公开(公告)号：US20200183352A1

公开(公告)日：2020-06-11

申请号：US16692054

申请日：2019-11-22

Applicant: FANUC CORPORATION

Inventor： Yuanming XU

IPC: G05B19/19 ,  G05B13/02

Abstract: A machine tool includes: a spindle that causes a tool to rotate and move; a workpiece rotation mechanism that causes a workpiece W to rotate; a control unit that controls the spindle and the workpiece rotation mechanism in accordance with commands from a program; and a cutting load detection unit that detects a cutting load imparted on the workpiece by the tool, and the control unit controls a cutting route such that a cutting depth of the workpiece cut with the tool in a region with a small cutting load is greater than the cutting depth in a region with a large cutting load within such a range that the cutting load detected by the cutting load detection unit does not exceed a predetermined load.

公开(公告)号：US20200306914A1

公开(公告)日：2020-10-01

申请号：US16788012

申请日：2020-02-11

Applicant: Fanuc Corporation

Inventor： Satoshi IKAI ,  Daisuke UENISHI ,  Yuanming XU

IPC: B23Q17/12 ,  B23Q17/00 ,  B23Q17/10

Abstract: A spindle vibration measuring system which measures vibration of a spindle in a machining device that performs a cutting or abrading process on a workpiece. The machining device has a workpiece holder that holds the workpiece, the spindle that holds a tool, and a moving mechanism that relatively moves the workpiece holder and the spindle. The spindle vibration measuring system acquires positional variation data or vibration data of the moving mechanism when the spindle rotates, and a result related to vibration of the spindle to output or store based on the positional variation data or the vibration data.

公开(公告)号：US20180341244A1

公开(公告)日：2018-11-29

申请号：US15983374

申请日：2018-05-18

Applicant: FANUC CORPORATION

Inventor： Yuanming XU

IPC: G05B19/401 ,  G06N99/00

Abstract: A machine learning device of a controller observes, as state variables that express a current state of an environment, feeding amount data indicating a feeding amount per unit cycle of a tool and vibration amount data indicating a vibration amount of a cutting part of the tool when the cutting part of the tool passes through the workpiece. In addition, the machine learning device acquires determination data indicating a propriety determination result of the vibration amount of the cutting part of the tool when the cutting part of the tool passes through the workpiece. Then, the machine learning device learns the feeding amount per unit cycle of the tool when the cutting part of the tool passes through the workpiece in association with the vibration amount data, using the state variables and the determination data.