Correlated Rare Failure Analysis via Asymptotic Probability Evaluation

In this paper, a novel Asymptotic Probability Estimation (APE) method is proposed to estimate the probability of correlated rare failure events for complex integrated systems containing a large number of replicated cells. The key idea is to approximate the failure rate of the entire system by solving a set of nonlinear equations derived from a general analytical model. An error refinement method based on Look-up Table (LUT) is further developed to improve numerical stability and, hence, reduce estimation error. Furthermore, a statistical algorithm based on re-sampling is developed to accurately estimate the confidence interval of APE. Our numerical experiments demonstrate that compared to the state-of-the-art method, APE can reduce the estimation error by up to 30× without increasing the computational cost.