Markov Chain Monte Carlo를 이용한 반도체 결함 클러스터링 파라미터의 추정

• 영문명: Estimation of Defect Clustering Parameter Using Markov Chain Monte Carlo
• 발행기관: 한국산업경영시스템학회
• 저자명: 하정훈(Chunghun Ha) 장준현(Jun Hyun Chang) 김준현(Joon Hyun Kim)
• 간행물 정보: 『산업경영시스템학회지』제32권 제3호, 99~109쪽, 전체 11쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2009.09.30

영문 초록

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.

키워드

Yield Model Clustering Effect Parameter Estimation Markov Chain Monte Carlo Bayesian Estimation