suggested as to conciliate cost reduction, minimal experimentation with better design to obtain further and adequate information for process optimization.