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Remaining thickness error modeling during thin floor milling

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Abstract In this paper, the remaining thickness error during milling the thin floor of a flexible pocket structure is investigated. Firstly, a prediction model based on vibration theory of thin-walled shells is developed to calculate the remaining thickness error of the thin floor after milling. Thereafter, a simplified experimental setup is built to validate the error prediction model. Milling experiments are conducted based on the built experimental setup. The remaining thickness error of the workpiece is measured after the milling experiments. Finally, the error is simulated based on the prediction model and it is compared with the tested results. The comparison results show that the simulated error agrees well with tested ones, which demonstrates the effectiveness of the remaining thickness error prediction model. From the results, it is found that the remaining thickness error is mainly caused by the floor deformation along the axial direction of the milling cutter that is induced by the axial milling force, and that the error cannot be neglected during thin floor milling since it may be become significant, especially when the axial depth of cut is relatively large. The error prediction model can provide some guidance for compensation of the remaining thickness error during thin floor milling process.
Title: Remaining thickness error modeling during thin floor milling
Description:
Abstract In this paper, the remaining thickness error during milling the thin floor of a flexible pocket structure is investigated.
Firstly, a prediction model based on vibration theory of thin-walled shells is developed to calculate the remaining thickness error of the thin floor after milling.
Thereafter, a simplified experimental setup is built to validate the error prediction model.
Milling experiments are conducted based on the built experimental setup.
The remaining thickness error of the workpiece is measured after the milling experiments.
Finally, the error is simulated based on the prediction model and it is compared with the tested results.
The comparison results show that the simulated error agrees well with tested ones, which demonstrates the effectiveness of the remaining thickness error prediction model.
From the results, it is found that the remaining thickness error is mainly caused by the floor deformation along the axial direction of the milling cutter that is induced by the axial milling force, and that the error cannot be neglected during thin floor milling since it may be become significant, especially when the axial depth of cut is relatively large.
The error prediction model can provide some guidance for compensation of the remaining thickness error during thin floor milling process.

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