Optimization of Surface Quality and Power Consumption in Machining Hardened AISI 4340 Steel

Abstract

Hard turning has become an attractive method of machining for most manufacturers in the last few years due to its low cost and superior surface quality compared to grinding. In this experimental study, the machinability of hardened steel under dry machining on a CNC lathe is undertaken to optimize the cutting parameters for minimum surface roughness and energy consumption with the cutting speed (320, 450, and 575), tool type (coated and uncoated), and feed rate (0.1, 0.18, and 0.26) as the input parameters. The Taguchi method, based on the L18 orthogonal array, the variance analysis, the signal-to-noise ratios, and the response surface methodology have been used to optimize surface roughness (Ra) and cutting power (Cp). Optimum cutting parameters and levels were determined, and the relationship between cutting parameters and output variables was analyzed with the aid of two-dimensional and three-dimensional graphics. The results show that the most effective parameter on the surface roughness was the tool type (78%), while the most effective parameter on energy consumption was the cutting speed (90%). The combination of low feed rate and high cutting speed is necessary for minimizing the surface roughness. Besides, the impact of two-factor interactions of the feed rate-cutting speed and depth of cut-cutting speed appears to be substantial. The linear regression models were validated using confirmation tests. Finally, regression coefficients were determined as a mathematical model, and it was observed that this estimated model yielded results that were very similar to those achieved via real experiment (correlation values: 97.64% for surface roughness and 98.72% for energy consumption).