Development and analysis of methodologies for accurate identification of a mechanistic cutting force model in milling - application to high-feed milling of Ti-6Al-4V titanium alloy

Accurate prediction of cutting forces is essential for process planning and optimisation in modern machining. Mechanistic modelling is widely used for this purpose, but its accuracy is strongly affected by imprecise evaluation of uncut chip thickness and cutter-workpiece engagement. In addition, the choice of a suitable cutting force model and its identification methodology are non-trivial and directly influence cutting force prediction. This article introduces a general methodology for the modelling of uncut chip thickness in both conventional and high-feed milling. The approach is based on a parametric description of milling cutters combined with an algorithm for the computation of uncut chip thickness. This framework accounts for geometrical effects such as tool run-out, differential pitch and insert geometry, enabling a more reliable description of cutter-workpiece engagement than classical approximations. The methodology is coupled with mechanistic cutting force models and validated experimentally through instrumented high-feed milling tests of Ti-6Al-4V titanium alloy. An inverse identification strategy is developed to determine cutting force model coefficients from measured forces, including a quantitative correction of tool angular shift between simulation and measurement. In addition, the influence of the transition uncut chip thickness on the fractional model is investigated. Finally, the variability of identified coefficients is analysed across tool revolutions and cutting conditions. Sensitivity analysis demonstrates how this variability impacts simulated forces, providing a criterion for assessing the relevance and robustness of cutting force models. The proposed methodology thus offers a systematic framework for accurate force prediction and critical evaluation of mechanistic models in milling.