Methodology for Fast and Accurate Analog Production Test

This paper describes a new technique to reduce the number of simulations required during analog fault simulation. The method takes into account process parameter variations and aims to reduce the number of the computational expensive Monte Carlo simulations often required during analog fault simulation. In section I a review of the state of the art is presented, section II and III introduce the algorithm and describe the methodology of our approach. The results on CMOS 2-stage opamp and conclusions are given in sections IV and V

SIMULATION DE FAUTES ET OPTIMISATION DES TESTS DE PRODUCTION POUR LES CIRCUITS ANALOGIQUES AVEC PRISE EN COMPTE DES TOLERANCES

PARIS-BIUSJ-Mathématiques rech (751052111) / SudocCentre Technique Livre Ens. Sup. (774682301) / SudocSudocFranceF

Optimisation des Tests de Production pour les Circuits Analogiques avec prise en compte des tolérances

National audienc

Fault Simulation for Analog Circuits Under Parameter Variations

International audienceAnalog integrated circuit testing and diagnosis is a very challenging problem. The inaccuracy of measurements, the infinite domain of possible values and the parameter deviations are among the major difficulties. During the process of optimizing production tests, Monte Carlo simulation is often needed due to parameter variations, but because of its expensive computational cost, it becomes the bottleneck of such a process. This paper describes a new technique to reduce the number of simulations required during analog fault simulation. This leads to the optimization of production tests subjected to parameter variations. In Section 1 a review of the state of the art is presented, Section 2 introduces the algorithm and describes the methodology of our approach. The results on CMOS 2-stage opamp and Fifth-order Low-pass switched-capacitor Filter are given in Sections 3 and conclusions in Section 4

FDP: Fault Detection Probability Function For Analog Circuits

In analog integrated circuits, process variations result in physical parameter variations. Simulated performance values must then be considered with their tolerance intervals. Consequently, contrarily to digital circuits where the outputs are either '0' or '1' such that we can decide without ambiguity whether a fault is detectable or not, for analog circuits fault detectability is still a vague problem since the fault can either be completely detectable, partially detectable or completely undetectable which makes it very difficult to take a decision. In order to solve this decision problem, we have introduced the fault detection probability (FDP) function which allows to formalize the problem of analog fault detection subjected to parameter variations