Reducing the complexity of defect level modeling using the clustering effect

Accounting for the clustering effect is fundamental to increasing the accuracy of defect level (DL) modeling. This result has long been known in yield modeling but, as far as known, only one DL model directly accounts for it. In this paper we improve this model, reducing its number of parameters from three to two by noticing that multiple faults caused by a single defect can also be modeled as additional clustering. Our result is supported by test data from a real production line