A robot system includes a robot that self-travels along a traveling shaft and is provided with a position detection sensor at a distal end, a support member that has a plurality of reference positions juxtaposed and supports a workpiece, a plurality of calibration members that are juxtaposed along the traveling shaft, and a control device, in which the calibration members each have a calibration position, and the control device is configured to cause the robot to move by a predetermined first distance along the traveling shaft, calibrate position coordinates of the robot based on position coordinates of the calibration positions detected by the position detection sensor, and subsequently calibrate position coordinates of the workpiece based on position coordinates of the reference positions detected by the position detection sensor.

A calculation formula learning unit sets a coefficient relating to a time lag element in a thermal displacement estimation calculation formula by machine learning while fixing a coefficient relating to measured data except the coefficient relating to the time lag element at a predetermined value based on a difference between a thermal displacement estimated value about a machine element calculated by substituting a measured data group into the thermal displacement estimation calculation formula and a thermal displacement actual measured value about the machine element; sets the coefficient relating to the measured data except the coefficient relating to the time lag element in the thermal displacement estimation calculation formula by machine learning based on the difference while fixing the coefficient relating to the time lag element at a predetermined value; and repeats the machine learning.

A thermal compensation control system for a machine tool having a milling cutter and a cutter driver includes a tool setting probe, a temperature sensor, a workpiece touch probe, and a controller. The cutter driver is connected to the milling cutter to drive the milling cutter to process the work piece based on a control signal. The tool setting probe is configured to detect a cutter length of the milling cutter. The temperature sensor is configured to sense a measured temperature of the cutter driver or the milling cutter. The workpiece touch probe is configured to measure processing errors of the processed work piece. The controller is configured to generate the control signal based on a processing instruction, a temperature compensation model, the cutter length, and the measured temperature. The controller is further configured to determine whether to modify the temperature compensation model based on the processing errors.

A machine tool includes a workpiece holding unit to hold a workpiece. A tool holding unit holds a tool. At least one of the workpiece holding unit and the tool holding unit is drivingly rotatable or drivingly movable in a predetermined direction to machine the workpiece with the tool. Temperature sensors are attached to members constituting the machine tool. An estimator calculates an environmental temperature system thermal displacement amount due to a heat source outside the machine tool. A correction magnification processor calculates an environmental temperature system thermal displacement correction amount. Another estimator calculates a driving system thermal displacement amount due to a heat source in the machine tool. A thermal displacement correction amount adder obtains and outputs a total thermal displacement correction amount based on which the machine tool performs thermal displacement correction control.

A thermal compensation control system for a machine tool having a milling cutter and a cutter driver includes a tool setting probe, a temperature sensor, a workpiece touch probe, and a controller. The cutter driver is connected to the milling cutter to drive the milling cutter to process the work piece based on a control signal. The tool setting probe is configured to detect a cutter length of the milling cutter. The temperature sensor is configured to sense a measured temperature of the cutter driver or the milling cutter. The workpiece touch probe is configured to measure processing errors of the processed work piece. The controller is configured to generate the control signal based on a processing instruction, a temperature compensation model, the cutter length, and the measured temperature. The controller is further configured to determine whether to modify the temperature compensation model based on the processing errors.

To provide a wire electric discharge machine which can appropriately perform thermal displacement correction of upper/lower guides even when the installation environment changes. Provided are a storage unit that stores temperatures of machine elements as temperature data, and a rendering unit that digitizes the installation environment and renders as environmental data. Additionally provided are a position command unit that commands a relative position of the upper/lower guides; and a relational expression calculation unit that sets the temperature data environmental data as input data, sets the relative position as training data, and calculates the relational expression by way of machine learning. Further provided are a relational expression decision unit that calculates a correction amount by substituting the temperature of the machine element into this relational expression, and in the case of error between the relative position of the upper/lower guides based on this correction amount and the relative position commanded by the position command unit being small, decides this relational expression as a formal relational expression; and a correction execution unit that performs correction on the relative position of the upper/lower guides using this relational expression.

A thermal displacement compensation system detects a state quantity indicating a state of an operation of a machine, infers a thermal displacement compensation amount of the machine from the detected state quantity, and performs a thermal displacement compensation of the machine based on the inferred thermal displacement compensation amount, of the machine. The thermal displacement compensation system generates a learning model by machine learning that uses a feature quantity and stores the generated learning model in association with a combination of specified conditions of the operation of the machine.

To provide a wire electric discharge machine capable of suitably and simply performing thermal displacement correction on upper and lower guides. Provided are a storage unit that stores temperatures of machine elements and actual values for relative positions of upper and lower guides to be associated with each other as associated data; and a relational expression calculation unit that infers and calculates a relational expression between the temperature of the machine element and the relative positions of the upper and lower guides by way of machine learning with this associated data as training data. Additionally provided are a position estimation unit that substitutes temperatures of the machine element into the relational expression and calculates an estimated value for the relative position of the upper and lower guides; and a correction amount calculation unit that calculates a correction amount for the upper and lower guides, based on the estimated value for the relative position. Further provided is a correction execution unit that performs correction of the relative position of the upper and lower guides based on this correction amount.

A calculation formula learning unit sets a coefficient relating to a time lag element in a thermal displacement estimation calculation formula by machine learning while fixing a coefficient relating to measured data except the coefficient relating to the time lag element at a predetermined value based on a difference between a thermal displacement estimated value about a machine element calculated by substituting a measured data group into the thermal displacement estimation calculation formula and a thermal displacement actual measured value about the machine element; sets the coefficient relating to the measured data except the coefficient relating to the time lag element in the thermal displacement estimation calculation formula by machine learning based on the difference while fixing the coefficient relating to the time lag element at a predetermined value; and repeats the machine learning.

Highly accurate press working is performed while responding to mechanical alteration due to thermal expansion. Prior to a series of processing to a workpiece, a servomotor control unit moves a slide to a stop position, and a sensing value detecting unit detects a sensing value of a sensing element at the stop position of the slide, and stores the detected sensing value. Then, in the series of processing, the sensing value detecting unit detects a sensing value of the sensing element at the stop position of the slide, and stores the detected sensing value in the processing sensing value storing unit. A correction value calculating unit calculates a correction value based on the two store values, and a servomotor control unit controls the servomotor based on the detected slide position, the slide position that has been set, and the correction value calculated by the correction value calculating unit.