Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Estimation of Defect Clustering Parameter Using Markov Chain Monte Carlo

Markov Chain Monte Carlo를 이용한 반도체 결함 클러스터링 파라미터의 추정

  • Ha, Chung-Hun (School of Information and Computer Engineering, Hongik University) ;
  • Chang, Jun-Hyun (School of Information and Computer Engineering, Hongik University) ;
  • Kim, Joon-Hyun (School of Information and Computer Engineering, Hongik University)
  • 하정훈 (홍익대학교 정보컴퓨터공학부) ;
  • 장준현 (홍익대학교 정보컴퓨터공학부) ;
  • 김준현 (홍익대학교 정보컴퓨터공학부)
  • Published : 2009.09.30
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Abstract

Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

Keywords

References

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