Automated image analysis and image classification system that employs machine learning has been developed and applied to the PWQ/FEM flow to enhance the Process Stability Diagnosis (PSD) solution, which can now handle a significant volume of wafer images while realizing a 4X reduction in time to results. Moving the task of image analysis and classification to the computer has the added benefit of avoiding person-to-person inconsistencies in classification. The data flow consists of an automated machine learning-enabled process window analysis system that relies on CDSEM images taken on a FEM or Focus/Exposure Matrix wafer. We report results based on CDSEM images containing both contact hole and line features. The system enables full-wafer SEM image auto-classification and process window characterization.
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