{"title":"A new method for calculating one-dimensional process margin in consideration of process variations","authors":"T. Miwa, T. Noda, T. Akiyama, S. Sugimoto","doi":"10.1109/IWSTM.1999.773196","DOIUrl":null,"url":null,"abstract":"Yield and device characteristics in VLSI become more sensitive to process variations with finer patterns and enlargement of wafer size. Thus, process integration should take account of the inter- and intra-wafer process variations for elimination of yield loss. However, it is difficult to perform experiments which cover possible process variations because of cost and time. In this paper, we describe a new method for calculating a process margin for processes such as etching and deposition with consideration of process variations using the Monte Carlo method.","PeriodicalId":253336,"journal":{"name":"1999 4th International Workshop on Statistical Metrology (Cat. No.99TH8391)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1999 4th International Workshop on Statistical Metrology (Cat. No.99TH8391)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWSTM.1999.773196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Yield and device characteristics in VLSI become more sensitive to process variations with finer patterns and enlargement of wafer size. Thus, process integration should take account of the inter- and intra-wafer process variations for elimination of yield loss. However, it is difficult to perform experiments which cover possible process variations because of cost and time. In this paper, we describe a new method for calculating a process margin for processes such as etching and deposition with consideration of process variations using the Monte Carlo method.