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Taguchi-Based Surface Roughness Optimization for Slotted and Tapered Cylindrical Products in Milling and Turning Operations

Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li


The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L9 Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability Cp and the process capability index Cpk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: CNC milling, CNC turning, surface roughness, Taguchi analysis.

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[1] DeGarmo, E. Paul. Materials and Processes in Manufacturing. Wiley, 2003.
[2] Kumar, N. Satheesh, et al. “Effect of Spindle Speed and Feed Rate on Surface Roughness of Carbon Steels in CNC Turning.” Procedia Engineering, vol. 38, 2012, pp. 691–697., doi:10.1016/j.proeng.2012.06.087.
[3] Wang, Yan-Shuang, and Qian-Qian Yuan. “Contact Force Distribution and Static Load-Carrying Capacity of Large Size Double Row Four-Point Contact Ball Bearing.” Defence Technology, vol. 9, no. 4, 2013, pp. 229–236, doi:10.1016/j.dt.2013.12.003.
[4] Jurko, Jozef, et al. “Study on Cone Roller Bearing Surface Roughness Improvement and the Effect of Surface Roughness on Tapered Roller Bearing Service Life.” The International Journal of Advanced Manufacturing Technology, vol. 82, no. 5-8, 2015, pp. 1099–1106., doi:10.1007/s00170-015-7449-8.
[5] He, Zhenzhi, et al. “Analysis of Contact Characteristics of Tapered Roller Bearing with Crowned Rollers.” 2017, doi:10.1063/1.5005263.
[6] G. Taguchi, Introduction to Quality Engineering, Asian Productivity Organization, Tokyo, 1990.
[7] Yang, W.H., and Y.S. Tarng. “Design Optimization of Cutting Parameters for Turning Operations Based on the Taguchi Method.” Journal of Materials Processing Technology, vol. 84, no. 1-3, 1998, pp. 122–129., doi:10.1016/s0924-0136(98)00079-x.
[8] Hasçalık, Ahmet, and Ulaş Çaydaş. “Optimization of Turning Parameters for Surface Roughness and Tool Life Based on the Taguchi Method.” International Journal of Advanced Manufacturing Technology, no. 38, 1 Oct. 2008, pp. 896–903., doi:10.1007/s00170-007-1147-0.
[9] Zhang, Julie Z., et al. “Surface Roughness Optimization in an End-Milling Operation Using the Taguchi Design Method.” Journal of Materials Processing Technology, no. 184, 27 Sept. 2006, pp. 233–239., doi:10.1016/j.jmatprotec.2006.11.029.
[10] J.A. Ghani, I.A. Choudhury, H.H. Hassan, Application of Taguchi method in the optimization of end milling parameters, Journal of Materials Processing Technology 145 (2004) 84–92.
[11] Ab. Rashid, M.F.F., and M.R. Abdul Lani. “Surface Roughness Prediction for CNC Milling Process Using Artificial Neural Network.” Proceedings of the World Congress on Engineering 2010, III, 2 July 2010.
[12] Al-Hazza, Muataz Hazza Faizi, et al. “Surface Roughness Optimization Using Taguchi Method of High Speed End Milling For Hardened Steel D2.” IOP Conference Series: Materials Science and Engineering, vol. 184, 2017, p. 012047. doi:10.1088/1757-899x/184/1/012047.
[13] Agarwal, Nitin. “Surface Roughness Modeling with Machining Parameters (Speed, Feed & Depth of Cut) in CNC Milling.” MIT International Journal of Mechanical Engineering, vol. 2, no. 1, 12 Jan. 2012, pp. 55–61.
[14] Chen, Joseph, and N Hundal. “A Systematic Approach for Identifying Turning Center Capabilities with Vertical Machining Center in Milling Operation.” International Journal of Industrial and Manufacturing Engineering, vol. 8, no. 5, 2014, pp. 892–901.,
[15] D. C. Montgomery, Design and Analysis of Experiments, Wiley, Singapore, 1991.
[16] R. A. Fisher, Statistical Methods for Research Workers, Oliver and Boyd, London, 1925.
[17] Rao, C.R. (1946a) Proc. National Institute of Science, 12, 123 – 135.
[18] Rao, C.R.(1946b) Bull. Calcutta Math. Soc.,38, 67-78.