Global Identification of Variability Factors and Its Application to the Statistical Worst-Case Model Generation

A novel methodology is presented to generate the worst-case model including extraction of its compact model parameters. This method enables physically accurate worst-case prediction in the early stage of device development concurrently. It is found through the intensive TEG analysis and TCAD simulation that correlations between process factors have a significant impact on the worst-case corner estimation. A new extraction method of compact model parameters based on error propagation analysis is developed to consider correlations between parameters