PDF Solutions, Inc.
Semiconductor yield prediction

Abstract:

A method for predicting yield for a semiconductor process. A particular type of wafer is fabricated to have a first set of features disposed on the wafer, with a wafer map identifying a location for each of the first set of features on the wafer. Data from wafer acceptance tests and circuit probe tests is collected over time for wafers of that particular type as made in a semiconductor fabrication process, and at least one training dataset and a least one validation dataset are created from the collected data. A second set of "engineered" features are created and also incorporated onto the wafer and wafer map. Important features from the first and second sets of features are identified and selected, and using those important features as inputs, a number of different process models are run, with yield as the target. The results of the different models can be combined, for example, statistically.