CPC G06F 18/214 (2023.01) [G06F 18/24 (2023.01); G06N 20/00 (2019.01); H01L 21/0206 (2013.01); H01L 21/02019 (2013.01)] | 20 Claims |
1. A system for foreline diagnostics and control, comprising:
a foreline coupled to an exhaust of a processing chamber;
a sensor positioned to measure deposition build-up in the foreline; and
a build-up monitor coupled to the first sensor, the build-up monitor comprising a trained machine learning (ML) model and configured to generate an output indicating deposition build-up and trigger a corrective action when the indicated deposition build-up is at or above a build-up threshold, 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.
|