Application of Grey Based Taguchi Method in Simultaneous Optimization of Surface Roughness and Material Removal Rate in Hard Milling under Nanofluid MQL Condition
Author(s):
Quoc-Manh Nguyen†, The-Vinh Do‡,*
Affiliation(s):
† Hung Yen University of Technology and Education, Hung Yen, Vietnam
‡ Thai Nguyen University of Technology, Thai Nguyen city, Vietnam
Corresponding Author Email: [email protected]
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper presents the simultaneous optimization of cutting conditions in hard milling of JIS SKD 61 alloy steel using Grey based Taguchi method. Experiments were designed and carried out based on the L27 orthogonal array of the Taguchi method. The input parameters selected of the milling condition are cutting speed, feed rate, depth of cut, and nanoparticle concentration. The responses are surface roughness and material removal rate (MRR). The signal-to-noise ratio was calculated for the determination of a grey relation grade. An analysis was conducted to find out the effect of input factor on the grey relation grade by using the ANOVA. As result, the cutting speed is the factor having the strongest impact on multiple performance characteristics, followed by the nanoparticle concentration. Also, the optimal milling condition for the minimum surface roughness and maximum MRR is the condition consisting of cutting speed of 80m/min, feed rate of 0.02 mm/tooth, depth of cut of 0.6mm, and nanoparticle concentration of 4wt%.