Defect cluster analysis for wafer-scale integration

Abstract

A methodology for characterizing spatial defect distributions is presented. A correlation function approach providing spatial information not measurable with classical methods such as yield-versus-area curves is described. This additional information includes the spatial extent of defect clustering, the strength of clustering, and uncertainty in clustering magnitude. The correlation function methods are applicable to experimentally determined defect maps or to simulation results based on different assumptions concerning the spatial distribution of defects. It is also shown that the approach is useful in predicting yield for redundant circuit configurations when experimental data pertaining to the spatial distribution of defects are available. This type of yield prediction capability is important for judging the feasibility of various redundancy implementations, including wafer scale integration. >