An effective diagnosis method to support yield improvement

The ability to achieve and maintain high yield levels depends on the capability of detecting, analyzing and correcting repetitive failure mechanisms. In this paper, a statistical fault diagnosis method based on using only the first or the first few failing test vectors is presented. The new approach is analyzing the failing vectors from an entire lot and produces a finite list of suspect locations, which are then subjected to further statistical and physical analysis. The results of the performed case studies show the usefulness of this method when applied in a production environment. We were able to detect repetitive failure mechanisms and accurately correlate electrical fail locations to in-line inspection data and thus greatly improve the accuracy of the determined kill ratio.