Fast and Accurate DPPM Computation Using Model Based Filtering

Abstract

Defective Parts Per Million (DPPM) is an important quality metric that indicates the ratio of defective devices shipped to the customers. It is necessary to estimate and minimize DPPM in order to meet the desired level of quality. However, DPPM estimation requires statistical simulations, which are computationally costly if traditional methods are used. In this work, we propose an efficient DPPM estimation method for analog circuits that greatly reduces the computational burden. We employ a model based approach to selectively simulate only consequential samples in DPPM estimation. We include methods to mitigate the effect of model imperfection and robust model fitting to guarantee a consistent and efficient estimation. Experimental results show that the proposed method achieves 10xto 25x reduction in the number of simulations for an RF receiver front-end circuit.