In a controller, a machine learning device, and a system that are capable of addressing change in a clamping force without use of expensive equipment, the controller includes the machine learning device that observes machining condition data indicating machining conditions for cutting, spindle torque data indicating spindle torque during the cutting, and cutting force component direction data indicating cutting force component direction information on cutting resistance against a cutting force, as state variables representing a current state of an environment, and that carries out learning or decision making with use of a learning model modelling the machining conditions for the cutting on which the cutting force that allows holding by a clamping force from a machining jig is exerted on a workpiece based on the state variables.

In a controller, a machine learning device, and a system that are capable of addressing change in a clamping force without use of expensive equipment, the controller includes the machine learning device that observes machining condition data indicating machining conditions for cutting, spindle torque data indicating spindle torque during the cutting, and cutting force component direction data indicating cutting force component direction information on cutting resistance against a cutting force, as state variables representing a current state of an environment, and that carries out learning or decision making with use of a learning model modelling the machining conditions for the cutting on which the cutting force that allows holding by a clamping force from a machining jig is exerted on a workpiece based on the state variables.