Abstract
In high-speed micromilling of complex 3D thin-walled structures like microelectrodes, microfins, micro-needles, etc., stiffness of the workpiece will be approximately equal to that of the cutting tool. Also, with every cutting, the stiffness of thin-walled workpiece reduces significantly. Due to the varying stiffness of thin-walled structure coupled with low stiffness of cutting tool, deflection increases while machining, which makes the micromilling process unstable and leads to chatter. Thus, the effect of varying stiffness has to be incorporated while predicting stable process parameters. It is essential to find natural frequency, damping and modal stiffness, which are the necessary modal parameters required for predicting stable depth of cut at different spindle speeds. Experimental modal analysis (EMA) is the most popular technique used to get all the required modal parameters, but it cannot be performed for all possible machining conditions and tool-work geometries as experimental cost and time increases leading to high manufacturing cost of the components. Thus, the present work analyses the feasibility of using numerical method to find the modal parameters for different machining conditions in order to reduce the manufacturing time and cost. Experimentally developed stability lobe diagram incorporates the effect of varying stiffness for prediction of stable process parameters. Experimental validation of simulated modal parameters has been done by performing experimental modal analysis on flexible thin-walled Ti6Al4V. Validation showed an error of 5.1% in predicted natural frequency and the percentage error in predicted modal stiffness was 8.04%. It is expected that stable parameters chosen from the developed stiffness dependent stability lobe can increase the cutting tool life and enhances the material removal rate.
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Gururaja, S., Singh, K.K., Mittal, R.K. (2023). Analysis of Numerical Method for Modal Analysis of Thin-Walled Structures for Achieving Low-Cost Manufacturing. In: Joshi, S.N., Dixit, U.S., Mittal, R.K., Bag, S. (eds) Low Cost Manufacturing Technologies. NERC 2022. Springer, Singapore. https://doi.org/10.1007/978-981-19-8452-5_1
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