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US 12,228,907 B2Granted
Chip processing device for machine tool and chip processing method
AssigneeDmg Mori Co., Ltd.
InventorMasahiro Shimoike
Life of this patent
Estimating the term…
Abstract
Disclosed is a chip processing device for a machine tool, including a cleaning nozzle control unit 30 that controls a cleaning nozzle for spraying a cleaning fluid onto chips scattered during machining so as to guide the chips to a chip collection portion, wherein the cleaning nozzle control unit 30 includes: a position estimation unit 31 that estimates an accumulation position of generated chips by analyzing machining conditions of a workpiece; and a nozzle orientation adjustment unit 34 that adjusts an orientation of the cleaning nozzle toward the accumulation position estimated by the position estimation unit 31.
Claims9
A chip processing device for a machine tool, comprising
- a cleaning nozzle control unit that controls a cleaning nozzle for spraying a cleaning fluid onto chips scattered during machining so as to guide the chips to a chip collection portion,
- wherein the cleaning nozzle control unit includes:
- a position estimation unit that estimates an accumulation position of chips to be generated, before the chips are generated, by analyzing machining conditions of a workpiece that are conditions for machining the workpiece with a tool;
- and
- a nozzle orientation adjustment unit that adjusts an orientation of the cleaning nozzle toward the accumulation position estimated by the position estimation unit;
- wherein the position estimation unit includes a machine learning device from which an accumulation position of the chips is output when a machining parameter included in an NC program used for machining and an in-machine shape that is an internal shape of the machine tool are input to the machine learning device;
- wherein the machine learning device comprises a primary learned device that has been subjected to primary learning in advance, using, as input data, the machining parameter and the in-machine shape, and using, as training data, the accumulation position of the chips calculated based on the scattering trajectory of the chips obtained by the FEM analysis based on the machining parameter and the in-machine shape;
- wherein the machine learning device comprises a secondary learned device obtained by subjecting the primary learned device to secondary learning, using, as training data, an accumulation position of the chips obtained from captured images of an interior of the machine tool before and after machining.
5 more elements
A chip processing method for a machine tool, comprising
- a cleaning nozzle control step of controlling a cleaning nozzle for spraying a cleaning fluid onto chips scattered during machining so as to guide the chips to a chip collection portion,
- wherein the cleaning nozzle control step includes:
- a position estimation step of estimating an accumulation position of chips to be generated, before the chips are generated, by analyzing machining conditions of a workpiece that are conditions for machining the workpiece with a tool, and
- a nozzle orientation adjustment step of adjusting an orientation of the cleaning nozzle toward the accumulation position estimated in the position estimation step;
- wherein the position estimation step is a step of inputting, to a machine learning device, a machining parameter included in an NC program used for machining and an in-machine shape that is an internal shape of the machine tool, and causing the machine learning device to output an accumulation position of the chips;
- wherein the machine learning device comprises a primary learned device that has been subjected to primary learning in advance, using, as input data, the machining parameter and the in-machine shape, and using, as training data, the accumulation position of the chips calculated based on the scattering trajectory of the chips obtained by the FEM analysis based on the machining parameter and the in-machine shape;
- wherein the machine learning device comprises a secondary learned device obtained by subjecting the primary learned device to secondary learning, using, as training data, an accumulation position of the chips obtained from captured images of an interior of the machine tool before and after machining;
- wherein the machine learning device is a secondary learned device obtained by subjecting the primary learned device to secondary learning, using, as training data, an accumulation position of the chips obtained from captured images of an interior of the machine tool before and after machining.
5 more elements
Dependencies are inferred from the claim text.