Abstract: A spindle vibration measuring system which measures vibration of a spindle in a machining device that performs a cutting or abrading process on a workpiece. The machining device has a workpiece holder that holds the workpiece, the spindle that holds a tool, and a moving mechanism that relatively moves the workpiece holder and the spindle. The spindle vibration measuring system acquires positional variation data or vibration data of the moving mechanism when the spindle rotates, and a result related to vibration of the spindle to output or store based on the positional variation data or the vibration data.

Abstract: 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.

Abstract: A machine learning device of a controller observes, as state variables that express a current state of an environment, feeding amount data indicating a feeding amount per unit cycle of a tool and vibration amount data indicating a vibration amount of a cutting part of the tool when the cutting part of the tool passes through the workpiece. In addition, the machine learning device acquires determination data indicating a propriety determination result of the vibration amount of the cutting part of the tool when the cutting part of the tool passes through the workpiece. Then, the machine learning device learns the feeding amount per unit cycle of the tool when the cutting part of the tool passes through the workpiece in association with the vibration amount data, using the state variables and the determination data.

Abstract: A spindle vibration measuring system which measures vibration of a spindle in a machining device that performs a cutting or abrading process on a workpiece. The machining device has a workpiece holder that holds the workpiece, the spindle that holds a tool, and a moving mechanism that relatively moves the workpiece holder and the spindle. The spindle vibration measuring system acquires positional variation data or vibration data of the moving mechanism when the spindle rotates, and a result related to vibration of the spindle to output or store based on the positional variation data or the vibration data.

Abstract: 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.

Abstract: A numerical controller which compensates an estimated value of a thermal displacement amount of a machine tool is provided with an estimation unit comprising a learning model having learned the correlations between information on the temperature of the machine tool and information on a thermal displacement and configured to acquire the information on the temperature from the machine tool and calculate an estimated value of the thermal displacement, based on the information on the temperature and the learning model, a compensation condition acquisition unit configured to acquire positioning information from the machine tool, and a compensation unit configured to compensate the estimated value of the thermal displacement based on the positioning information.

Abstract: A machine learning device of a controller observes, as state variables that express a current state of an environment, feeding amount data indicating a feeding amount per unit cycle of a tool and vibration amount data indicating a vibration amount of a cutting part of the tool when the cutting part of the tool passes through the workpiece. In addition, the machine learning device acquires determination data indicating a propriety determination result of the vibration amount of the cutting part of the tool when the cutting part of the tool passes through the workpiece. Then, the machine learning device learns the feeding amount per unit cycle of the tool when the cutting part of the tool passes through the workpiece in association with the vibration amount data, using the state variables and the determination data.