Diagnosing Cell Internal Defects Using Analog Simulation-Based Fault Models

The industry is encountering an increasing number of front-end-of-line defects in the most advanced technology nodes due to extremely small feature size and complex manufacturing processes. Traditional scan diagnosis algorithms can locate a defective cell by examining its excitation conditions for cell internal defects, but cannot provide the more precise defect location inside the cell that is necessary for effective physical failure analysis and statistical yield learning. In this work, we propose a new cell-aware diagnosis algorithm, based on accurate fault models derived by analog simulation, that can pinpoint the defect location within a cell for various cell internal defects. The proposed method already has achieved dramatic resolution improvement for real silicon failures.