Rational decision-making tool for semiconductor processes
AssigneePDF Solutions, Inc.
InventorsTomonori Honda, Lin Lee Cheong, Lakshmikar Kuravi, Bogdan Cirlig
Life of this patent
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Abstract
A robust predictive model. A plurality of different predictive models for a target feature are run, and a comparative analysis provided for each predictive model that meet minimum performance criteria for the target feature. One of the predictive models is selected, either manually or automatically, based on predefined criteria. For semi-automatic selection, a static or dynamic survey is generated for obtaining user preferences for parameters associated with the target feature. The survey results will be used to generate a model that illustrates parameter trade-offs, which will be used to finalize the optimal predictive model for the user.
Claims27
A method for generating a robust predictive model for a target feature in a semiconductor process, comprising:
- identifying a plurality of minimum performance criteria for the target feature;
- generating a plurality of different predictive models each configured to predict the target feature;
- for each of the plurality of predictive models that meet the plurality of minimum performance criteria for the target feature, comparing a plurality of true positive results for the target feature with a plurality of false positive results for the target feature;
- based on defined selection criteria for the comparison of true positive results with false positive results, selecting one of the plurality of predictive models that meet the plurality of minimum performance criteria;
- and
- deploying the selected predictive model into the semiconductor process.
A method for generating a robust predictive model for a target feature in a semiconductor process, comprising:
- identifying a plurality of minimum performance criteria for the target feature;
- generating a plurality of different predictive models each configured to predict the target feature;
- performing a comparative analysis of results from each of the plurality of predictive models that meet the plurality of minimum performance criteria for the target feature;
- displaying the comparative analysis of results in a user interface;
- receiving user input from the user interface to establish customer preferences and/or customer utility for each of a plurality of key parameters associated with the target feature;
- selecting one of the plurality of predictive models that meet the plurality of minimum performance criteria based on the customer preferences and/or customer utility for each of the plurality of key parameters;
- and
- deploying the selected predictive model into the semiconductor process.
A robust predictive model for predicting a target feature in a semiconductor process including a processor and non-transitory storage for program instruction, the program instructions configured for causing the processor to:
- identify a plurality of minimum performance criteria for the target feature;
- generate a plurality of different predictive models each configured to predict the target feature;
- perform a comparative analysis of results from each of the plurality of predictive models that meet the plurality of minimum performance criteria for the target feature;
- display the comparative analysis of results in a user interface;
- receive user input through the user interface to establish customer preferences and/or customer utility for each of a plurality of key parameters associated with the target feature;
- and
- select one of the plurality of predictive models that meet the plurality of minimum performance criteria based on the customer preferences and/or customer utility for each of the plurality of key parameters.
Dependencies are inferred from the claim text.