Fanuc Corporation

Takuya Saitou

Mamoru Kubo

Koichi Murata

Toshinori Matsukawa

A machine learning device included in a tool selecting apparatus includes a state observing unit that observes, as state variables indicative of a current environmental state, data related to machining condition, data related to cutting condition, data related to machining result, and data related to a tool, and a learning unit that, by using the state variables, learns distribution of the data related to the machining condition, the data related to the cutting condition, and the data related to the machining result, with respect to data related to the tool.

Tool selecting apparatus and machine learning device

In a numerical control system including a numerical controller having a tool database and a tool catalog database which can be referred to from the numerical controller, the tool catalog database has tool catalog data including first cutting condition data, and the tool database has tool data including second cutting condition data to be used for machining. After execution of the machining, the numerical controller updates the first cutting condition data to be stored in the tool catalog database based on the second cutting condition data stored in the tool database.

Numerical control system coordinating with tool catalog database

A numerical controller operates a machine tool based on a plurality of parameters and a machining program. A user is allowed to refer to a parameter that has not been set, in other words, a parameter not falling within the range of recommended setting values, among parameters that may influence the shortening of a cycle time of the operation of the machining program on a display screen. For this reason, the user can use the parameter as a reference for reviewing the parameter setting for the purpose of shortening the cycle time or the like.

Numerical controller having parameter setting support function relating to cycle time

A numerical controller which controls a machine tool acquires tool information including a shape of a tool, a machining condition in machining, and information related to a machining result of a workpiece after machining. A machine learning device performs machine learning on tendency of the information related to a machining result with respect to the tool information and the machining condition based on the tool information and the machining condition used as input data and based on the information related to a machining result used as teacher data, so as to construct a learning model. The machine learning device determines whether or not a machining result is good by using the learning model based on the tool information and the machining condition before the machine tool machines a workpiece.

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Yamanashi, Japan

Takuya Saitou