We present a contour metrology-based process matching flow with machine learning-based site selection for best coverage, contour comparisons, and scoring to quantify process differences. This method can significantly improve the efficiency of process technology transfers between fabs. The key technology includes: 1) high-performance ML clustering on a full chip product with hundreds of millions of anchoring points, 2) process-matching oriented custom feature engineering that drives quantitative understanding of each SEM image, and 3) stable and reliable contour extraction of large amounts of CD-SEM images.
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