D. Brahmeswara Rao,M.Balaji,P.B.G.S.N.Murthy,K.Venkata Rao,



Surface Roughness,Micro Milling,Tool wear,Taguchi,LDV,Multi Response Optimization,


The present work is aimed to investigate the influence of process parameters namely cutting speed, feed and uncut chip thickness ontool life in micro milling of Ti-6Al-4V alloy. Twenty Seven experiments have been planned as per full factorial design with three levels of each parameter using carbide end mill cutters. Surface roughnessand vibration amplitude are considered as responses to evaluate the tool life and to identify significance of input process parameters. In this study, a non-contact sensor, Laser Doppler Vibrometer (LDV) was used to measure the vibration of tool in terms of AcoustoOptic Emission (AOE) signals. A high-speed Fast Fourier Transform (FFT) analyser was used to transform the acousto optic emission signals in to useful signals like vibration amplitude. In the analysis of surface roughness and amplitude of vibration, optimum cutting parameters were found as 5000 r.p.m. of spindle speed, 40 mm/min of feed rate and 25.6 µm of uncut chip thickness.


I. Bhuvnesh Bhardwaj, Rajesh Kumar, Pradeep K Singh, “Surface roughness predction model for turning of AISI 1019 steel using response surface methodology and Box–Cox transformation”, Proc I Mech E Part B: Journal of Engineering Manufacture,Volume: 228, Issue:2, pp: 223–232, 2014.
II. EmelKuram and Babur Ozcelik, “Effects of tool paths and machining parameters on the performance in micro-milling of Ti-6Al-4V titanium with high-speed spindle attachment”, International Journal of Advanced Manufacturing Technology, Volume: 84. Pp.691–703, 2016.
III. Fabio de Oliveira Campos, Adriane Lopes Mougo and Anna Carla Araujo, “Study of thecutting forces on micromilling of an aluminum alloy”, Journal of Brazilian Society of Mechanical Science and Engineering, Volume: 39, pp:1289–1296, 2017.
IV. Hongqiu Liu, Yongjun He , Xinyong Mao , Bin Li and Xing Liu, “Effects of cutting conditions on excitation and dynamic stiffness in milling”, International Journal of Advanced Manufacturing Technology, Volume: 91, pp.813–822, 2017.
V. James M. Griffin, Fernanda Diaz, Edgar Geerling, Matias Clasing, Vicente Ponce, Chris Taylor, Sam Turner, Ernest A. Michael, F. Patricio Mena and Leonardo Bronfman, “Control of deviations and prediction of surface roughness from micro machining of THz waveguides using acoustic emission signals”, Mechanical Systems and Signal Processing, Volume: 85, pp:1020–1034, 2017.
VI. Rajesh kumar Bhushan, “Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate”, ASME, Journal of Manufacturing Science and Engineering, Volume:135, pp:210-219, 2013.
VII. Rosemar B. da Silva Álisson R. Machado, Emmanuel O. Ezugwu, John Bonney, Wisley F. Sales, “Tool life and wear mechanisms in high speed machining of Ti–6Al–4V alloy with PCD tools under various coolant pressures”, Journal of Materials Processing Technology, Volume: 213, pp: 1459– 1464, 2013.
VIII. Samad NadimiBavilOliaei and YiğitKarpat, “Influence of tool wear on machining forces and tool deflections during micro milling”, International Journal of Advanced Manufacturing Technology,, Volume: 84, pp:1963–1980, 2016.
IX. Subramanian M., Sakthivel M., Sooryaprakash K., Sudhakaran R.,” Optimization of end mill tool geometry parameters for Al7075-T6 machining operations based on vibration amplitude by response surface methodology”, Measurement, Volume:46, pp: 4005–4022, 2013.
X. Wanqun Chen, Xiangyu Teng, DehongHuo and Quanlong Wang, “An improved cutting force model for micro milling considering machining dynamics”, International Journal of Advanced Manufacturing Technology,Volume:93, pp.3005–3016, 2017.
XI. W Rmili, A Ouahabi, R Serra, R Leroy, “An automatic system based on vibratory analysis for cutting tool wear monitoring”, Measurement, Volume: 77, pp: 117-123, 2016.

View Download