OPTIMIZATING SEMICONDUCTOR BINNING BY FEED-FORWARD PROCESS ADJUSTMENT

    公开(公告)号:US20190122911A1

    公开(公告)日:2019-04-25

    申请号:US15791451

    申请日:2017-10-24

    Abstract: One or more processors determine a predicted sorting bin of a semiconductor device, based on measurement and test data performed on the semiconductor device subsequent to a current metallization layer. A current predicted sorting bin and a target soring bin are determined by a machine learning model for the semiconductor device; the target bin include higher performance semiconductor devices than the predicted sorting bin. The model determines a performance level improvement attainable by adjustments made to process parameters of subsequent metallization layers of the semiconductor device. Adjustments to process parameters are generated, based on measurement and test data of the current metallization layer of semiconductor device, and the adjustment outputs for the process parameters of the subsequent metallization layers of the semiconductor device are made available to the one or more subsequent metallization layer processes by a feed-forward mechanism.

    OPTIMIZATING SEMICONDUCTOR BINNING BY FEED-FORWARD PROCESS ADJUSTMENT

    公开(公告)号:US20210249288A1

    公开(公告)日:2021-08-12

    申请号:US17244084

    申请日:2021-04-29

    Abstract: One or more processors determine a predicted sorting bin of a semiconductor device, based on measurement and test data performed on the semiconductor device subsequent to a current metallization layer. A current predicted sorting bin and a target sorting bin are determined by a machine learning model for the semiconductor device; the target bin include higher performance semiconductor devices than the predicted sorting bin. The model determines a performance level improvement attainable by adjustments made to process parameters of subsequent metallization layers of the semiconductor device. Adjustments to process parameters are generated, based on measurement and test data of the current metallization layer of semiconductor device, and the adjustment outputs for the process parameters of the subsequent metallization layers of the semiconductor device are made available to the one or more subsequent metallization layer processes by a feed-forward mechanism.

    Optimizing semiconductor binning by feed-forward process adjustment

    公开(公告)号:US11049744B2

    公开(公告)日:2021-06-29

    申请号:US15791451

    申请日:2017-10-24

    Abstract: One or more processors determine a predicted sorting bin of a semiconductor device, based on measurement and test data performed on the semiconductor device subsequent to a current metallization layer. A current predicted sorting bin and a target soring bin are determined by a machine learning model for the semiconductor device; the target bin include higher performance semiconductor devices than the predicted sorting bin. The model determines a performance level improvement attainable by adjustments made to process parameters of subsequent metallization layers of the semiconductor device. Adjustments to process parameters are generated, based on measurement and test data of the current metallization layer of semiconductor device, and the adjustment outputs for the process parameters of the subsequent metallization layers of the semiconductor device are made available to the one or more subsequent metallization layer processes by a feed-forward mechanism.

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