Research on optimization method of process parameters for SiC components robotic bonnet polishing

Abstract

Silicon carbide (SiC) materials are widely used in the fields of advanced optics, such as SiC mirrors. To improve the polishing efficiency and surface quality of SiC components, reduce the cost of polishing equipment and shorten the production cycle, a robotic bonnet polishing (RBP) technology based on industrial robots was proposed. To obtain the global optimal parameters, a regression orthogonal experiment was designed by using the response surface methodology (RSM). The material removal model capturing the main process parameters was established successfully. The predicted optimal process parameters were verified by experiments. Under the optimal process parameters, the predicted material removal rate (MRR) is 0.0543 mm³/min , with an error of 9.8%. The relationship between main process parameters and surface roughness (RMS) was established by the support vector machine (SVM), and the predicted optimal value is 8.58 nm, with an error of 10.26%. Thus, the precise and controllable polishing of SiC components can be realized by RBP technology.

Keywords

silicon carbide components industrial robot bonnet polishing response surface methodology support vector machine

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