Test yield estimation for analog/RF circuits over multiple correlated measurements
Fang Cherry Liu, Erkan Acar, Sule Ozev · 2007
Circuit and test yield information provides essential feedback to circuit designers and test engineers to evaluate their designs and test set-ups. Traditionally, Monte Carlo analysis and other sample-and-simulate based approaches have been used for yield estimation. However, such computationally costly techniques cannot be used if yield estimation needs to be repeated multiple times, as in the case of test evaluation. In this paper, we propose a technique to conduct accurate and efficient overall yield estimation based on hybrid quadratic modelling and hierarchical statistical profiling. We also develop compatible models for environmental noise and measurement error, two most important error sources in the test process. Our experiments on a baseband amplifier and a cascaded LNA-mixer circuit confirm that the proposed yield estimation technique achieves significant computational time saving with negligible accuracy loss when used for multiple test set-up evaluations.