Numerical modeling and experimental evaluation of machining parameters for 2-dimensions ultrasonic-assisted micro-milling at low and high-speed machining

Keywords: high-speed machining, low-speed machining, micro-milling, toolpath trajectory, vibration assisted machining (VAM)

Abstract

Vibration assisted machining (VAM) is one of the hybrid machining processes for improving the machined surface quality. VAM performance is mainly influenced by the combination of machining and vibration control parameters, where surface roughness value (Ra) became the benchmarking indicator. It is difficult to determine the optimum parameter combination to produce high precision products, especially for micro-milling, due to the interconnected correlation among parameters. The benefits of high-speed machining with VAM are high material removal rate and shorter machining time than low-speed machining. VAM operation at high-speed machining is still limited due to the high possibility of chatter occurrence. Therefore, this research aims to evaluate the 2D VAM resonant performance at low-speed and high-speed machining, operated at ultrasonic vibration and amplitude below one μm. The mathematical model and experimental evaluate the vibration effect based on machining mode, amplitude, and spindle speed variation. The mathematical modelling and experiment result complement each other, where the mathematical model can characterize the effect of resonant vibration, amplitude, and spindle speed increment on the tool path trajectory. The 2D resonant vibration at the feed direction causes interrupting cutting and transforms the tool path trajectory from linear to wavy. The mathematical model and experiment result show the dominant influence of spindle speed and feed rate on the toolpath trajectory and Ra, where low spindle speed and feed rate result in better machine surface roughness. The low-speed machining with VAM results in Ra value between 0.1–0.155 μm, which is below the high-speed machining result, between 0.2–0.38 μm

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Author Biographies

Wina Libyawati, Universitas Indonesia

Department of Mechanical Engineering

Gandjar Kiswanto, Universitas Indonesia

Department of Mechanical Engineering

Agung Shamsuddin Saragih, Universitas Indonesia

Department of Mechanical Engineering

Tae Jo Ko, Yeungnam University

School of Mechanical Engineering Departement

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Published
2022-05-31
How to Cite
Libyawati, W., Kiswanto, G., Saragih, A. S., & Ko, T. J. (2022). Numerical modeling and experimental evaluation of machining parameters for 2-dimensions ultrasonic-assisted micro-milling at low and high-speed machining. EUREKA: Physics and Engineering, (3), 57-68. https://doi.org/10.21303/2461-4262.2022.002440
Section
Engineering