Information processing apparatus, inference apparatus, machine-learning apparatus, information processing method, inference method, and machine-learning method

An inference apparatus comprising:

• a memory;
• and
• a processor configured to perform:
• an information acquisition process of acquiring polishing conditions including top-ring state information indicating a state of a top ring, polishing-table state information indicating a state of a polishing table, and polishing-fluid-supply-nozzle state information indicating a state of a polishing-fluid supply nozzle in chemical mechanical polishing of a substrate performed by a substrate processing apparatus including the polishing table configured to rotatably support a polishing pad, the top ring configured to press the substrate against the polishing pad, and the polishing-fluid supply nozzle configured to supply a polishing fluid onto the polishing pad;
• and
• an inference process of inferring substrate state information indicating a state of the substrate on which the chemical mechanical polishing is performed under the polishing conditions when the polishing conditions are acquired in the information acquisition process.

An inference apparatus comprising:

• a memory;
• and
• a processor configured to perform:
• an information acquisition process of acquiring stress information indicating stress applied to a substrate on which chemical mechanical polishing is performed by a substrate processing apparatus including a polishing table configured to rotatably support a polishing pad, a top ring configured to press the substrate against the polishing pad, and a polishing-fluid supply nozzle configured to supply a polishing fluid onto the polishing pad;
• and
• an inference process of inferring polishing quality information indicating a polishing quality of the substrate to which the stress indicated by the stress information is applied when the stress information is acquired in the information acquisition process.

A machine-learning apparatus comprising:

• a learning-data storage section storing multiple sets of learning data including polishing conditions and substrate state information, the polishing conditions including top-ring state information indicating a state of a top ring, polishing-table state information indicating a state of a polishing table, and polishing-fluid-supply-nozzle state information indicating a state of a polishing-fluid supply nozzle in chemical mechanical polishing of a substrate performed by a substrate processing apparatus including the polishing table configured to rotatably support a polishing pad, the top ring configured to press the substrate against the polishing pad, and the polishing-fluid supply nozzle configured to supply a polishing fluid onto the polishing pad, the substrate state information indicating a state of the substrate on which the chemical mechanical polishing is performed under the polishing conditions;
• a machine-learning section configured to cause a learning model to learn a correlation between the polishing conditions and the substrate state information by inputting the multiple sets of learning data to the learning model;
• and
• a learned-model storage section configured to store the learning model that has learned the correlation by the machine-learning section.

A machine-learning apparatus comprising:

• a learning-data storage section storing multiple sets of learning data including stress information and polishing quality information, the stress information indicating stress applied to a substrate on which chemical mechanical polishing is performed by a substrate processing apparatus including a polishing table configured to rotatably support a polishing pad, a top ring configured to press the substrate against the polishing pad, and a polishing-fluid supply nozzle configured to supply a polishing fluid onto the polishing pad, the polishing quality information indicating a polishing quality of the substrate to which the stress indicated by the stress information is applied;
• a machine-learning section configured to cause a learning model to learn a correlation between the stress information and the polishing quality information by inputting the multiple sets of learning data to the learning model;
• and
• a learned-model storage section configured to store the learning model that has learned the correlation by the machine-learning section.