Efficient Monte Carlo-based analog parametric fault modelling

The accepted approach in industry today to ensure out-going quality in high-volume manufacturing of analog circuits is to measure datasheet specifications. The lack of a comprehensive fault model that is computationally efficient makes the elimination of any tests or the use of lower-cost alternative tests too risky or too time-consuming. Monte Carlo simulations offer a general way to model parametric variations, but inherently focus on normal instead of defective performance. This paper defines a new, general fault model comprising a set of marginally failing circuit instances to evaluate parametric fault coverage of test suites in a way that reduces the number of Monte Carlo simulations by one or more orders of magnitude. As an illustrative example, the technique is applied to six parameters of an RF low-noise amplifier (LNA).