Machined Surface Roughness Geometry Model Development on Ultrasonic Vibration Assisted Micromilling with End Mill

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Micro products or micro components are commonly used in today’s world. Research around micromanufacture technologies to produce a better product quality has been going on extensively. Ultrasonic vibration assisted micromilling (UVAM) is one of the technologies that can give a better machining qualities over the conventional ones. One of the benefits UVAM can give is reducing the machined surface roughness. The purpose of this paper is to give an idea how vibration assisted micromilling can give a better surface roughness quality. The theoritical surface roughness geometry model is made using MATLAB software. The cutting tool used in the simulation is end mill. There is a feature of the cutting tool called bottom cutting edge angle. This feature will be considered on this paper. The effects of the bottom cutting edge on workpiece machined surface can be looked visually from the simulation. Thus, the effects of cutting process using UVAM on the workpiece surface can be looked as well through the simulation.

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122-127

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June 2020

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© 2020 Trans Tech Publications Ltd. All Rights Reserved

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[1] Kumar, M. N., Subbu, S. K., Krishna, P. V., & Venugopal, A. (2014). Vibration Assisted Conventional and Advanced Machining: A Review. Procedia Engineering, 97, 1577–1586.

DOI: 10.1016/j.proeng.2014.12.441

Google Scholar

[2] Xu, L., Na, H., & Han, G. (2018). Machinablity improvement with ultrasonic vibration–assisted micro-milling. Advances in Mechanical Engineering, 10(12), 168781401881253.

DOI: 10.1177/1687814018812531

Google Scholar

[3] El-Taybany, Y., M. Hossam, and H. El-Hofy, Experimental Investigation of Ultrasonic-Assisted Milling of Soda Glass Using Factorial Design of Experiments. Procedia CIRP, 2017.58(Supplement C): pp.381-386 DOI: https://doi.org/10.1016/j.procir.2017.03.238.

DOI: 10.1016/j.procir.2017.03.238

Google Scholar

[4] Kurniawan, R., Kumaran, S. T., Ali, S., Nurcahyaningsih, D. A., Kiswanto, G., & Ko, T. J. (2018). Experimental and analytical study of ultrasonic elliptical vibration cutting on AISI 1045 for sustainable machining of round-shaped microgroove pattern. The International Journal of Advanced Manufacturing Technology, 98(5-8), 2031–2055.

DOI: 10.1007/s00170-018-2359-1

Google Scholar

[5] Ding, H., Chen, S.-J., & Cheng, K. (2010). Dynamic surface generation modeling of two dimensional vibration-assisted micro-end-milling. The International Journal of Advanced Manufacturing Technology, 53(9-12), 1075–1079.

DOI: 10.1007/s00170-010-2903-0

Google Scholar

[6] I Rasidi, I., Rafai, N. H., Rahim, E. A., Kamaruddin, S. A., Ding, H., & Cheng, K. (2015). An investigation of cutting mechanics in 2 dimensional ultrasonic vibration assisted milling toward chip thickness and chip formation. IOP Conference Series: Materials Science and Engineering, 100, 012057.

DOI: 10.1088/1757-899x/100/1/012057

Google Scholar

[7] Shahriar Kouravand & Behnam Moetakef Imani (2014) Developing A Surface Roughness Model for End-Milling of Micro-Channel, Machining Science and Technology: An International Journal, 18:2, 299-321,.

DOI: 10.1080/10910344.2014.897846

Google Scholar

[8] Malekian, M., Mostofa, M. G., Park, S. S., & Jun, M. B. G. (2012). Modeling of minimum uncut chip thickness in micro machining of aluminum. Journal of Materials Processing Technology, 212(3), 553–559.

DOI: 10.1016/j.jmatprotec.2011.05.022

Google Scholar

[9] De Oliveira, F. B., Rodrigues, A. R., Coelho, R. T., & de Souza, A. F. (2015). Size effect and minimum chip thickness in micromilling. International Journal of Machine Tools and Manufacture, 89, 39–54.

DOI: 10.1016/j.ijmachtools.2014.11.001

Google Scholar

[10] Biermann, D., & Kahnis, P. (2009). Analysis and simulation of size effects in micromilling. Production Engineering, 4(1), 25–34.

DOI: 10.1007/s11740-009-0201-1

Google Scholar