Machine learning apparatus, control device, laser machine, and machine learning method
AssigneeFanuc Corporation
InventorTakashi Izumi
Life of this patent
Estimating the term…
Abstract
A machine learning apparatus able to obtaining an optimal shift amount of an assist gas. The machine learning apparatus comprises a state-observation section configured to observe machining condition data included in a machining program given to the laser machine, and measurement data of a dimension of dross generated at a cutting spot of the workpiece when the machining program is executed, as a state variable representing a current state of an environment in which the workpiece is cut; and a learning section configured to learn the shift amount in association with cutting quality of the workpiece, using the state variable.
Claims11
A machine learning apparatus configured to learn a shift amount from being coaxial to being non-coaxial when cutting a workpiece by a laser machine configured to emit a laser beam and an assist gas coaxially and non-coaxially, the machine learning apparatus comprising:
- a state-observation section configured to observe machining condition data included in a machining program given to the laser machine, and measurement data of a dimension of dross generated at a cutting spot of the workpiece when the machining program is executed, as a state variable representing a current state of an environment in which the workpiece is cut;
- and
- a learning section configured to learn the shift amount in association with cutting quality of the workpiece, using the state variable.
A machine learning method of learning a shift amount from being coaxial to being non-coaxial when cutting a workpiece by a laser machine configured to emit a laser beam and an assist gas coaxially and non-coaxially, the method comprising:
- observing, by a processor, machining condition data included in a machining program given to the laser machine, and measurement data of a dimension of dross generated at a cutting spot of the workpiece when the machining program is executed, as a state variable representing a current state of an environment in which the workpiece is cut;
- and
- learning, by the processor, the shift amount in association with cutting quality of the workpiece, using the state variable.
Dependencies are inferred from the claim text.