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Modelling the vibration-assisted drilling process: identification of influential phenomena

Abstract : The increasing part of composite materials in aeronautic multi-material structures highlights the need to develop adapted new manufacturing processes for assembly. Among the new drilling techniques, the vibration-assisted drilling (VAD) allows to improve reliability of drilling operations on multi-layer materials. Forced vibrations are added to conventional motions to create a discontinuous cutting. The back and forth movement allows to improve the evacuation of chips by breaking it. This technology introduces two new operating parameters, the frequency and the amplitude of the oscillation. To optimize the process, the choice of parameters requires first to model precisely the operation cutting and dynamics. Many works have highlighted the parameters range to obtain fragmented chip. The accuracy of current model is not sufficient to get the optimal parameters. The goal of this work is to identify the most influential phenomena generating error between model and test. In this paper, a kinematic modelling of the process is firstly proposed. The limits of the modelling are analysed through comparison between measured and simulated down-hole surfaces. From experimental test results, the model is then completed in order to take into account dynamic phenomena that may explain behaviour differences between tests and simulations. The proposed model of cutting forces considering the dynamical behaviour of the machining system allows foreseeing the operating conditions which ensure good chips breaking. This work also presents the experimental method and the test results to validate the numerical simulator.
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Contributor : Olivier Cahuc <>
Submitted on : Monday, February 18, 2019 - 8:29:19 AM
Last modification on : Wednesday, March 3, 2021 - 3:33:46 AM


  • HAL Id : hal-02022515, version 1


Mathieu Ladonne, Mehdi Cherif, Yann Landon, Jean-Yves K’nevez, Olivier Cahuc, et al.. Modelling the vibration-assisted drilling process: identification of influential phenomena. International Journal of Advanced Manufacturing Technology, Springer Verlag, 2015, 81 (9-12), pp.1657-1666. ⟨hal-02022515⟩



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