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Analysis of the machining accuracy when dry turning via experiments and finite element simulations

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Abstract

Workpiece and tool are subjected to severe mechanical and thermal loads when turning. These loads cause thermal expansions and mechanically induced deflections of the tool and the workpiece. Such deformations induce deviations from the nominal workpiece geometry. In order to decrease these deviations, the cutting condition needs to be optimized prior to actual machining. In this paper, the accuracy of machining when dry turning aluminum is analyzed via experiments and finite element simulations. For this purpose, seven characteristic values were used: the forces, the deflection of the workpiece, the quantity of heat in the workpiece, the temperature distribution in the workpiece, the temperature of the tool, the temperature of the tool holder, and the actual dimension of the workpiece after turning. These experimentally determined results serve in addition as boundary conditions for a 3D finite element model of the workpiece, which calculates the deformations of the workpiece. The continuous removal of material affecting the temperature distribution in the workpiece is considered. The actual dimensions of the workpiece after turning revealed a remarkable influence of the cutting condition used on the accuracy of machining. Differences of up to 116 μm regarding the deviation from the nominal workpiece diameter of 30 mm were observed. The analysis of the machining accuracy reveals that particularly the use of both high cutting speeds and feeds enhances the accuracy of machining when dry turning aluminum.

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Acknowledgments

The authors would like to thank the German research foundation (DFG) for funding the project “Thermal effects when turning Al-MMC - experiments and simulations AU 185/26, STE 544/42” within the priority program SPP 1480.

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Correspondence to Marco Zimmermann.

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Aurich, J.C., Zimmermann, M., Schindler, S. et al. Analysis of the machining accuracy when dry turning via experiments and finite element simulations. Prod. Eng. Res. Devel. 8, 41–50 (2014). https://doi.org/10.1007/s11740-013-0508-9

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  • DOI: https://doi.org/10.1007/s11740-013-0508-9

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