A machine tool includes: a spindle that causes a tool to rotate and move; a workpiece rotation mechanism that causes a workpiece W to rotate; a control unit that controls the spindle and the workpiece rotation mechanism in accordance with commands from a program; and a cutting load detection unit that detects a cutting load imparted on the workpiece by the tool, and the control unit controls a cutting route such that a cutting depth of the workpiece cut with the tool in a region with a small cutting load is greater than the cutting depth in a region with a large cutting load within such a range that the cutting load detected by the cutting load detection unit does not exceed a predetermined load.

A numerical control device includes a control computation unit controlling a spindle as a rotation axis of a workpiece, a first shaft driving a tool performing vibration cutting machining on the workpiece, and a second shaft driving a tool performing vibration cutting machining on the workpiece. The computation unit includes: a storage unit storing a machining program; a determination unit determining whether the number of vibrations of the first shaft and the second shaft follows a rotation speed of the spindle specified by the machining program; and a number-of-vibrations calculation unit that, in response to the determination that the number of vibrations of at least one of the first shaft and the second shaft does not follow the rotation speed of the spindle, calculates the number of vibrations following the rotation speed of the spindle for the drive shaft assessed as not following it.

A numerical control device includes a control computation unit to control a spindle that is a rotation axis of a machining target, first and second drive axes to drive a first tool and a second tool, respectively, to perform vibration cutting machining on the machining target. The control computation unit includes a machine learning device to learn a pass/fail prediction in which whether the vibration cutting machining passes is predicted. The machine learning device includes: an observation unit to observe a state variable including a vibration cutting condition for the first and second drive axes for the vibration cutting machining; a data acquisition unit to acquire pass/fail information indicating whether the vibration cutting machining has passed; and a learning unit to learn the pass/fail prediction according to a data set based on a combination of the state variable and the pass/fail information.

A machine learning device for performing machine learning with respect to a numerical control device which causes a machine tool to operate, and is provided with: a state information acquisition unit that causes the machine tool to perform cutting work, in which a cutting amount and a cutting rate are set, and acquires state information including the cutting amount and cutting rate; an action information output unit that outputs action information; a reward calculation unit that acquires determination information that is information about the strength of pressure applied to a tool at least during cutting work, the shape of the waveform of the pressure applied to the tool, and time it has taken to perform work, and outputs a reward value in reinforcement learning; and a value function update unit that updates a value function on the basis of the reward value, the state information, and the action information.

This machining assistance apparatus, which calculates various types of data relating to the machining by a machine tool that cuts a workpiece into a polygon shape by rotating the workpiece and the tool at a constant rate, receives input of information relating to the machining, including information relating to the number of polygon surfaces of the workpiece formed by cutting and the number of blades attached to the tool, sets in advance the axial rotation speed of the tool and the workpiece, calculates the rotation speed ratio of the tool with respect to the number of polygon surfaces on the basis of the number of polygon surfaces and the number of blades, calculates an axial rotation speed, or a candidate thereof, of the tool and the workpiece on the basis of the rotation speed ratio within the set range of the axial rotation speed of the tool and workpiece, and outputs and displays the calculation result on a display unit that is connected to the machining assistance apparatus.