Impact of multiple-detect test patterns on product quality

Abstract This paper presents the impact of multiple-detect test patterns on outgoing product quality. It introduces an ATPG tool that generates multiple-detect test patterns while maximizing the coverage of node-to-node bridging defects. Volumedata obtained by testing a production ASIC with these new multiple-detect patterns shows increased defect screening capability and very good agreement with the bridging coverage estimated by the ATPG tool. 1. Introduction One of the key objectives of manufacturing test is to ensure high quality of shipped parts while managing the cost of test. Scan–based DFT methodology, combined with ATPG tools, automate the generation of test patterns with very high fault coverage. The advantage ofa structure-based ATPG tool is its high efficiency and effectiveness in generating a test set by targeting different fault models, such as stuck-at, transition, path delay, and DDQ . DFT tooI ls assess the quality of test patterns by reporting the fault coverage of the target fault models. However, real defects may not always be detected by test patterns generated for the targeted fault model. The stuck-at fault model has been used in DFT ince sthe very beginning and, while showing some limitations and imperfections, it has demonstrated its robustness and adaptability. Even though the stuck-at fault model may not always model behavior of a faulty circuit it serves very well as a target, i.e. a test set developed to test stuck-at faults will also cover many other defects that do not behave as stuck-at faults. Good understanding of bridging defects is at the center of explanation of the effectiveness of the stuck-at fault model. It also provides the key clues to its enhancements. In an experimental study of bridging faults in a state of the art microprocessor design [1] it has been observed that approximately 80% of all bridges occur between a node and Vcc or Vss, and 20% involve nonsupply nod- es. Global signals were involved in 70% of these defects and leaf-level signals contributed only 30%. In another experimental evaluation of scan tests for bridging defects [2] it was concluded that bridges with power rails contributed between 60% to 90% of all bridging defects. It is clear that a test that detect a stuck-at fault on a node willdetect a low resistive bridging defect with the supply lines. This is exactly the behavior of a node stuckat- -0 or stuckat- -1. However, the detection of node-to-node bridging defects is not guaranteed. If a stuckat fault on a node is detected once, the- probability f detecting a static bridging fault witho another un-correlated node that has signal probability 50% is also 50% [3]. If the stuck at fault is detected- twice, the estimated probability of detecting the bridging fault with another node acting as an aggressor is 75%. Signal correlation may reduce the coverage of nodeto-node bridging faults. It was- observed [1] that a test set with greater than 95% stuck-at fault coverage produced only 33% coverage of nodeto-node bridging faults. Most likely the- disappointing coverage was an artifact of signal correlation. Typically a test set created by conventional ATPG aiming at single detection may have up to 6% of faults detected only once and up to 10% of faults detected only once or twice. This may result in inadequate coverage of nodeto-node -bridging defects. In general, there are two directions to overcome the limitation and improve the test quality. One direction is to enhance the fault model by describing the defect behavior and presenting it in a suitable form to the ATPG tool. In this case the fault model is more precise and complex and the fault list s longer. Thei advanced fault models, like bridging faults and cross-talk effects, use physical layout information to compile the fault lists. A complete example of this approach is demonstrated in [2]. Here the possible bridges are identified by analysis of layout using weighted critical area and their behavior is modeled by different types of faults and a special netlist. The experimental results from the project show that