Enabling Volume Electrical Fault Isolation Workflow with Automation to Enhance Throughput and Success Rate

Summary:

Earlier studies have reported that static fault isolation (FI) methods such as NIR-PEM and TIVA could be utilized, in the absence of software diagnostic or dynamic FI capabilities, to localize subtle defects resulting in functional logic and memory failures. However, the success to this approach relied on interrogating large samples of fail dies to chance upon “Golden” dies, where defect could trigger detectable weak induced emission, from floating gate or bridging effects, from nets that are connected to sensitive combinational logic. This has resulted in long cycle time with current manual fault isolation workflow in localizing these “golden” dies and subsequently identifying the best candidate among these few dies for physical analysis. In this paper, for the first time, we described a novel volumetric electrical fault isolation workflow tested on a new static fault isolation system to perform semi-automated fault isolation. An image recognition software was further employed to cherry pick the best candidates for analysis. Two case studies would be described to illustrate how volumetric fault isolation has improved the success rate and cycle time by 8x with the identification of the best candidates for PFA. We believed this approach would be highly valuable to FA community, especially foundries to enlarge static fault isolation coverage on functional logic failure in the absence of diagnostic or dynamic fault isolation capabilities.