| Title | Combining Enhanced Diagnostic-Driven Analysis Scheme and Static Near Infrared Photon Emission Microscopy for Effective Scan Failure Debug |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Moon, S. J., Nagalingam, D., Ngow, Y. T., Quah, A. C. T. |
| Conference Name | 2022 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA) |
| Date Published | jul |
| Keywords | composability, defect prediction (key words), failure analysis, Foundries, Human Behavior, Inspection, integrated circuits, microscopy, photon emission microscopy, Product design, pubcrawl, Resiliency, Scan Diagnosis, scan failure, Software, static analysis |
| Abstract | Software based scan diagnosis is the de facto method for debugging logic scan failures. Physical analysis success rate is high on dies diagnosed with maximum score, one symptom, one suspect and shorter net. This poses a limitation on maximum utilization of scan diagnosis data for PFA. There have been several attempts to combine dynamic fault isolation techniques with scan diagnosis results to enhance the utilization and success rate. However, it is not a feasible approach for foundry due to limited product design and test knowledge and hardware requirements such as probe card and tester. Suitable for a foundry, an enhanced diagnosis-driven analysis scheme was proposed in [1] that classifies the failures as frontend-of-line (FEOL) and backend-of-line (BEOL) improving the die selection process for PFA. In this paper, static NIR PEM and defect prediction approach are applied on dies that are already classified as FEOL and BEOL failures yet considered unsuitable for PFA due to low score, multiple symptoms, and suspects. Successful case studies are highlighted to showcase the effectiveness of using static NIR PEM as the next level screening process to further maximize the scan diagnosis data utilization. |
| DOI | 10.1109/IPFA55383.2022.9915727 |
| Citation Key | moon_combining_2022 |
Combining Enhanced Diagnostic-Driven Analysis Scheme and Static Near Infrared Photon Emission Microscopy for Effective Scan Failure Debug