PROCESS WINDOW BASED ON FAILURE RATE
    1.
    发明申请

    公开(公告)号:WO2022002599A1

    公开(公告)日:2022-01-06

    申请号:PCT/EP2021/066324

    申请日:2021-06-17

    Abstract: Described herein is a method for determining a process window of a patterning process based on a failure rate. The method includes (a) obtaining a plurality of features printed on a substrate, (b) grouping, based on a metric, the features into a plurality of groups, and (c) generating, based on measurement data associated with a group of features, a base failure rate model for the group of features, wherein the base failure rate model identifies the process window related to the failure rate of the group of features. The method further includes generating, using the base failure rate model, a feature-specific failure rate model for a specific feature, wherein the feature-specific failure rate model identifies a feature-specific process window such that an estimated failure rate of the specific feature is below a specified threshold.

    DETERMINING HOT SPOT RANKING BASED ON WAFER MEASUREMENT

    公开(公告)号:WO2020064544A1

    公开(公告)日:2020-04-02

    申请号:PCT/EP2019/075326

    申请日:2019-09-20

    Abstract: A method of hot spot ranking for a patterning process. The method includes obtaining (i) a set of hot spots of a patterning process, (ii) measured values of parameters of the patterning process corresponding to the set of hot spots, and (ii) simulated values of the parameters of the patterning process corresponding to the set of hot spots; determining a measurement feedback based on the measured values and the simulated values of the parameters of the patterning process; and determining, via simulation of a process model of the patterning process, a ranking of a hot spot within the set of hot spots, generated by the simulation, based on the measurement feedback.

    METHOD OF EVALUATING SELECTED SET OF PATTERNS

    公开(公告)号:WO2023030807A1

    公开(公告)日:2023-03-09

    申请号:PCT/EP2022/071659

    申请日:2022-08-02

    Abstract: Described herein is systems and methods for evaluating selected set of patterns of a design layout. A method herein includes obtaining (i) a first pattern set resulting from a pattern selection process, (ii) first pattern data associated with the first pattern set, (iii) characteristic data associated with the first pattern data, and (iv) second pattern data associated with a second pattern set. A machine learning model is trained based on the characteristic data, where the machine learning model being configured to predict pattern data for an input pattern. The second pattern set is input to the trained machine learning model to predict second pattern data of the second pattern set. The first pattern set is evaluated by comparing the second pattern data and the predicted second pattern data. If the evaluation indicates insufficient pattern coverage, additional patterns can be included to improve the pattern coverage.

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