Songhua Lia,b, Chuang Lia, Minghe Liua, Yonghua Wanga,*, Chuang Zuoa, Hao Zhanga and Yifeng Gaoa
aSchool of Mechanical Engineering, Shenyang Jianzhu University, Shenyang 110168, China
bNational-Local Joint Engineering Laboratory of NC Machining Equipment and Technology of High-Grade Stone, Shenyang 110168, China
This article is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
In order to improve the machining accuracy of the cylindrical surface of silicon nitride ceramic spindle, the machining technology of the cylindrical surface of ceramic spindle was studied by high-speed universal cylindrical grinder in this experiment. Firstly, the primary and secondary order of the influence of various factors on the surface roughness of ceramic spindle is determined by orthogonal experiment, then the influence law of single grinding parameter on the surface roughness of ceramic spindle is explored by single factor experiment, and the prediction model of the grinding surface roughness value of ceramic spindle is calculated by numerical analysis software, and finally the optimal processing parameters of the cylindrical surface of ceramic spindle are obtained. The experimental results show that the grinding surface roughness of silicon nitride ceramic spindle first decreases and then increases with the increase of grinding wheel linear speed and workpiece linear speed, and then increases with the increase of transverse feed speed and axial feed speed. The relative error between the predicted value of the prediction model and the actual measured value is less than 5%, which shows that the prediction model has a good prediction effect and provides a theoretical basis for actual machining.
Keywords: Silicon nitride ceramic spindle, surface roughness, Roundness and cylindricity, High speed grinding, prediction model.
2023; 24(6): 1025-1036
Published on Dec 31, 2023
School of Mechanical Engineering, Shenyang Jianzhu University, Shenyang 110168, China
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