Hierarchical probabilistic diagnosis of MCMs on large-area substrates

This paper addresses the issue of testing MCMs fabricated on large-area substrates. The cost of testing MCMs may be as high as 40% of the manufacturing cost. In order to reduce test costs, at is essential that the testing be parallelized taking advantage of the fact that all the MCMs on the large-area substrate are similar. In this paper we propose a hierarchical probabilistic test algorithm for MCMs on large-area substrates. In this method, the MCMs on the substrate are divided into clusters. The responses of the MCMs are analyzed within their clusters, and the most common responses are sent to a global tester for determining the likely correct response. Based on this, the MCMs are diagnosed as faulty or fault free. The decisions are made after each test is applied. Our algorithm performs better than the existing probabilistic test algorithms and provides up to an order of magnitude reduction in test application time as opposed to serial MCM probe test