The shrinking of device critical dimensions (CD) requires tighter control of critical dimension uniformity with every new device node. For propagating CD sampling recipes from process development to high-volume manufacturing (HVM), the number of sampled sites needs to be reduced. One of the largest challenges is the optimization of the measurement sample plan without sacrificing fingerprint quality. We developed a sampling optimization module that can predict the impact of CD downsampling on model quality and variability. Two modes of sampling optimization have been evaluated: rule-based (maximizing distances between sites) and data-based (keeping specific CD signatures intact). The optimized sampling plans can be exported or used inside the process control and monitoring software (OVALiS) to down-sample existing dense measurements and verify the performance on unseen datasets. We can rigorously simulate the effect of reduced sampling on CD dose correction and CDU control.
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