Machine tool, simulation apparatus, and machine learning device

• US 10,331,104 B2
• Filed: 07/22/2016
• Issued: 06/25/2019
• Est. Priority Date: 07/30/2015
• Status: Active Grant

• Current Assignee: Fanuc Corporation
• Original Assignee: Fanuc Corporation
• Inventors: Hatanaka, Noriaki
• Primary Examiner(s): Sitiriche, Luis A
• Application Number:
  US15/216,970
• Publication Number:
  US 20170031343A1
• Time in Patent Office: 1,068 Days
• CPC Class Codes: G05B 19/19 characterised by positioning or contouring control systems, e.g. to control position from one programmed point to another or to control movement along a programmed continuous path
• CPC Class Codes: G05B 2219/33034 Online learning, training
• CPC Class Codes: G05B 2219/33037 Learn parameters of network offline, not while controlling system
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

A machine tool is provided with an operation evaluation section that outputs evaluation data on an operation of the machine tool and a machine learning device that performs machine learning of the movement amount of an axis. The machine learning device calculates a reward from physical-amount data on the machine tool and the evaluation data, performs adjustment of the movement amount of the axis based on a machine learning result of the adjustment of the movement amount of the axis and the physical-amount data, and performs the machine learning of the adjustment of the movement amount of the axis based on the adjusted movement amount of the axis, the physical-amount data after the operation of the machine tool based on the movement amount of the axis, and the reward.

Claims

1. A machine tool, comprising:

an axis;

a numerical controller configured to drive the axis based on a program to perform machining of a workpiece, the numerical controller configured to output evaluation data to evaluate an operation of the machine tool; and

a machine learning device that includes a processor programmed to

perform machine learning of an adjustment of a movement amount of the axis for each control cycle,

acquire physical-amount data including at least an axis position of the axis of the machine tool and the evaluation data,

calculate a reward based on the acquired physical-amount data and the acquired evaluation data,

adjust the movement amount of the axis for each control cycle based on a result of the machine learning of the adjustment of the movement amount of the axis for each control cycle and the acquired physical-amount data, and

output the adjusted movement amount of the axis for each control cycle,

wherein the processor is programmed to perform the machine learning of the adjustment of the movement amount of the axis for each control cycle based on the adjusted movement amount of the axis for each control cycle, the acquired physical-amount data after the operation of the machine tool based on the output movement amount of the axis for each control cycle, and the calculated reward, and

the numerical controller drives the axis of the machine tool to perform machining of the workpiece based on the adjusted movement amount having been completed the machine learning.

2. The machine tool according to claim 1, wherein

the processor is further programmed to calculate a positive reward when a combined speed of the axis is fast and configured to calculate a negative reward when there is a deviation from a range of a command path commanded by the program.

3. The machine tool according to claim 1, wherein

the machine tool is connected to at least one another machine tool and configured to mutually exchange or share the result of the machine learning with said at least one another machine tool.

4. The machine tool according to claim 3, wherein

the processor is further programmed to perform, in order to make the reward maximum, the machine learning using the adjusted movement amount of the axis for each control cycle and an evaluation function in which the acquired physical-amount data is expressed by an argument.