Compared to conventional machining tools, robotic milling offers high flexibility and a desirable ratio of workspace to investment costs, making it a promising technology in numerous contemporary industries. Unfortunately, industrial robots and robotic milling suffer two major drawbacks: significantly lower rigidity and undesirable vibration. These limitations are a great obstacle to realizing high-performance and flexible robotic milling as they deteriorate the tool life, productivity and machining quality.
Several strategies have been proposed to help improve robotic milling stability. Most of these approaches rely on either reducing the milling force magnitude using conservative milling parameters or exploring the potential of maximizing robotic stiffness in the milling force direction by optimizing some process parameters and configuration. While these approaches have produced remarkable results, some inherent limitations, like limited flexibility and productivity of the system, still exist. Another approach employs active and semi-active control of chatter to suppress vibrations. Still, they operate in a gain-scheduled manner that is insufficient to guarantee the desired system performance throughout the robot configuration.
To overcome these challenges, it is necessary to empirically pre-tune many sets of gains for different configurations. While implementing such controllers is complex and time-consuming, detailed proof of the stability and flexibility of the system cannot be adequately provided due to the poor understanding of the complex dynamics of active and semi-active chatter control. Recently, several self-tuning algorithms have been developed for active and semi-active dampers. Nevertheless, despite the remarkable attempts to demonstrate the superiority and effectiveness of these algorithms, these algorithms are not specifically designed for robotic milling systems. This warrants further studies to enable the adoption of these algorithms in robotic milling.
On this account, Professor Kai Guo, Dr. Yiran Zhang, Professor Jie Sun from Shandong University proposed an active contact robotic milling approach to improve the system stability without compromising on flexibility and productivity. To achieve this, an active force was exerted on the robotic structure by controlling the contact between the robot and the workpiece. Theoretical analysis was carried out to validate the impact of this approach. Their work is currently published in the International Journal of Machine Tools and Manufacture.
The authors verified the feasibility of the proposed approach in improving the stability of the robotic milling systems without sacrificing productivity and flexibility. The theoretical analysis demonstrated the possibility of effectively improving the system stability without an elaborate optimization of the milling processes and parameters or robotic configuration, ensuring high productivity and flexibility of the robotic milling. Furthermore, the proposed active contact robotic milling principle was adopted to develop a new milling cutter consisting of plain rod, cutting edges and needle bearing. This cutter was capable of controlling the contact force between the workpiece and the robot. The end effectors could withstand the resultant contact and machining farces, whose component was controlled by the robot joint motors.
In summary, the new study demonstrated that besides the milling force, generating additional force between the workpiece and the robotic structure could improve the stability of robotic milling without compromising productivity and flexibility. The proposed new principle also offered a promising solution for stable robotic milling. The dynamic model provides more insights into the influences of contact interface interactions on system stability. The validity of the proposed principle was successfully validated experimentally. In a statement to Advances in Engineering, Professor Kai Guo, the first and corresponding author said that their study would contribute to designing new tools for stable milling with flexible machine tool systems.
Guo, K., Zhang, Y., & Sun, J. (2022). Towards stable milling: Principle and application of active contact robotic milling. International Journal of Machine Tools and Manufacture, 182, 103952.
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