This paper presents a new method for improving the quality and effectiveness of scan-based tests. The method, called statistical diagnosis, leverages defect likelihoods learned from analyzing populations of failing die instead of analyzing each die independently as traditionally done. The method was validated in a large silicon study that showed significant improvement in diagnosis resolution with minimal impact on diagnosis accuracy. Statistical diagnosis, as the paper explains, can also be used to predict or identify the dominant defect mechanism in low yielding wafers.

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