Abstract: An electric motor includes: a rotor; a stator disposed on an outer peripheral side of the rotor; a front-side housing provided with an opening housing a part of the rotor; a rear-side housing clamping the stator between the rear-side housing and the front-side housing; a plurality of fastening members fastening the stator, the front-side housing, and the rear-side housing together; and an annular portion disposed on a surface, of the front-side housing, the surface facing the stator and having an annular shape that surrounds the opening, wherein respective heights of first sections of the annular portion that are in the vicinity of insertion holes of the fastening members are lower than respective heights of second sections, which are positioned at middle points between an adjacent pair of the first sections, among the first sections, the intermediate point is close to the adjacent pair of the first sections.

Abstract: An electric motor includes: a rotor; a stator disposed on an outer peripheral side of the rotor; a front-side housing provided with an opening housing a part of the rotor; a rear-side housing clamping the stator between the rear-side housing and the front-side housing; a plurality of fastening members fastening the stator, the front-side housing, and the rear-side housing together; and an annular portion disposed on a surface, of the front-side housing, the surface facing the stator and having an annular shape that surrounds the opening, wherein respective heights of first sections of the annular portion that are in the vicinity of insertion holes of the fastening members are lower than respective heights of second sections, which are positioned at middle points between an adjacent pair of the first sections, among the first sections, the intermediate point is close to the adjacent pair of the first sections.

Abstract: A machine learning device and a machine learning method for optimizing timing at which a tool is to be compensated in a machine tool, and a machine tool including the machine learning device. The machine learning device includes a state observation unit for observing a time interval for compensating the tool, a processing error amount of a workpiece processed by the machine tool, and a machine working ratio of the machine tool as state variables, and a learning unit for learning an action value with respect to a change of a tool compensation interval based on the tool compensation interval, the processing error amount of a workpiece, and the machine working ratio that are observed by the state observation unit.

Abstract: A machine learning device and a machine learning method for optimizing timing at which a tool is to be compensated in a machine tool, and a machine tool including the machine learning device. The machine learning device includes a state observation unit for observing a time interval for compensating the tool, a processing error amount of a workpiece processed by the machine tool, and a machine working ratio of the machine tool as state variables, and a learning unit for learning an action value with respect to a change of a tool compensation interval based on the tool compensation interval, the processing error amount of a workpiece, and the machine working ratio that are observed by the state observation unit.

Abstract: The motor control device of the present invention comprises a sensor gear expansion amount estimation part which estimates the amount of expansion of a sensor gear, a sensor mount expansion amount estimation part which estimates the amount of expansion of a sensor mount, a sensor gear expansion amount correction part which corrects the estimated amount of expansion of the sensor gear, and a rotor temperature estimation part which estimates the temperature of the rotor based on the corrected sensor gear expansion amount of the sensor gear.