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    INTEGRATED SUBSTRATE MEASUREMENT SYSTEM TO IMPROVE MANUFACTURING PROCESS PERFORMANCE
    2.
    发明申请
    INTEGRATED SUBSTRATE MEASUREMENT SYSTEM TO IMPROVE MANUFACTURING PROCESS PERFORMANCE 有权

    公开(公告)号：US20220028713A1

    公开(公告)日：2022-01-27

    申请号：US17379653

    申请日：2021-07-19

    申请人： APPLIED MATERIALS, INC.

    发明人： Upendra V. Ummethala ,  Blake Erickson ,  Prashanth Kumar ,  Michael Kutney ,  Steven Trey Tindel ,  Zhaozhao Zhu

    IPC分类号： H01L21/67 ,  H01L21/66

    摘要： A method for determining whether to modify a manufacturing process recipe is provided. A substrate to be processed at a manufacturing system according to the first process recipe is identified. An instruction to transfer the substrate to a substrate measurement subsystem to obtain a first set of measurements for the substrate is generated. The first set of measurements for the substrate is received from the substrate measurement subsystem. An instruction to transfer the substrate from the substrate measurement subsystem to a processing chamber is generated. A second set of measurements for the substrate is received from one or more sensors of the processing chamber. A first mapping between the first set of measurements and the second set of measurements for the substrate is generated. The first set of measurements mapped to the second set of measurements for the substrate is stored. A determination is made based on the first set of measurements mapped to the second set of measurements for the substrate of whether to modify the first process recipe or a second process recipe for the substrate.

    DETERMINING SUBSTRATE PROFILE PROPERTIES USING MACHINE LEARNING
    4.
    发明申请
    DETERMINING SUBSTRATE PROFILE PROPERTIES USING MACHINE LEARNING 有权

    公开(公告)号：US20230062206A1

    公开(公告)日：2023-03-02

    申请号：US18046872

    申请日：2022-10-14

    申请人： APPLIED MATERIALS, INC.

    发明人： Thomas Li ,  Upendra V. Ummethala ,  Blake Erickson ,  Prashanth Kumar ,  Michael Kutney ,  Steven Trey Tindel ,  Zhaozhao Zhu

    IPC分类号： G03F7/20

    摘要： Spectral data associated with a first prior substrate and/or a second prior substrate is obtained. A metrology measurement value associated with the first portion of the first prior substrate is determined based on one or more metrology measurement values measured for at least one of a second portion of the first prior substrate or a third portion of a second prior substrate. Training data for training a machine learning model to predict metrology measurement values of a current substrate is generated. Generating the training data includes generating a first training input including the spectral data associated with the first prior substrate and generating a first target output for the first training input, the first target output including the determined metrology measurement value associated with the first portion of the first prior substrate. The training data is provided to train the machine learning model.

    DETECTING AND CORRECTING SUBSTRATE PROCESS DRIFT USING MACHINE LEARNING
    7.
    发明申请
    DETECTING AND CORRECTING SUBSTRATE PROCESS DRIFT USING MACHINE LEARNING 有权

    公开(公告)号：US20220066411A1

    公开(公告)日：2022-03-03

    申请号：US17379728

    申请日：2021-07-19

    申请人： APPLIED MATERIALS, INC.

    发明人： Upendra V. Ummethala ,  Blake Erickson ,  Prashanth Kumar ,  Michael Kutney ,  Steven Trey Tindel ,  Zhaozhao Zhu

    IPC分类号： G05B19/401 ,  G06N20/00 ,  G06N5/04

    摘要： Methods and systems for detecting and correcting substrate process drift using machine learning are provided. Data associated with processing each of a first set of substrates at a manufacturing system according to a process recipe is provided as input to a trained machine learning model. One or more outputs are obtained from the trained machine learning model. An amount of drift of a first set of metrology measurement values for the first set of substrates from a target metrology measurement value is determined from the one or more outputs. Process recipe modification identifying one or more modifications to the process recipe is also determined. For each modification, an indication of a level of confidence that a respective modification to the process recipe satisfies a drift criterion for a second set of substrates is determined. In response to an identification of the respective modification with a level of confidence that satisfies a level of confidence criterion, the process recipe is updated based on the respective modification.

    PLASMA EMISSION MONITORING SYSTEM WITH CROSS-DISPERSION GRATING
    8.
    发明申请
    PLASMA EMISSION MONITORING SYSTEM WITH CROSS-DISPERSION GRATING 审中-公开

    公开(公告)号：US20200340858A1

    公开(公告)日：2020-10-29

    申请号：US16828609

    申请日：2020-03-24

    申请人： Applied Materials, Inc.

    发明人： Philip Allan Kraus ,  Kelvin Chan ,  Travis Koh ,  Blake Erickson ,  Upendra Ummethala

    IPC分类号： G01J3/18 ,  G02B6/42 ,  G01J3/02

    摘要： Embodiments disclosed herein include an optical sensor system. In an embodiment, the optical sensor system comprises a processing chamber and a sensor. In an embodiment, the sensor comprises a first diffraction grating oriented in a first direction, a second diffraction grating oriented in a second direction, and a detector for detecting electromagnetic radiation diffracted from the first grating and the second grating. In an embodiment, the optical sensor system further comprises an optical coupling element, where the optical coupling element optically couples an interior of the processing chamber to the sensor.