US 2023/0065699 A1Published application

Machine learning device, prediction device, and control device

AssigneeFanuc Corporation

InventorShinichi OZEKI

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Abstract

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.

Claims8

Dependent claims

A machine learning device, comprising:

an input data obtaining unit configured to obtain input data that includes a machining condition for arbitrary wire-cut electrical discharge machining with respect to arbitrary workpiece by arbitrary wire-cut electrical discharge machine and consumables information including a degree of deterioration before wire-cut electrical discharge machining in accordance with the machining condition for at least one selected from an electrode line, an ion exchange resin, a power supply die, and an electrode line guide roller;
a label obtaining unit configured to obtain label data indicating a degree of deterioration after wire-cut electrical discharge machining in accordance with the machining condition included in the input data for the at least one selected from the electrode line, the ion exchange resin, the power supply die, and the electrode line guide roller;
and
a learning unit configured to use the input data obtained by the input data obtaining unit and the label data obtained by the label obtaining unit to execute supervised learning and generate a trained model.

1 more element

Dependencies are inferred from the claim text.