Taguchi design and response surface methodology based analysis of machining parameters in CNC turning under MQL

In manufacturing industry, the effect of cutting fluids has been known on the health, environment and productivity at machining operations such as turning, milling, drilling, etc. Surface roughness is a common indicator of the quality characteristics for machining processes. The machining process is more complex, and therefore, it is very hard to determine the effects of process parameters on surface quality in all turning operations. In this study, design of experiments has been used to study the effect of the main turning parameters such as cooling condition, cutting speed, feed rate and depth of cut on arithmetic average roughness (Ra) and average maximum height of the profile (Rz) when turning of AISI 1050 steel. Experiments have been performed under dry cutting (DC), conventional wet cooling (CC) and MQL. Tests are designed according to Taguchi's L-16 (4(3) x 2(1)) orthogonal array. ANOVA analysis was performed to determine the importance of machining parameters on the Ra and Rz. The results were analyzed using 3D surface graphs, signal-to-noise ratios (S/N) and main effect graphs of means. Optimal operating parameters were determined using the S/N ratio and desirability function analysis. Mathematical models have been created for surface roughness, namely Ra and Rz, through response surface methodology (RSM). The results indicate that the most effective parameters are feed rate on the surface roughness. Cooling conditions are significantly effective on the surface roughness. MQL is a good tool in order to increase of the machined surface quality for cutting operations. (C) 2013 Elsevier Ltd. All rights reserved.