A machine learning device includes an input data acquisition unit which acquires input data containing a machining condition for any wire-cut electrical discharge machining applied to any workpiece by any wire-cut electrical discharge machining machine and consumables information including the degree of degradation of at least one of an electrode wire, ion exchange resin, a power supply die, and an electrode wire guide roller before wire-cut electrical discharge machining. The device also includes a label acquisition unit which acquires label data indicating the degree of degradation of at least one of the electrode wire, the ion exchange resin, the power supply die, and the electrode wire guide roller after the wire-cut electrical discharge machining under the machining condition contained in the input data, and a learning unit which uses the input data and the label data to execute supervised learning, thereby generating a learned model.

A machine learning device includes an input data acquisition unit which acquires input data containing a machining condition for any wire-cut electrical discharge machining applied to any workpiece by any wire-cut electrical discharge machining machine and consumables information including the degree of degradation of at least one of an electrode wire, ion exchange resin, a power supply die, and an electrode wire guide roller before wire-cut electrical discharge machining. The device also includes a label acquisition unit which acquires label data indicating the degree of degradation of at least one of the electrode wire, the ion exchange resin, the power supply die, and the electrode wire guide roller after the wire-cut electrical discharge machining under the machining condition contained in the input data, and a learning unit which uses the input data and the label data to execute supervised learning, thereby generating a learned model.

A wire disconnection prediction device includes: a data acquisition part configured to acquire data relating to machining of a workpiece in a state where a wire is not disconnected during machining of the workpiece by a wire electric discharge machine; a preprocessing part configured to create, machining condition data of a condition relating to a machining condition commanded in machining of the workpiece, machining member data relating to a member used in the machining, and machining state data during machining of the workpiece, as state data indicating a state of the machining; and a learning part configured to generate, based on the state data created by the preprocessing part, a learning model indicating correlation between the state data and the state where the wire of the wire electric discharge machine is not disconnected.

A wire disconnection prediction device includes: a data acquisition part configured to acquire data relating to machining of a workpiece in a state where a wire is not disconnected during machining of the workpiece by a wire electric discharge machine; a preprocessing part configured to create, machining condition data of a condition relating to a machining condition commanded in machining of the workpiece, machining member data relating to a member used in the machining, and machining state data during machining of the workpiece, as state data indicating a state of the machining; and a learning part configured to generate, based on the state data created by the preprocessing part, a learning model indicating correlation between the state data and the state where the wire of the wire electric discharge machine is not disconnected.

A thermal displacement compensator measures a temperature of an environment in which a machine is installed and a temperature of each part of the machine, and calculates a temperature difference between at least two temperatures among measured temperatures. Furthermore, the thermal displacement amount of the machine is acquired. Then, based on teacher data using the measured temperatures and the calculated temperature difference as input data and using the acquired thermal displacement amount as output data, a thermal displacement compensation model that estimates the output data from the input data is created by machine learning.

A thermal displacement compensator measures a temperature of an environment in which a machine is installed and a temperature of each part of the machine, and calculates a temperature difference between at least two temperatures among measured temperatures. Furthermore, the thermal displacement amount of the machine is acquired. Then, based on teacher data using the measured temperatures and the calculated temperature difference as input data and using the acquired thermal displacement amount as output data, a thermal displacement compensation model that estimates the output data from the input data is created by machine learning.

A solar cell assembly is presented. The solar cell assembly includes one or more solar cell units coupled in series. The solar cell unit includes a first solar cell series and a second solar cell series connected in parallel. The first and second solar cell series include a plurality of solar cells connecting in series respectively. The solar cell assembly also includes a bypass diode coupled to each solar cell unit and shared between the first and second solar cell series in each solar cell unit.

A solar cell assembly is presented. The solar cell assembly includes one or more solar cell units coupled in series. The solar cell unit includes a first solar cell series and a second solar cell series connected in parallel. The first and second solar cell series include a plurality of solar cells connecting in series respectively. The solar cell assembly also includes a bypass diode coupled to each solar cell unit and shared between the first and second solar cell series in each solar cell unit.

Provided are an estimation method. and a control device for a wire electrical discharge machine, the method and device being for estimating the tension of a wire electrode on the basis of information obtained from a motor included in a feed mechanism of the wire electrode. A control device for a wire electrical discharge machine provided with a first motor and a second motor that induce rotation of a first roller and a second roller for feeding a wire electrode, the control device including: an acquisition unit that acquires a noise load and/or a torque command from one of the first motor and the second motor; a feed motor control unit that controls the first motor and the second motor so that the wire electrode is tensioned; and an estimation unit that estimates the tension on the basis of the noise load and/or the torque command for the time when the wire electrode is tensioned.

A method for preprocessing data related to a tool electrode, which is applied in an EDM machine to manufacture a part comprises: generating an electrode model for the tool electrode based on the geometry of the part; generating the cavity shape model (volume of the part to erode), combining the electrode and cavity shape model, dividing the resulting model into a plurality of slices in a plurality of parallel planes, wherein at least one slice is composed of at least two sections, which are topologically disconnected; and generating for each slice a slice-geometry data, and generating an electrode-geometry data including the slice-geometry data.