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Research on the prediction model of micro-milling surface roughness of Inconel718 based on SVM

Xiaohong Lu (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Xiaochen Hu (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Hua Wang (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Likun Si (Key Laboratory for Precision and Non-traditional Machining, Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Yongyun Liu (Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, China)
Lusi Gao (School of Materials Science and Engineering, Dalian University of Technology, Dalian, China)

Industrial Lubrication and Tribology

ISSN: 0036-8792

Article publication date: 14 March 2016

642

Abstract

Purpose

The purpose of this paper is to establish a roughness prediction model of micro-milling Inconel718 with high precision.

Design/methodology/approach

A prediction model of micro-milling surface roughness of Inconel718 is established by SVM (support vector machine) in this paper. Three cutting parameters are involved in the model (spindle speed, cutting depth and feed speed). Experiments are carried out to verify the accuracy of the model.

Findings

The results show that the built SVM prediction model has high prediction accuracy and can predict the surface roughness value and variation law of micro-milling Inconel718.

Practical implication

Inconel718 with high strength and high hardness under high temperature is the suitable material for manufacturing micro parts which need a high strength at high temperature. Surface roughness is an important performance indication for micro-milling processing. Establishing a roughness prediction model with high precision is helpful to select the cutting parameters for micro-milling Inconel718.

Originality/value

The built SVM prediction model of micro-milling surface roughness of Inconel718 is verified by experiment for the first time. The test results show that the surface roughness prediction model can be used to predict the surface roughness during micro-milling Inconel718, and to provide a reference for selection of cutting parameters of micro-milling Inconel718.

Keywords

Acknowledgements

The research is supported by the National Natural Science Foundation of China under grant no. 51305061 and the Specialized Research Fund for the Doctoral Program of Higher Education under project number 20120041120034. The financial contributions are gratefully acknowledged.

Citation

Lu, X., Hu, X., Wang, H., Si, L., Liu, Y. and Gao, L. (2016), "Research on the prediction model of micro-milling surface roughness of Inconel718 based on SVM", Industrial Lubrication and Tribology, Vol. 68 No. 2, pp. 206-211. https://doi.org/10.1108/ILT-06-2015-0079

Publisher

:

Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited

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