Waviness prediction device, waviness prediction method, processing method for polishing target article, and program

A waviness prediction method, comprising:

• a) receiving an input of waviness data obtained by measuring waviness of a polishing target surface that is polished by rotating a polishing pad with a planetary gear mechanism;
• b) obtaining a feature including both a number of processed polishing targets in the polishing pad, and a torque of a sun gear;
• and
• c) predicting the waviness by inputting the obtained feature to a prediction model that learns a relationship between the feature and the waviness data,
• a), b), and c) being performed by a computer.

A processing method for a polishing target, the processing method comprising:

• a) receiving an input of waviness data obtained by measuring waviness of a polishing target surface that is polished by rotating a polishing pad with a planetary gear mechanism;
• b) obtaining a feature including both a number of processed polishing targets in the polishing pad, and a torque of a sun gear;
• c) predicting the waviness by inputting the obtained feature obtained in the feature obtainment procedure to a prediction model that learns a relationship between the feature and the waviness data;
• d) comparing a prediction value of the waviness with a predetermined threshold;
• e) searching for a processing condition that the prediction value of the waviness becomes lower than the threshold, when the prediction value of the waviness is equal to or higher than the threshold,
• a), b), c), d), and e) being executed by a computer;
• and
• f) processing the polishing target based on the processing condition that is found in e),
• f) being performed by a polisher.

A non-transitory computer-readable recording medium storing a program for causing a computer to execute:

• receiving an input of waviness data obtained by measuring waviness of a polishing target surface that is polished by rotating a polishing pad with a planetary gear mechanism;
• obtaining a feature including both a number of processed polishing targets in the polishing pad, and a torque of a sun gear;
• and
• predicting the waviness by inputting the obtained feature to a prediction model that learns a relationship between the feature and the waviness data.