Invention Application
- Patent Title: MACHINE LEARNING ON WAFER DEFECT REVIEW
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Application No.: US17870654Application Date: 2022-07-21
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Publication No.: US20220359154A1Publication Date: 2022-11-10
- Inventor: Chung-Pin CHOU , Sheng-Wen HUANG , Jun-Xiu LIU
- Applicant: Taiwan Semiconductor Manufacturing Co., Ltd.
- Applicant Address: TW Hsinchu
- Assignee: Taiwan Semiconductor Manufacturing Co., Ltd.
- Current Assignee: Taiwan Semiconductor Manufacturing Co., Ltd.
- Current Assignee Address: TW Hsinchu
- Main IPC: H01J37/28
- IPC: H01J37/28 ; H01J37/22 ; G06N20/00 ; H01J37/26 ; H01J37/153

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.
Public/Granted literature
- US11935722B2 Machine learning on wafer defect review Public/Granted day:2024-03-19
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