Coating quality prediction device and learned model generation method

A coating quality prediction device comprising:

• a learned model that has learned a relationship between information regarding a paint, conditions at a time of applying the paint, and a variation in a coating color among a plurality of objects to be coated on which the paint is applied under the conditions;
• and
• a calculation unit that uses the learned model to calculate the variation in the coating color from the information regarding the paint and the conditions at the time of applying the paint.

A method for generating a learned model, the method comprising:

• acquiring training data including characteristics of a paint, conditions at a time of applying the paint, and a smoothness of a surface of a coating film obtained by applying the paint under the conditions;
• and
• using the training data to generate a learned model that outputs the smoothness of the surface of the coating film when the characteristics of the paint and the conditions at the time of applying the paint are input.

A method for generating a learned model, the method comprising:

• acquiring training data including information regarding a paint, conditions at a time of applying the paint, and a variation in a coating color among a plurality of objects to be coated on which the paint is applied under the conditions;
• and
• using the training data to generate a learned model that outputs the variation in the coating color when the information regarding the paint and the conditions at the time of applying the paint are input.