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Application of data mining for improving and predicting yield in wafer fabrication system
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Dong-Hyun Baek (Division of Business & Commerce, Cheonan University)
Chang-Hee Han (Department of Business Administration, Hanyang University)
Vol. 9, No. 1, Page: 157 ~ 177
Keywords
data mining, wafer fabrication, yield
Abstract
This paper presents a comprehensive and successful application of data mining methodologies to improve and predict wafer yield in a semiconductor wafer fabrication system. As the wafer fabrication process is getting more complex and the volume of technological data gathered continues to be vast, it is difficult to analyze the cause of yield deterioration effectively by means of statistical or heuristic approaches. To begin with this paper applies a clustering method to automatically identify AUF (Area Uniform Failure) phenomenon from data instead of naked eye that bad chips occurs in a specific area of wafer. Next, sequential pattern analysis and classification methods are applied to and out machines and parameters that are cause of low yield, respectively. Furthermore, radial bases function method is used to predict yield of wafers that are in process. Finally, this paper demonstrates an information system, Y2R-PLUS (Yield Rapid Ramp-up, Prediction, analysis & Up Support), that is developed in order to analyze and predict wafer yield in a korea semiconductor manufacturer.
Show/Hide Detailed Information in Korean
데이터마이닝을 이용한 반도체 FAB공정의 수율개선 및 예측
백동현 (천안대학교 경상학부)
한창희 (한양대학교 디지털 경영학부)
Keywords
데이터 마이닝, 반도체 FAB공정, 수율
Abstract
본 논문은 반도체 FAB공정의 수율개선 및 예측을 위해 데이터마이닝 기법을 적용한 사례를 소개한다. FAB 공정의 복잡성과 생산현장에서 수집되는 방대한 기술데이터로 인해 기존의 통계적 방법이나 엔지니어의 경험적 분석 방법만으로는 미처 파악하지 못하는 수율 저하 요인이 상당 수 존재한다. 본 논문은 먼저, FAB공정을 마친 웨이퍼에 불량 칩(chip)이 지리적으로 특정 위치에 집중적으로 발생하는 현상을 육안검사 대신 군집분석을 이용하여 데이터로부터 자동 판별할 수 있는 방법을 제안한다. 다음으로 연속패턴분석, 분류분석, RBF(Radial Base Function) 기법을 적용하여 수율 저하의 원인이 되는 문제 장비나 문제 파라미터를 신속, 정확하게 파악할 수 있도록 해 줄 뿐만 아니라 공정 진행 중인 제품의 미래 수율을 예측할 수 있도록 지원하는 방법을 제안한다. 또한 위 기법들을 반도체 FAB공정을 대상으로 국내 모 반도체 회사에서 정보시스템으로 구현한 Y2R-PLUS (Yield Rapid Ramp-up, Prediction, analysis & Up Support) 시스템을 소개한다.
Cite this article
JIIS Style
Baek, D.-H., and C.-H. Han, "Application of data mining for improving and predicting yield in wafer fabrication system", Journal of Intelligence and Information Systems, Vol. 9, No. 1 (2003), 157~177.

IEEE Style
Dong-Hyun Baek, and Chang-Hee Han, "Application of data mining for improving and predicting yield in wafer fabrication system", Journal of Intelligence and Information Systems, vol. 9, no. 1, pp. 157~177, 2003.

ACM Style
Baek, D.-H., and Han, C.-H., 2003. Application of data mining for improving and predicting yield in wafer fabrication system. Journal of Intelligence and Information Systems. 9, 1, 157--177.
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@article{Baek:JIIS:2003:156,
author = {Baek, Dong-Hyun and Han, Chang-Hee},
title = {Application of data mining for improving and predicting yield in wafer fabrication system},
journal = {Journal of Intelligence and Information Systems},
issue_date = {June 2003},
volume = {9},
number = {1},
month = Jun,
year = {2003},
issn = {2288-4866},
pages = {157--177},
url = {},
doi = {},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { data mining, wafer fabrication and yield },
}
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%A Chang-Hee Han
%T Application of data mining for improving and predicting yield in wafer fabrication system
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 9
%N 1
%P 157-177
%D 2003
%R
%I Korea Intelligent Information System Society