Effective excursion detection by defect type grouping in in-line inspection and classification

In this paper, a new methodology for effective process excursion monitoring using defect review/classification information is proposed. We introduce a new defect classification scheme, in which relevant defect types that are likely to be caused by the same mechanism or source are grouped into a "def ect family." It is demonstrated that trending by the defect family drastica lly improves the detection efficiency of killer defect excursion by reducin g or eliminating noise resulting from irrelevant benign defects. We compare the risks of missing critical excursions for monitoring by total defect co unt, killer defect count, and killer defect family, and illustrate the effe ctiveness of our methodology using data from actual fabline.