Prediction model of the surface roughness of micro-milling single crystal copper
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Presently, the demand for single crystal copper micro-components is increasing in various fields because single crystal copper has good electrical conductivity. Micro-milling technology is an effective processing technology for small single crystal copper parts. Surface roughness is a key performance indicator for micro-milling single crystal copper. Establishing a surface roughness prediction model with high precision is useful to guarantee the processing quality by selecting the cutting parameters for micro-milling. Few studies have currently focused on micro-milling single crystal copper. In this study, the orthogonal experiments of micro-milling single crystal copper were conducted, and the influences of the spindle and feed speeds and axial depth of cut on the surface roughness of micro-milled single crystal copper with different orientations were analyzed by range analyses. The spindle rotation speed was the major affecting factor. The surface roughness of single crystal copper in different crystal orientations was predicted by using the SVM method. Experimental results showed that the average relative error of the surface roughness of <100>, <110>, and <111> crystal orientation single crystal copper was 2.7 %, 3.3 %, and 2.2 %, respectively, and that the maximum relative errors were 7.0 %. 10.1 %, and 3.1 %, respectively. The uncertainty analysis was conducted by using the Monte Carlo method to verify the reliability of the built surface roughness model.
KeywordsMicro-milling Prediction model Single crystal copper Surface roughness
Depth of cut
Feed per tooth
Gamma, a parameter in RBF
Radial basis kernel function
Support vector machine
Support vector machine regression
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The study is supported by the National Natural Science Foundation of China under Grant No. 51875080 and Liaoning Natural Science Foundation Project under Grant No. 2019- MS-038. The financial contributions are gratefully acknowledged.
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