Optimizing turning operation of St37 steel using grey relational analysis

Nowadays, in order to reach minimum production cost in machining operations, various optimization methods have been proposed. Since turning operation has different parameters affecting the workpiece quality, it was selected as a complicated manufacturing method in this paper. To reach sufficient quality, all influencing parameters such as cutting speed, federate, depth of cut and tool rake angle were selected as input parameters. Furthermore, both surface roughness and tool life were considered as the objectives. Also, ST37 steel and M1 high speed steel (HSS) were selected as workpiece material and tool, respectively. Subsequently, grey relational analysis was performed to elicit optimal values for the mentioned input data. To achieve this goal, first, degree of freedom was calculated for the system and the same experiments were performed based on the target values and number of considered levels, leading to calculating grey relational generating, grey relational coefficient and grey relational grade. As the next step, the grey relational graph was sketched for each level. Finally, optimum values of the parameters were obtained for better surface roughness and tool life. It was shown that the presented method in the turning operation of ST37 led to high surface quality and tool life.