Optimization of cutting parameters using Response Surface Method for minimizing energy consumption and maximizing cutting quality in turning of AISI 6061 T6 aluminum

Abstract Modern production is faced with the challenge of reducing the environmental impacts related to machining processes. Machine tools consume large amounts of energy and, as a consequence, environmental impacts are generated owing to this consumption. Many studies have been carried out in order to minimize cutting power, cutting energy or power consumed by the machine tool. Nevertheless, the response variables mentioned before do not take into account the energy required by all the components inside the machine tool during the cutting operation. This paper presents an experimental study related to the optimization of cutting parameters in roughing turning of AISI 6061 T6 aluminum. Energy consumption and surface roughness were minimized, while the material removal rate of the process was maximized. A set of experimental runs was established using a Central Composite Design, and the Response Surface Method was employed to obtain the regression model for the energy consumed during machining, specific energy, surface roughness and material removal rate. The adequacy of the model was proved by Analysis of Variance analysis. The relationship between cutting parameters and the response variables (energy consumption, surface roughness and material removal rate) was analyzed using contour plots. Moreover, the desirability method was used to define the values of the variables that achieved a minimum quantity of specific energy consumed and minimum surface roughness. Feed rate and depth of cut were the most significant factors for minimizing the total specific energy consumed, and for minimizing the surface roughness, feed rate was the most significant factor. Compared to the traditional objective optimization, the optimal turning parameters determined by the proposed optimization method reduced the energy consumption in 14.41%, and the surface roughness in 360.47%. Consequently, sustainability and quality of the machining process were achieved at the same time.