Process control knob estimation

A method, comprising:

• receiving, by a processing device, training data comprising (i) first sensor data indicating a first state of a coating of a first processing chamber processing a substrate subsequent to a chamber recovery procedure performed on the first processing chamber, (ii) first substrate process data indicating a first set of process parameter values associated with performing a first substrate processing procedure by the first processing chamber having the coating in a second state prior to the chamber recovery procedure, and (iii) second substrate process data indicating a first update to at least one of the first set of process parameter values, wherein the first update is associated with performing the first substrate processing procedure by the first processing chamber having the coating in the first state;
• and
• training, by the processing device, one or more machine learning models (MLMs) with (i) input data comprising the first sensor data and the first substrate process data and (ii) target output comprising the second substrate process data, wherein the one or more trained MLMs are to receive a new input having new sensor data indicating a third state of the coating of a new processing chamber processing a new substrate subsequent to the chamber recovery procedure and third substrate process data indicating a second set of process parameter values associated with performing the first substrate processing procedure by the new processing chamber having the coating in a fourth state prior to the chamber recovery procedure to produce a new output based on the new input, the new output indicating a second update to at least one of the second set of process parameter values, wherein the second update is associated with performing the first substrate processing procedure by the new processing chamber having the coating in the third state.