International Science Index


10008824

Optimization of Surface Roughness in Turning Process Utilizing Live Tooling via Taguchi Methodology

Abstract:

The objective of this research is to optimize the process of cutting cylindrical workpieces utilizing live tooling on a HAAS ST-20 lathe. Surface roughness (Ra) has been investigated as the indicator of quality characteristics for machining process. Aluminum alloy was used to conduct experiments due to its wide range usages in engineering structures and components where light weight or corrosion resistance is required. In this study, Taguchi methodology is utilized to determine the effects that each of the parameters has on surface roughness (Ra). A total of 18 experiments of each process were designed according to Taguchi’s L9 orthogonal array (OA) with four control factors at three levels of each and signal-to-noise ratios (S/N) were computed with Smaller the better equation for minimizing the system. The optimal parameters identified for the surface roughness of the turning operation utilizing live tooling were a feed rate of 3 inches/min(A3); a spindle speed of 1300 rpm(B3); a 2-flute titanium nitrite coated 3/8” endmill (C1); and a depth of cut of 0.025 inches (D2). The mean surface roughness of the confirmation runs in turning operation was 8.22 micro inches. The final results demonstrate that Taguchi methodology is a sufficient way of process improvement in turning process on surface roughness.

References:
[1] Kirby, E. Daniel, Zhe Zhang, and Joseph C. Chen. "Development of an accelerometer-based surface roughness prediction system in turning operations using multiple regression techniques." Journal of Industrial Technology 20.4 (2004): 1-8.
[2] Productivity Inc. Live Tool for Lathe Training Manual. Sept. 2014.
[3] Phadke, Madhan Shridhar. Quality engineering using robust design. Prentice Hall PTR, 1995.
[4] Cesarone, J. (2001). The Power of Taguchi: You've Heard of Design of Experiments and Taguchi Methods; Now Understand When It's Appropriate to Use Each Method. IIE Solutions, 33(11), 36-40.
[5] Wysk, R. A., et al. "Manufacturing processes: integrated product and process design." (2000).
[6] Abhang, L. B., and M. Hameedullah. "Determination of optimum parameters for multi-performance characteristics in turning by using grey relational analysis." The International Journal of Advanced Manufacturing Technology 63.1-4 (2012): 13-24.
[7] Zhang, Julie Z., Joseph C. Chen, and E. Daniel Kirby. "Surface roughness optimization in an end-milling operation using the Taguchi design method." Journal of materials processing technology 184.1-3 (2007): 233-239.
[8] Sahoo, P. "Optimization Of Turning Parameters For Surface Roughness Using RSM and GA." Advances in Production Engineering & Management 6.3 (2011).
[9] Shokrani, Alborz, Vimal Dhokia, and Stephen T. Newman. "Investigation of the effects of cryogenic machining on surface integrity in CNC end milling of Ti–6Al–4V titanium alloy." Journal of Manufacturing Processes 21 (2016): 172-179.