Festo Andre Hardinsi, Oyong Novareza, Achmad As’ad Sonief


In the manufacturing industries, the main problem in process of operating CNC milling machine was chatter effect (self-excited vibration) which increases the quality of the surface roughness. In this study is to determine optimal value of parameters for chatter and surface roughness. The chatter measured using accelerometer MPU-6050 with Arduino by software LabVIEW-2019 based on peaks-FFT value and the surface roughness measured by SJ-301 tester. The research parameters like variable helix angle, spindle speed, feed rate, and depth of cut using stainless steel 304 by Taguchi method. The optimum parameters value obtained are variable helix 35/38 degrees, spindle speed 3000 RPM, feed rate 150 mm/min and depth of cut 0.4 mm. Based on ANOVA value, the variable helix angle and depth of cut are found to be significant for chatter and surface roughness. The depth of cut was high contribution by ANOVA chatter by 93.84% and surface roughness by 91.93%.


chatter, surface roughness, Taguchi method, ANOVA

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G. Karunya, P. Ravikumar, P. Geeta Krishna, and P. Shiva Krishna, “Optimization of the surface roughness by applying the taguchi technique for the turning of AISI 304 austenitic stainless steel,” Int. J. Mech. Eng. Technol., vol. 8, no. 8, pp. 694–701, 2017.

K. Krishnaprasad, C. S. Sumesh, and A. Ramesh, “Numerical modeling and multi objective optimization of face milling of AISI 304 steel,” J. Appl. Comput. Mech., vol. 5, no. 4, pp. 749–762, 2019.

R. Sreenivasulu, “Combination of Machining Parameters to Optimize Surface Roughness and Chip Thickness during End Milling Process on Aluminium 6351-T6 Alloy Using Taguchi Design Method,” Indep. J. Manag. Prod., vol. 7, no. 4, pp. 1212–1226, 2016.

L. Peña-Parás et al., “Optimization of milling parameters of 1018 steel and nanoparticle additive concentration in cutting fluids for enhancing multi-response characteristics,” Wear, vol. 426–427, no. January, pp. 877–886, 2019.

S. S. Panshetty, “Optimization of Process Parameters in Milling Operation by Taguchi ’ s Technique using Regression Analysis,” Int. J. Sci. Technol. Eng., vol. 2, no. 11, pp. 130–136, 2016.

S. S. Bhogal, C. Sindhu, S. S. Dhami, and B. S. Pabla, “Minimization of Surface Roughness and Tool Vibration in CNC Milling Operation,” J. Optim., vol. 2015, pp. 1–13, 2015.

Y. Wang, T. Wang, Z. Yu, Y. Zhang, Y. Wang, and H. Liu, “Chatter prediction for variable pitch and variable helix milling,” Shock Vib., vol. 2015, 2015.

H. M. Majd and M. J. Azizpour, “A study of the effects of machining parameters on the surface roughness in turning operations by back propagation neural network,” no. January 2016, pp. 1586–1589, 2011.

P. Mihirthakorbhai, “Optimization of milling process parameters - A review,” Int. J. Adv. Res. Eng. Appl. Sci., vol. 4, no. 9, pp. 24–37, 2015.

Y. Guo, B. Lin, and W. Wang, “Optimization of variable helix cutter for improving chatter stability,” Int. J. Adv. Manuf. Technol., vol. 104, no. 5–8, pp. 2553–2565, 2019.

J. Mei, M. Luo, J. Guo, H. Li, and D. Zhang, “Analytical Modeling, Design and Performance Evaluation of Chatter-Free Milling Cutter with Alternating Pitch Variations,” IEEE Access, vol. 6, no. c, pp. 32367–32375, 2018.

M. Balaji, B. S. N. Murthy, and N. M. Rao, “Optimization of Cutting Parameters in Drilling of AISI 304 Stainless Steel Using Taguchi and ANOVA,” Procedia Technol., vol. 25, no. Raerest, pp. 1106–1113, 2016.

J. Ren, J. Zhou, and J. Wei, “Optimization of cutter geometric parameters in end milling of titanium alloy using the grey-taguchi method,” Adv. Mech. Eng., vol. 7, no. 2, 2015.

P. S. Sivasakthivel, R. Sudhakaran, and S. Rajeswari, “Optimization of machining parameters to minimize vibration amplitude while machining Al 6063 using gray-based Taguchi method,” Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., vol. 227, no. 12, pp. 1788–1799, 2013.

A. K. M. N. Amin, S. B. Dolah, M. B. Mahmud, and M. A. Lajis, “Effects of workpiece preheating on surface roughness, chatter and tool performance during end milling of hardened steel D2,” J. Mater. Process. Technol., vol. 201, no. 1–3, pp. 466–470, 2008.

K. KRISHNAIAH and P. SHAHABUDEEN, Applied Design of Experiments and Taguchi Methods. 2012.

H. Li, X. Jing, and J. Wang, “Detection and analysis of chatter occurrence in micro-milling process,” Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., vol. 228, no. 11, pp. 1359–1371, 2014.

A. Bouchareb, A. Lagred, and A. Amirat, “Effect of the interaction between depth of cut and height-to-width ratio of a workpiece on vibration amplitude during face milling of C45 steel,” pp. 1221–1227, 2019.

H. Akkuş and H. Yaka, “Experimental and statistical investigation of the effect of cutting parameters on surface roughness, vibration and energy consumption in machining of titanium 6Al-4V ELI (grade 5) alloy,” Meas. J. Int. Meas. Confed., vol. 167, no. June 2020, 2021.

Xiao Jian Zhang, Cai Hua Xiong, Ye Ding, Ming Jun Feng and You Lun Xiong Milling stability analysis with simultaneously considering the structuralmode coupling effect and regenerative effect. Int Journal of Machine Tools & Manufacture 53 127–140, 2012

Niu Jinbo, Ding Y, Zhu L and Ding H. Mechanics and Multi-Regenerative Stability of

Variable Pitch and Variable Helix Milling Tools Considering Runout International Journal

of Machine Tools and Manufacture 123 129-145, 2017.

Achmad As’ad Sonief, Arda Nur Fauzan and Fikrul Akbar Alamsyah. Evaluation of Aluminum Surface Roughness in the Slot End-Mill Process with Variable Helix Angle Evaluation of Aluminum Surface Roughness in the Slot End- Mill Process with Variable Helix Angle. IOP Conf. Serial Materials Science and Engineering, 494, 012045, 2019.

DOI: https://doi.org/10.21776/ub.jemis/2021.09.01.3


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