Support device, support method, substrate processing system, and storage medium

A support device that supports adjustment of values of parameters of a substrate processing apparatus that operates based on the parameters to perform substrate processing, the parameters including detection target parameters of which corresponding physical quantities are to be detected, the support device comprising

• an arithmetic processing section that includes a processor and outputs parameter recommended values using a first machine learning model and a second learning model, the parameter recommended values being recommended values of the values of the parameters, wherein
• the arithmetic processing section is configured or programmed to
• build a predictive model that predicts quality of the substrate processing performed by the substrate processing apparatus through the first machine learning model performing learning of first training data that includes detection data pieces relating to the physical quantities and quality data relating to the quality of the substrate processing, the predictive model being configured to accept detection data pieces relating to the physical quantities as input thereto and to predict and output the quality of the substrate processing,
• acquire detection data recommended values by executing Bayesian optimization based on the predictive model, an acquisition function, and a search range, the detection data recommended values being recommended values of the detection data pieces such that the predictive model outputs the quality of the substrate processing closest to target quality,
• cause the second machine learning model to perform learning of the second training data including the detection data pieces and values of the detection target parameters that are set at detection of the physical quantities, the second machine learning model having performed the learning being configured to accept the detection data recommended values as input thereto and to output the parameter recommended values, and
• convert the detection data recommended values to the parameter recommended values by inputting the detection data recommended values to the second machine learning model having performed the learning.