This paper proposes a new cluster index that utilizes the defect location data on a wafer in terms of the coefficent of variation. The proposed cluster index is independent of the chip area and does not rquire assumptions on the distribution of defects. An extensive simulation is performed under a variety of cluster patterns and a yield prediction moedel is derived through the regression analysis to the relate the yield with the proposed cluster index and the average number of defects per chip. The performance ofthe proposed simulaation-based yield prediction model is compared with that of the well-known negative binomial model.
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