Comparative assessment between DFA, NSGA-II coupled with TOPSIS, GRA, and TOPSIS for multiobjective optimization of gray cast iron turning process using CBN insert

This work deals with the optimization of the machining process of EN-GJL-250 gray cast iron with a CBN/Tin-coated insert. The multiobjective optimization was performed by four methods, in order to find the optimal cutting conditions (cutting speed (Vc), feed rate (f), and depth of cut (ap)) that would satisfy the goals of improving surface quality, minimizing power consumption, and maximizing productivity simultaneously. The aim is to evaluate the performance of different techniques, namely desirability function approach, Grey relational analysis, technique of order preference similarity to the ideal solution (TOPSIS), and nondominated sorting genetic algorithm coupled with TOPSIS. The outcomes revealed that the methods propose different solutions, where significant divergences were mainly observed in power consumption and material removal rate objectives. This raises the issue of selecting the most appropriate optimization method for industrial needs and confirms the need for further efforts in this field, i.e. optimization of the machining process.