PROBABILISTIC FAULT-DETECTION AND THE SELECTION OF MEASUREMENTS FOR ANALOG INTEGRATED-CIRCUITS

New methods for analog fault detection and for the selection of measur ements for analog testing (wafer probe or final testing) are presented , Using Bayes' rule, the information contained in the measurement data and the information of the a priori probabilities of a circuit's bein g fault free or faulty are converted into a posteriori probabilities a nd used for fault detection in analog integrated circuits, with a deci sion Criterion that considers the statistical tolerances and mismatche s of the circuit parameters. An adaptive formulation of the a priori p robabilities is given that updates their values according to the resul ts of the testing and fault detection, In addition, a systematic metho d is,proposed for the optimal selection of the measurement components so as to minimize the probability of an erroneous test decision. Examp les of DC wafer-probe testing as well as production testing using the power-supply current spectrum are given that demonstrate the effective ness of the algorithms.