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Experimental investigation of the application of parameter inversion for residual stress adjustment in five-axis milling using an annular cutter

  • Kun HuangEmail author
  • Wenyu YangEmail author
  • Yi Gao
  • Xiaoming Ye
ORIGINAL ARTICLE
  • 45 Downloads

Abstract

Five-axis milling makes it possible to control the relative pose between a tool and surface normal of a workpiece, and is widely used in manufacturing. In this study, an experimental investigation of the application of parameter inversion for residual stress adjustment in five-axis milling has been conducted based on two methods: an orthogonal experiment with interaction of factors and a random setting of the expected residual stress. The results of the orthogonal experiment with interactions of factors show that the significance of the influence of the machining parameters on the residual stress obtained with parameter inversion is similar to the experimental results. The results of the experiment with a random setting of the expected residual stress show that the average of the difference between the measured and expected results for the 30 cutting conditions is only 0.3951 MPa, which indicates that residual stress prediction using parameter inversion is statistically effective. Moreover, the results show that using parameter inversion, the correctness of the prediction of compressive and tensile residual stress is 73.33%, which is higher than the 50% value that is achievable without any adjustment. Overall, the results of the experimental investigation in this paper show that residual stress adjustment based on parameter inversion is applicable for five-axis milling, which shows the potential of this adjustment method for industrial applications.

Keywords

Machining Orthogonal experiment with interaction of factors Residual stress Parameter inversion 

Notes

Acknowledgments

This work is supported by the Major State Basic Research Development Program of China (973 Program, Grant No. 2014CB046704). Special thanks to the Advanced Manufacturing and Technology Experiment Center (in the School of Mechanical Science and Engineering, Huazhong University of Science and Technology) and the Analysis and Testing Center of Huazhong University of Science and Technology for their help.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Guangdong Bright Dream Robotics CO. LTD.FoshanChina
  2. 2.State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhanChina
  3. 3.School of Energy and Power EngineeringHuazhong University of Science and TechnologyWuhanChina

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