The attempt to differentiate between normal global uniformity and local uniformity pose a metrology challenge. In this paper, we present a scanning electron microscopy (SEM) based method for detecting stochastic defects. The detected defects are reviewed by metrology and classified by defect margin merit. The proposed merit converts geometrical attributes into statistical attributes which identify whether a pattern is statistically normal or a statistical outlier.
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