{"title":"Characterization algorithm of failure distribution for LSI yield improvement","authors":"M. Sugimoto, M. Tanaka","doi":"10.1109/ISSM.2001.962966","DOIUrl":null,"url":null,"abstract":"This paper describes an improvement in our algorithm, which can efficiently characterize a process-induced random failure distribution and a design-induced systematic failure distribution from unknown-induced failure distributions of a memory LSI, to predict a reason for yield degradation in it. The algorithm analyzes a function \"T(f) isn't greater than 1or not\" related to kind and content of \"f\". The \"f\" is a divisor of distances between failure-pairs. We have expanded the algorithm, which can pick out 7 characteristic failure distributions by using relationship between the failure densities and the function \"T(f)\".","PeriodicalId":356225,"journal":{"name":"2001 IEEE International Symposium on Semiconductor Manufacturing. ISSM 2001. Conference Proceedings (Cat. No.01CH37203)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2001 IEEE International Symposium on Semiconductor Manufacturing. ISSM 2001. Conference Proceedings (Cat. No.01CH37203)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSM.2001.962966","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
This paper describes an improvement in our algorithm, which can efficiently characterize a process-induced random failure distribution and a design-induced systematic failure distribution from unknown-induced failure distributions of a memory LSI, to predict a reason for yield degradation in it. The algorithm analyzes a function "T(f) isn't greater than 1or not" related to kind and content of "f". The "f" is a divisor of distances between failure-pairs. We have expanded the algorithm, which can pick out 7 characteristic failure distributions by using relationship between the failure densities and the function "T(f)".