Patent ID: 11860973
Assignee: APPLIED MATERIALS, INC.
Field: Semiconductors (Electrical engineering)
Classification: CPC G  H  C  B | IPC G  H

Claim 7:
8. A non-transitory computer-readable medium comprising instructions for executing a method for foreline deposition diagnostics, the method comprising:
receiving sensor data from at least one of a plurality of sensors;
providing the sensor data to a build-up monitor comprising a trained machine learning (ML) model configured to generate an output indicating deposition build-up, wherein the trained ML model is trained via a process comprising:
receiving sensor training data from a database comprising sensor data from prior operation of a semiconductor processing chamber;
classifying the sensor training data to differentiate between a clean surface of the foreline and a deposition thickness of a material deposited on the foreline; and
generating model parameters for the trained machine learning model based on the classifying; and

generating a corrective action based on the output when the sensor data is indicated to be at or above a build-up threshold.