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.

    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.

    MACHINE LEARNING ON WAFER DEFECT REVIEW
    7.
    发明申请

    公开(公告)号:US20200105500A1

    公开(公告)日:2020-04-02

    申请号:US16430323

    申请日:2019-06-03

    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.

    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.

    INSPECTION METHOD AND APPARATUS
    9.
    发明申请

    公开(公告)号:US20200264111A1

    公开(公告)日:2020-08-20

    申请号:US16278083

    申请日:2019-02-16

    Abstract: A method includes generating a primary radiation beam from a radiation source; splitting the primary beam into a first radiation beam and a second radiation beam; directing the first radiation beam onto a front side of a wafer; directing the second radiation beam onto a back side of a wafer; generating an image of the front side of the wafer by receiving a reflection of the first radiation beam reflected from the wafer; and generating an image of the back side of the wafer by receiving a reflection of the second radiation beam reflected from the wafer.

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