SEM is widely used in semiconductor wafer defect inspection, critical dimension measurement, and defect review and classification after final CP testing. Electron beam defect review equipment can acquire high-resolution morphological images of wafer surface defects. Relying on deep learning-driven automatic defect recognition and classification algorithms, it achieves intelligent detection and classification of hotspot defects. At the same time, it can accurately measure the linewidth and pattern profile dimensions of multilayer thin-film structures on wafers and locate process anomalies, providing intuitive microscopic evidence and quantitative data support for process optimization and chip yield improvement.
