Defect screening using independent component analysis on I/sub DDQ/

Abstract

An I/sub DDQ/ Statistical Post-Processing/spl trade/ (SPP) outlier screen is presented based on the computation of statistically independent sources of variation in the I/sub DDQ/ measurements. I/sub DDQ/ measurements from die passing all other tests are modeled using sources of variation extracted by independent component analysis (ICA). Outliers are separated from the sample population based on residuals computed using these sources and a nearest neighbor spatial signature. An algorithm is presented for applying the proposed technique in production. The screen is demonstrated with 0.18/spl mu/m and 0.11/spl mu/m volume data and shown to effectively identify the outliers at the 0.1 /spl mu/m technology node.