Abstract

Defect number and defect clustering are two key determinants of wafer yield. Preventing and detecting wafer defects thus is an important issue in integrated circuit manufacturing. Defect clustering tends to grow with increasing wafer size. Methods have been developed for assessing defect clustering on wafers. However, these methods require either statistical assumptions regarding defect distribution or complex computations. This study develops a new cluster index, utilizing the rotating axis technique from multivariate analysis to accurately quantify defect clusters on a wafer. The developed defect-clustering index does not require making assumptions regarding defect distribution. Thus, the proposed method can be efficiently used by engineers with little statistical background. A simulation experiment is conducted to demonstrate the effectiveness of the proposed defect-clustering index.

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