Prediction of Failure Probabilities of Chips of a Wafer
AssigneeRobert Bosch GmbH
InventorsEric Sebastian Schmidt, Stefan Patrick Lindt
Life of this patent
Estimating the term…
Abstract
A method is for teaching a machine learning system to predict failure probabilities of chips on a wafer. The method is based on a prediction of final test yields depending on wafer-level test measurements by the machine learning system. The machine learning system predicts the failure probabilities of the chips depending on the wafer-level test measurements, and the predicted failure probabilities are aggregated to the predicted final test yields. The machine learning system is trained, such that a math difference between predicted final test yields and final test yields from a training data set is minimized. Differences between the predicted final test yields and final test yields from a training data set are minimized.
Claims9
A method for teaching a machine learning system to predict failure probabilities of chips on a wafer, comprising:
- providing a training data set comprising a plurality of wafers, each with wafer-level test measurements and an associated final test yield;
- repeating several times:
- drawing a plurality of wafer-level test measurements and associated final test yields,
- predicting final test yields depending on the plurality of wafer-level test measurements by the machine learning system, wherein the machine learning system determines the failure probabilities of the chips on the wafer depending on the plurality of wafer-level test measurements,
- aggregating the determined failure probabilities to the predicted final test yields, and
- teaching the machine learning system, such that a mathematical difference between the predicted final test yield and the assigned final test yield is minimized.
Dependencies are inferred from the claim text.