A Quality Data Mining System in TFT-LCD Industry

TFT-LCD 산업에서의 품질마이닝 시스템

  • Lee, Hyun-Woo (Korea Reliability Technology Service) ;
  • Nam, Ho-Soo (Department of System & Management Engineering, Dongseo University)
  • 이현우 ((주)한국신뢰성기술서비스) ;
  • 남호수 (동서대학교 시스템경영공학과)
  • Published : 2006.03.31

Abstract

Data mining is a useful tool for analyzing data from different perspectives and for summarizing them into useful information. Recently, the data mining methods are applied to solving quality problems of the manufacturing processes. This paper discusses the problems of construction of a quality mining system, which is based on the various data mining methods. The quality mining system includes recipe optimization, significant difference test, finding critical processes, forecasting the yield. The contents and system of this paper are focused on the TFT-LCD manufacturing process. We also provide some illustrative field examples of the quality mining system.

Keywords

References

  1. 백준걸, 김강호, 김성식, 김창욱(2000), '실시간 기계상태 데이터베이스에서 데이터마이닝을 위한 적응형 의사결정트리 알고리듬', 대한산업공학화지, 26권, 2호, pp. 171-183
  2. 백동현, 한창희(2003), '데이터마이닝을 이용한 반도체 FAB공정의 수율개선 및 예측', 한국지능정보시스템학회논문지, 9권, 1호, pp. 157-177
  3. 안진석, 고용민, 장중순(1999), '데이터마이닝을 이용한 최적공정조건 탐색', 대한설비관리학회지, 4권, 2호, pp. 129-144
  4. 이현우, 남호수, 강중철(2005), 'A Study on Data Mining Application Problem in the TFT-LCD Industry', 한국데이터정보과학회지, 16권, 4호, pp. 823-833
  5. 장남식(1999), '성공적인 지식경영을 위한 핵심정보 기술 :데이터마이닝' 대청미디어
  6. Braha, D. and Shmilovici, A.(2002), 'Data Mining for Improving a Cleansing Process in the Semiconductor Industry', IEEE Transactions on Semiconductor Industry, Vol. 15, No.1, pp. 91-101 https://doi.org/10.1109/66.983448
  7. Fayyad, D., Piatetsky-Shapiro, G., and Smyth, P.(1996), 'From Data Mining to Knoeledge Discovery in Databases', Advances in knowledge discovery and data mining, AAAI Press/MIT Press, pp. 1-34
  8. Lian, J., Lai, X. M., Lin, Z. Q., and Yao, F. S.(2002), 'Application of Data Mining and Process Knowledge Discovering in Sheet Metal Assembly Dimensional Variation Diagnosis', Journal of Materials Processing Technology, Vol. 129, pp. 315-320 https://doi.org/10.1016/S0924-0136(02)00691-X