Analysis and simulation of process damping in HPC milling

Wöste, F.1, a; Baumann, J.1, b; Wiederkehr, P.2, c; Surmann, T.3

Institute of Machining Technology, TU Dortmund University, Baroper Str. 303, D-44227 Dortmund, Germany
Chair 14 for Software Engineering – Virtual Machining, TU Dortmund University, Otto-Hahn-Straße 12, D-44227 Dortmund, Germany
Premium AEROTEC GmbH, Riesweg 151-155, 26316 Varel, Germany

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The use of tools with chamfered cutting edges is an essential part of high performance cutting (HPC) as a rough milling process strategy for manufacturing structural components in the aerospace industry. Due to an interaction between the chamfer and the undulated workpiece surface, tool vibrations can be damped allowing high depths of cut without the occurrence of harmful dynamic effects. Hence, a significant increase in efficiency is possible. As a result of process damping, the stability boundary predicted by linear stability analysis provided for instance by analytical or geometric physically-based simulations will generally underestimate the experimentally determined one. Consequently, the object of this procedure, namely to reduce the number of test runs until sufficient process parameter values are determined, could not be met. Therefore, the damping effect induced by chamfered tools was analyzed in this paper. It is shown that the use of chamfered cutting edges leads to a significant limitation of chatter amplitudes when exceeding the stability limit. The strength of this effect depends on the cutting speed and the engagement situation, which influence the intensity and number of interactions between the chamfer and the workpiece surface and, thus, the resulting process damping. Moreover, a dynamic process damping model presented in the literature was chosen and implemented in a geometric physically-based milling simulation. An evaluation of its validity points out the challenges regarding the simulation of process damping.


HPC milling, Process damping, Chamfered cutting edge, Stability prediction, Milling simulation


Production Engineering, (2019), doi: /10.1007/s11740-019-00912-4