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This paper presents an experiment on the modeling, analysis, prediction and optimization of machining parameters used during the turning process of the low-carbon steel known as ST40. The parameters used to develop the model are the cutting speed, the feed rate, and the depth of the cut. The experiments were carried out under various conditions, with three level of parameters and two different treatments for each level (with and without a lubricant), to determine the effects of the parameters on the surface roughness and electric current consumption. These effects were investigated using response surface methodology (RSM). A second-order model is used to predict the values of the surface roughness and the electric current consumption from the results of experiments which collected preliminary data. The results of the experiment and the predictions of the surface roughness and electric current consumption under both treatments were found to be nearly identical. This result shows that the feed rate is the main factor that influences the surface roughness and electric current consumption.

Application of Response Surface Methodology for Modeling and Optimization of Surface Roughness and Electric Current Consumption in Turning Operation