Fast Monte Carlo-Based Estimation of Analog Parametric Test Metrics

The accepted approach in industry today to ensure out-going quality in high-volume manufacturing of analog circuits is to directly measure datasheet specifications. To reduce the involved costs it is required to eliminate specification tests or use instead lower-cost alternative tests. However, this is too risky if the resultant fault coverage and yield coverage metrics of the new test approach are not estimated accurately. This paper proposes a methodology to efficiently derive a set of most probable failing and marginally functional circuit instances. Based on this set, we can readily define and estimate fault coverage and yield coverage metrics. Our methodology reduces the required number of Monte Carlo simulations by one or more orders of magnitude. As an illustrative example, the methodology is applied to a radio frequency low-noise amplifier.