Patent ID: 11972987
Assignee: PDF SOLUTIONS, INC.
Field: Semiconductors (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 11:
12. A method, comprising:
obtaining testing data for a plurality of process control parameters from a plurality of test sites formed on and distributed across a semiconductor wafer, the testing data obtained prior to slicing a multiplicity of dies from the wafer;
obtaining a die level map of the semiconductor wafer, the map including graphical details regarding a multiplicity of semiconductor features formed on each die and corresponding locations on the wafer for each of the multiplicity of features;
providing the testing data and the die level map as input data to a multiplicity of machine learning tree models, each one of the multiplicity of machine learning tree models corresponding to a respective one of the multiplicity of dies; and
wherein each of the multiplicity of machine learning tree models is programmed with instructions to learn non-linear relationships between each of the plurality of process control parameters and yield performance on the basis of the testing data and the die level map, and to impute each of the plurality of process control parameters for each respective die on the basis of the determined non-linear relationships, each of the multiplicity of machine learning tree models is initially configured from training sets of input data.