Abstract
In order to solve the problem of poor consistency and low processing efficiency of artificial grinding, this paper establishes a six-axis robot automatic grinding platform. In the first section of the paper, the qualitative relationship between the process parameters and the grinding quality could be learned from the single factor experiment, and the primitive range of the process parameter domain is obtained. On the basis, an orthogonal experiment is carried out, and a quantitative regression empirical model is established. Then the parameter sensitivity function is deduced based on the model. In regards to the grinding quality and stability constraints, the process parameter domain optimization is carried out. Finally, considering the influence of grinding attitude, the optimal attitude angle is found in the range of process parameters. The results show that the blade grinding system and the grinding scheme are effective.
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References
Wu, S., Kazerounian, K., Gan, Z., et al.: Int. J. Adv. Manufact. Technol. 64, 447 (2013). https://doi.org/10.1007/s00170-012-4030-6
Tsai, M.J., Huang, J.F.: Efficient automatic polishing process with a new compliant abrasive tool. Int. J. Adv. Manuf. Technol. 30, 817–827 (2006)
Song, Y., Liang, W., Yang, Y.: A method for grinding removal control of a robot belt grinding system. J. Intell. Manuf. 23(5), 1903–1913 (2012)
Sabourin, M., Paquet, F., Hazel, B., et al.: Robotic approach to improve turbine surface finish. In: International Conference on Applied Robotics for the Power Industry. IEEE Xplore, pp. 1–6 (2010)
Ahn, J.H., Shen, Y.F., Kim, H.Y., et al.: Development of a sensor information integrated expert system for optimizing die polishing. Robot. Comput. Integr. Manuf. 17(4), 269–276 (2001)
Tsai, M.J., Huang, J.F., Kao, W.L.: Robotic polishing of precision molds with uniform material removal control. Int. J. Mach. Tools Manuf. 49(11), 885–895 (2009)
Pessoles, X., Tournier, C.: Automatic polishing process of plastic injection molds on a 5-axis milling center. J. Mater. Process. Technol. 209(7), 3665–3673 (2009)
Brecher, C., Tuecks, R., Zunke, R., et al.: Development of a force controlled orbital polishing head for free form surface finishing. Prod. Eng. 4(2), 269–277 (2010)
Pan, Z., Zhang, H.: Robotic machining from programming to process control: a complete solution by force control. Ind. Robot 35(5), 400–409 (2008)
Qi, J., Zhang, D., Li, S., et al.: Modeling and prediction of surface roughness in belt polishing based on artificial neural network. Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. 0954405416683737 (2017). https://doi.org/10.1177/0954405416683737
Huai, W., Tang, H., Shi, Y., et al.: Int. J. Adv. Manuf. Technol. 90, 699 (2017). https://doi.org/10.1007/s00170-016-9397-3
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Xie, S., Li, S., Chen, B., Qi, J. (2017). Research on Robot Grinding Technology Considering Removal Rate and Roughness. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10463. Springer, Cham. https://doi.org/10.1007/978-3-319-65292-4_8
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DOI: https://doi.org/10.1007/978-3-319-65292-4_8
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