Information processing method, information processing apparatus, and substrate processing system

An information processing apparatus comprising:

• an acquisitor configured to acquire time series data from a plurality of types of sensors having different sampling periods provided in a substrate processing apparatus;
• a learner configured to perform learning of first learning models that output information relating to the substrate processing apparatus in a case where the time series data from the sensors are input, using each of the pieces of time series data having different sampling periods for each of the sensors individually;
• and
• an estimator configured to input the time series data from the sensors into the corresponding first learning models after learning to output an estimation result based on information obtained from the first learning models.

A substrate processing system comprising:

• a plurality of substrate processing apparatuses configured to include edge devices connected to sensors and a host device connected to the edge devices, and execute substrate processing inside a chamber;
• and
• an apparatus group server communicably connected to the plurality of substrate processing apparatuses, wherein
• each of the edge devices includes
• an acquisitor configured to acquire time series data from one of a plurality of types of sensors having different sampling periods,
• a first learner configured to perform learning of a first learning model that outputs information relating to the substrate processing apparatus on which the sensor is provided in a case where the time series data from the one of a plurality of types of sensors is input based on the acquired time series data,
• a first estimator configured to input the time series data from the one of a plurality of types of sensors into the first learning model after learning to output an estimation result based on information obtained from the first learning model, and
• an output configured to output a first feature value extracted from the time series data to the host device,
• the host device includes
• a first feature value storage configured to store the first feature value input from the edge device,
• a second learner configured to perform learning of a second learning model that outputs the information relating to the substrate processing apparatus in a case where the first feature value is input based on the stored first feature value,
• a second estimator configured to input a newly acquired first feature value into a second learning model after learning to output an estimation result based on information obtained from the second learning model, and
• a transmitter configured to transmit a second feature value of the time series data extracted for each substrate processing apparatus to the apparatus group server, and
• the apparatus group server includes
• a second feature value storage configured to store the second feature value received from the host device,
• a third learner configured to perform learning of a third learning model that outputs the information relating to the substrate processing apparatus in a case where the second feature value is input based on the stored second feature value, and
• a third estimator configured to input a newly acquired second feature value to a third learning model after the learning to output an estimation result based on information obtained from the third learning model.