Abstract
This research develops an analytical structure comprised of a filtering scheme and a fuzzy rule-based inference system to help identify defect spatial patterns. These defect spatial patterns include ring, scratch, zone and repeating types. A set of image processing masks is designed to locate defect positions and then the filtering scheme is applied to extract defect clusters on wafers. With clearly identified defect clusters, three features of minimum rectangle area are used to locate and describe the shape of defect clusters. When all possible defect clusters are well represented by minimum rectangle areas, a set of fuzzy rules are established to combine all the defect clusters and therefore defect spatial patterns are identified. The experiments show that the present approach can effectively identify different defect spatial patterns on wafers.
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