Using diagnosis-driven yield analysis, companies have decreased their time to yield, managed manufacturing excursions and recovered yield caused by systematic defects. Dramatic time savings and yield gains have been proven using these methods. Companies must plan ahead to advantage of diagnosis-driven yield analysis. The planning needs to include how and what patterns to generate during ATPG/DFT, what design data to archive, how to optimize your test program, how much data to collect, and what/how much diagnosis to perform. This white paper will address how to optimize the test environment in order to enable efficient diagnosis-driven yield analysis.

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