CD-SEM Anomaly Detection Through Machine Learning and Generative AI

In a complex semiconductor manufacturing environment, critical dimension scanning electron microscope (CD-SEM) images are captured at metrology step to monitor structural measurements and detect anomaly to meet the stringent process control requirements. This paper focuses on advanced CD-SEM image processing and anomaly detection using machine learning and generative AI models, which include computer vision (CV) image processing, Residual Neural Network (ResNet) deep learning and Generative Adversarial Network (GAN) model for various use cases. The applications of these models during in-line monitoring are crucial to identify potential process issues for yield and quality improvement.