Abstract: A cool cluster comprises one or more transfer chambers; a plurality of process chambers connected to the one or more transfer chambers; and a computing device of the tool cluster. The computing device is to receive first measurements generated by sensors of a first process chamber during or after a process is performed within the first process chamber; determine that the first process chamber is due for maintenance based on processing the first measurements using a first trained machine learning model; after maintenance has been performed on the first process chamber, receive second measurements generated by the sensors during or after a seasoning process is performed within the first process chamber; and determine that the first process chamber is ready to be brought back into service based on processing the second measurements using a second trained machine learning model.

Abstract: A substrate processing system comprises one or more transfer chambers; a plurality of process chambers connected to the one or more transfer chambers; and a computing device connected to each of the plurality of process chambers. The computing device is to receive first measurements generated by sensors of a first process chamber during or after a process is performed within the first process chamber; determine that the first process chamber is due for maintenance based on processing the first measurements using a first trained machine learning model; after maintenance has been performed on the first process chamber, receive second measurements generated by the sensors during or after a seasoning process is performed within the first process chamber; and determine that the first process chamber is ready to be brought back into service based on processing the second measurements using a second trained machine learning model.

Abstract: A substrate processing system comprises one or more transfer chambers; a plurality of process chambers connected to the one or more transfer chambers; and a computing device connected to each of the plurality of process chambers. The computing device is to receive first measurements generated by sensors of a first process chamber during or after a process is performed within the first process chamber; determine that the first process chamber is due for maintenance based on processing the first measurements using a first trained machine learning model; after maintenance has been performed on the first process chamber, receive second measurements generated by the sensors during or after a seasoning process is performed within the first process chamber; and determine that the first process chamber is ready to be brought back into service based on processing the second measurements using a second trained machine learning model.

Abstract: A method of forming a multi-layer stack on a substrate comprises: processing a substrate in a first process chamber using a first deposition process to deposit a first layer of a multi-layer stack on the substrate; removing the substrate from the first process chamber; measuring a first thickness of the first layer using an optical sensor; determining, based on the first thickness of the first layer, a target second thickness for a second layer of the multi-layer stack; determining one or more process parameter values for a second deposition process that will achieve the second target thickness for the second layer; and processing the substrate in a second process chamber using the second deposition process with the one or more process parameter values to deposit the second layer of the multi-layer stack approximately having the target second thickness over the first layer.

Abstract: A substrate processing system comprises an etch chamber configured to perform an etch process on a substrate, the etch chamber comprising an optical sensor to generate one or more optical measurements of a film on the substrate during and/or after the etch process. The system further comprises a computing device operatively connected to the etch chamber, wherein the computing device is to: receive the one or more optical measurements of the film; determine, for each optical measurement of the one or more optical measurements, a film thickness of the film; determine an etch rate of the film based on the one or more optical measurements using the determined film thickness of each optical measurement of the one or more optical measurements; and determine a process parameter value of at least one process parameter for a previously performed process that was performed on the substrate based on the etch rate.