Test cost minimization through adaptive test development

The ever-increasing complexity of mixed-signal circuits imposes an increasingly complicated and comprehensive parametric test requirement, resulting in a highly lengthened manufacturing test phase. Attaining parametric test cost reduction with no test quality degradation constitutes a critical challenge during test development. The capability of parametric test data to capture systematic process variations engenders a highly accurate prediction of the efficiency of each test for a particular lot of chips even on the basis of a small quantity of characterized data. The predicted test efficiency further enables the adjustment of the test set and test order, leading to an early detection of faults. We explore such an adaptive strategy, by introducing a technique that prunes the test set based on a test correlation analysis. A test selection algorithm is proposed to identify the minimum set of tests that delivers a satisfactory defect coverage. A probabilistic measure that reflects the defect detection efficiency is used to order the test set so as to enhance the probability of an early detection of faulty chips. The test sequence is further optimized during the testing process by dynamically adjusting the initial test order to adapt to the local defect pattern fluctuations in the lot of chips under test. Experimental results show that the proposed technique delivers significant test time reductions while attaining higher test quality compared to previous adaptive test methodologies.