Random forest model for prediction of chip layout attributes

    公开(公告)号:US10885259B2

    公开(公告)日:2021-01-05

    申请号:US16557945

    申请日:2019-08-30

    Abstract: An improved random forest model is provided, which has been trained based on silicon data generated from tests of previously fabricated chips. An input is provided to the random forest model, the input including a feature set of a pattern within a particular chip layout, the feature set identifying geometric attributes of polygonal elements within the pattern. A result is generated by the random forest model based on the input, where the result identifies a predicted attribute of the pattern based on the silicon data, and the result is generated based at least in part on determining, within the random forest model, that geometric attributes of the pattern were included in the previously fabricated chips, where the previously fabricated chips have chip layouts are different from the particular chip layout.

    RANKING OF OBJECTS WITH NOISY MEASUREMENTS
    12.
    发明申请

    公开(公告)号:US20200005451A1

    公开(公告)日:2020-01-02

    申请号:US16557906

    申请日:2019-08-30

    Abstract: A method includes, for each data object of a plurality of data objects, performing a measurement on a plurality of instances of the data object to generate a plurality of measurement values for the data object, and generating a distribution of the measurement values for the data object. The method further includes generating an aggregate distribution based on each of the distributions of the measurement values generated for the data objects, and scoring a first data object of the plurality of data objects based on the distribution of the measurement values for the first data object and the aggregate distribution.

    Unsupervised clustering to identify anomalies

    公开(公告)号:US11282189B2

    公开(公告)日:2022-03-22

    申请号:US16572594

    申请日:2019-09-16

    Abstract: Images are accessed representing a status in a fabrication of a semiconductor chip corresponding to a particular stage in the fabrication. Distortion is removed from the images and actual features of the semiconductor chip are extracted from the images. Synthesized ideal features of the semiconductor chip associated with completion of the particular stage in the fabrication are determined from the one or more images. The actual features are compared to the ideal features to determine whether anomalies associated with the particular stage exist in the semiconductor chip.

    UNSUPERVISED CLUSTERING TO IDENTIFY ANOMALIES

    公开(公告)号:US20200013157A1

    公开(公告)日:2020-01-09

    申请号:US16572594

    申请日:2019-09-16

    Abstract: Images are accessed representing a status in a fabrication of a semiconductor chip corresponding to a particular stage in the fabrication. Distortion is removed from the images and actual features of the semiconductor chip are extracted from the images. Synthesized ideal features of the semiconductor chip associated with completion of the particular stage in the fabrication are determined from the one or more images. The actual features are compared to the ideal features to determine whether anomalies associated with the particular stage exist in the semiconductor chip

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