PDF Solutions, Inc.
Failure detection and classsification using sensor data and/or measurement data
Last updated:
Abstract:
A model is generated for predicting failures at the wafer production level. Input data from sensors is stored as an initial dataset, then data exhibiting excursions or useless impact is removed from the dataset. The dataset is converted into target features, where the target features are useful in predicting whether a wafer will be normal or not. A trade-off between positive and negative results is selected, and a plurality of predictive models are created. The final model is selected based on the trade-off criteria, and deployed.
Status:
Grant
Type:
Utility
Filling date:
8 Mar 2019
Issue date:
8 Jun 2021