Iterative Cluster Harvesting for Wafer Map Defect Patterns

arXiv:2404.15436v1 Announce Type: new
Abstract: Unsupervised clustering of wafer map defect patterns is challenging because the appearance of certain defect patterns varies significantly. This includes changing shape, location, density, and rotation of the defect area on the wafer. We present a harvesting approach, which can cluster even challenging defect patterns of wafer maps well. Our approach makes use of a well-known, three-step procedure: feature extraction, dimension reduction, and clustering. The novelty in our approach lies in repeating dimensionality reduction and …

abstract arxiv cluster clustering cs.cv iterative location map patterns rotation type unsupervised