Qin Jie

Dr. Qin Jie


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 March 2019 in Applied Sciences
Verified
Journal Article
Open access
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QJQin Jie
Qin Jie
YLYuwen Li
Yuwen Li
XXXiong Xiong
Xiong Xiong
Although industrial robots are widely used in production automation, their applications in machining have been limited because of the structural vibrations induced by periodic cutting forces. Since the dynamic characteristics of an industrial robot depends on its configuration, the responses of the robot structure to the cutting forces are affected by how the workpiece is placed within the workspace of the robot. This paper presents a method for workpiece pose optimization for a robotic milling system to improve the quasi-static performance during machining. Since the milling forces are time-varying due to the characteristics of the multi-tooth and discontinuity of milling, these forces can excite vibrations inside the robot structure. To address this issue, a structural dynamics model is established for industrial robots, considering their joint flexibility, and a milling force formulation is incorporated into the robot dynamics model to investigate the forced vibrations of the flexible joints. Then, the quasi-static performance of the robotic machining system is evaluated by the vibration-induced offset of the cutter tool that is mounted on the end-effector. Finally, an optimization approach is given for the workpiece pose to minimize the cutter tool offset under the periodic milling force. A numerical simulation demonstrates that the optimal workpiece pose can significantly reduce the overall tool offset during machining and can lower the variation of the tool offset along the milling path.