Modeling and forecasting of defect-limited yield in semiconductor manufacturing

Abstract

A detailed cause-and-effect stochastic model is developed to relate the type, size, location, and frequency of observed defects to the final yield in IC manufacturing. The model is estimated on real data sets with a large portion of unclassified defects and uninspected layers, and in presence of clustering of defects. Results of this analysis are used for evaluating kill ratios and effects of different factors, identifying the most dangerous cases and the most probable causes of failures, forecasting the yield, and designing optimal yield-enhancement strategies. © 2008 IEEE.