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A prediction model for the milling of thin-wall parts considering thermal-mechanical coupling and tool wear

journal contribution
posted on 2024-11-02, 13:09 authored by Ge Wu, Guangxian Li, Wencheng Pan, Xu WangXu Wang, Songlin DingSonglin Ding
In thin-wall milling processes, the interactions between cutting loads and the displacement of the thin-wall part lead to varying tool-workpiece engagement boundaries and undesired surface form errors. This unavoidable issue becomes more severe in the machining of titanium alloys due to their poor machinability caused by the low thermal conductivity, high strength and high chemical reactivity. This paper presents a new predictive model to calculate the cutting-induced thermal-mechanical loads and workpiece deflection in milling Ti-6Al-4V thin-wall components. The cutting heat sources and the development of tool flank wear were considered in the modelling process to improve the prediction accuracy. The cutting loads were modelled analytically and calculated using an efficient iterative algorithm, and the deformation of the thin-wall part was simulated through a finite element model. A series of cutting experiments were conducted under various cutting conditions to validate the predicted results. Both the cutting forces and thin-wall displacement were recorded to examine prediction accuracy, and good agreements have been achieved between the measured results and simulated outcomes. The predicted cutting forces in the radial, feed and axial directions are within errors of 14%, 10% and 5%, respectively, concerning the experimental values. Meanwhile, the maximum predicted deformation errors at the initial, middle and end portions of the workpiece are less than 20%.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1007/s00170-020-05346-2
  2. 2.
    ISSN - Is published in 02683768

Journal

The International Journal of Advanced Manufacturing Technology

Volume

107

Start page

4645

End page

4659

Total pages

15

Publisher

Springer

Place published

United Kingdom

Language

English

Copyright

© Springer-Verlag London Ltd., part of Springer Nature 2020

Former Identifier

2006099125

Esploro creation date

2020-06-22