Kinematics and improved surface roughness model in milling

  • Dewei Liu
  • , Changhe Li*
  • , Lan Dong
  • , Aiguo Qin
  • , Yanbin Zhang
  • , Min Yang
  • , Teng Gao
  • , Xiaoming Wang
  • , Mingzheng Liu
  • , Xin Cui
  • , Hafiz Muhammad Ali
  • , Shubham Sharma
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

Surface roughness has a significant influence on the mechanical properties and service life of a component. During face milling, surface roughness greatly varies in the tool step direction and can be controlled by using a surface roughness prediction model. However, the issues of accuracy and efficiency of surface roughness prediction models have not been adequately addressed. This study aims to address these research constraints. An improved surface roughness prediction model is proposed, taking into consideration the influences of insert back cutting and stepover ratio. First, the profile-forming mechanism is analyzed based on geometry and kinematics. Subsequently, an improved surface roughness prediction model is established. Thereafter, the influence of feed per tooth, stepover ratio, corner radius, and minor cutting edge angle on surface roughness are analyzed through numerical simulation. Finally, the experiment of face milling aerospace aluminum alloy 7075 is suggested to verify the improved model, and the Z-Map model is introduced for comparison. Results show that the surface roughness is nonlinear with a feed per tooth and stepover ratio, a monotonic variation with corner radius, and a minor cutting edge angle. The predicted values of the improved model and the Z-Map model for the Rsm are equal to the experimental values. However, the improved model reduces the prediction error of Ra from 11.2 to 4.2% in the non-overlapping compared with the Z-Map model and from 62.58 to 13.34% in the overlapping. In addition, the improved model performs better than the Z-Map model in predicting the shape parameters. This work serves as a significant reference for selecting and optimizing the milling parameters to enable machining quality control.

Original languageEnglish
Pages (from-to)2087-2108
Number of pages22
JournalInternational Journal of Advanced Manufacturing Technology
Volume131
Issue number5-6
DOIs
StatePublished - Mar 2024

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022.

Keywords

  • Geometry
  • Kinematics
  • Milling
  • Surface roughness model

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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