Abstract
Abstract Carbon fibre reinforced polymer (CFRP) is characterised by a high potential for lightweight constructions due to its high specific strength and stiffness properties. Especially applications in aerospace industries necessitate numerous drilling operations in CFRP with high tolerance requirement for subsequent riveting. The bore quality in drilling CFRP is the result of complex interactions of various geometry parameters of the drilling tool, the process parameters and the material properties. Due to a strong correlation between the process forces and the resulting bore quality, analytical force models are valuable to optimise tool geometries and process strategies. Furthermore, analytical force models enable single parameter variation, which would be feasible in experiments only with excessive effort and costs. This research aims to develop an analytical force model for drilling out predrilled UD CFRP material. Based on detailed chip formation analysis by means of high-speed recordings and scanning electron microscopy (SEM), four intervals with similar chip formation mechanisms and two fundamental failure mechanisms are identified. In the modelling approach, a coordinated structural failure of entire fibre regions by axial compression is considered by micro-buckling. For fibre loading situations dominated by lateral bending deformations, fibre failure by exceeding tensile strength in the contact region is considered. Therefore, the tool-fibre contact situation is simplified as the Hertzian contact between two cylinders. In addition to force components due to an initial fibre separation in front of the cutting edge, additional force components due to elastic spring back effects of the CFRP material on the flank face are taken into account. Combined with the drilling kinematics and under consideration of oblique cutting conditions, the thrust force and the torque values are analytically determined for the entire range of fibre cutting angles during one half tool rotation. Subsequent validation shows a good agreement of simulated and experimental data.
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