{"title":"Effective multi-stage test equipment capacity allocation for semiconductor fabrication yield enhancement","authors":"K.D. Chen, R. Akella, I. Emami, M. McIntyre","doi":"10.1109/ISSM.1997.664628","DOIUrl":null,"url":null,"abstract":"We formulate a multi-stage inspection planning model based on configurations in actual semiconductor fab-lines, specifically taking into account both the capacity constraint and the congestion effects at the inspection station. We propose a new mixed First-Come-First-Serve (FCFS) and Last-Come-First-Serve (LCFS) discipline for serving the inspection samples to expedite the detection of potential yield problems. Employing this mixed FCFS and LCFS discipline, we derive approximate expressions for the queueing delays in yield problem detection time and develop near-optimal algorithms to obtain the inspection logistics planning policies.","PeriodicalId":138267,"journal":{"name":"1997 IEEE International Symposium on Semiconductor Manufacturing Conference Proceedings (Cat. No.97CH36023)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1997 IEEE International Symposium on Semiconductor Manufacturing Conference Proceedings (Cat. No.97CH36023)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSM.1997.664628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
We formulate a multi-stage inspection planning model based on configurations in actual semiconductor fab-lines, specifically taking into account both the capacity constraint and the congestion effects at the inspection station. We propose a new mixed First-Come-First-Serve (FCFS) and Last-Come-First-Serve (LCFS) discipline for serving the inspection samples to expedite the detection of potential yield problems. Employing this mixed FCFS and LCFS discipline, we derive approximate expressions for the queueing delays in yield problem detection time and develop near-optimal algorithms to obtain the inspection logistics planning policies.