Computer-aided fault to defect mapping (CAFDM) for defect diagnosis

Defects diagnosis in random logic is currently done using the stuck-at fault model, while most defects seen in manufacturing result in bridging faults. In this work we use physical design and test failure information combined with bridging and stuck-at fault models to localize defects in random logic. We term this approach computer-aided fault to defect mapping (CAFDM). We build on top of the existing mature stuck-at diagnosis infrastructure. The performance of the CAFDM software was tested by injecting bridging faults into samples of a streaming audio controller chip and comparing the predicted defect locations and layers with the actual values. The correct defect location and layer was predicted in all 9 samples for which scan-based diagnosis could be performed. The experiment was repeated on production samples that failed scan test, with promising results.

Stanojevic, Z., Balachandran, H., Walker, D., Lakhani, F., Jandhyala, S., Saxena, J., & Butler, K. M.

Stanojevic, Z||Balachandran, H||Walker, DMH||Lakhani, F||Jandhyala, S||Saxena, J||Butler, KM

Computer-aided fault to defect mapping (CAFDM) for defect diagnosis Academic Article