Machine learning platform for substrate processing

A method of operating a substrate processing facility, the method comprising:

• identifying current data associated with current substrate lots of the substrate processing facility;
• identifying current features associated with the current data;
• providing the current features to a trained machine learning model that was trained based on historical features, the historical features being generated based on at least one of historical data for historical substrate lots or simulated data for simulated substrate lots;
• obtaining, from the trained machine learning model, one or more outputs;
• and
• causing, based on the one or more outputs, performance of one or more corrective actions associated with the substrate processing facility.

A non-transitory machine-readable storage medium storing instructions which, when executed cause a processing device to perform operations comprising:

• identifying at least one of historical data associated with historical substrate lots processed by substrate processing tools in a substrate processing facility or simulated data for simulated substrate lots processed by simulated substrate processing tools;
• generating features from the at least one of the historical data for the historical substrate lots or the simulated data for the simulated substrate lots;
• and
• training a machine learning model with data input comprising the features to generate a trained machine learning model, the trained machine learning model being capable of generating one or more outputs indicative of one or more corrective actions to be performed in the substrate processing facility.