IN-SITU APPARATUS FOR DETECTING ABNORMALITY IN PROCESS TUBE

    公开(公告)号:US20230060183A1

    公开(公告)日:2023-03-02

    申请号:US17461715

    申请日:2021-08-30

    Abstract: A process tube device can detect the presence of any external materials that may reside within a fluid flowing in the tube. The process tube device detects the external materials in-situ which obviates the need for a separate inspection device to inspect the surface of a wafer after applying fluid on the surface of the wafer. The process tube device utilizes at least two methods of detecting the presence of external materials. The first is the direct measurement method in which a light detecting sensor is used. The second is the indirect measurement method in which a sensor utilizing the principles of Doppler shift is used. Here, contrary to the first method that at least partially used reflected or refracted light, the second method uses a Doppler shift sensor to detect the presence of the external material by measuring the velocity of the fluid flowing in the tube.

    MACHINE LEARNING ON WAFER DEFECT REVIEW

    公开(公告)号:US20210027984A1

    公开(公告)日:2021-01-28

    申请号:US17069712

    申请日:2020-10-13

    Abstract: This disclosure is directed to solutions of detecting and classifying wafer defects using machine learning techniques. The solutions take only one coarse resolution digital microscope image of a target wafer, and use machine learning techniques to process the coarse SEM image to review and classify a defect on the target wafer. Because only one coarse SEM image of the wafer is needed, the defect review and classification throughput and efficiency are improved. Further, the techniques are not distractive and may be integrated with other defect detecting and classification techniques.

    METHOD AND SYSTEM FOR DIAGNOSING A SEMICONDUCTOR WAFER

    公开(公告)号:US20190164264A1

    公开(公告)日:2019-05-30

    申请号:US15919428

    申请日:2018-03-13

    Abstract: Methods and systems for diagnosing a semiconductor wafer are provided. A first raw image, a second raw image, and a third raw image of the semiconductor wafer are obtained by an inspection apparatus according to graphic data system (GDS) information regarding layout of a target die. A first image-based comparison is performed by a determining circuitry on the first, second, and third raw images, so as to provide a comparison result. The comparison result indicates whether an image difference is present between the first, second, and third raw images.

    MACHINE LEARNING ON WAFER DEFECT REVIEW

    公开(公告)号:US20220359154A1

    公开(公告)日:2022-11-10

    申请号:US17870654

    申请日:2022-07-21

    Abstract: This disclosure is directed to solutions of detecting and classifying wafer defects using machine learning techniques. The solutions take only one coarse resolution digital microscope image of a target wafer, and use machine learning techniques to process the coarse SEM image to review and classify a defect on the target wafer. Because only one coarse SEM image of the wafer is needed, the defect review and classification throughput and efficiency are improved. Further, the techniques are not distractive and may be integrated with other defect detecting and classification techniques.

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