Machine learning device, machined state prediction device, and control device

A machine learning device, comprising:

• a non-transitory memory configured to store a program;
• a processor configured to execute the program stored on the memory to cause the machine learning device to:
• obtain, as input data, machining information for burnishing in which surface treatment was performed by pressing an arbitrary tool against a machined surface of a workpiece, wherein the machining information including at least information on the workpiece before the burnishing and information on a machining condition for the burnishing;
• obtain label data indicating machined state information including a machined state of the workpiece after the burnishing and a surface roughness of the workpiece in a case where the machined state is normal;
• and
• use the obtained input data and the obtained label data to execute supervised learning and generate a learned model that takes as an input machining information regarding burnishing to be performed and outputs machined state information for the burnishing to be performed,
• wherein the information on the workpiece before the burnishing includes surface roughness before machining of the workpiece,
• the machined state information includes a surface roughness after machining in the case where the machined state is normal,
• the machined state information outputted by the learned model is utilized to output an instruction to execute burnishing or an instruction to change the machining information, and
• further the machined state information outputted by the learned model is utilized to generate an operational command which are utilized by a machine tool to execute burnishing on the machining target workpiece.