Multi-objective optimization of multi-pass turning AISI 1064 steel

Manufacturing machine parts of high quality with high productivity and low cost is the most important goal of the production in metalworking industry. For the realization of production goals, single-objective optimization of the machining processes is a good way but multi-objective optimization is the right way. Turning is the most widely used machining process. Turning operation is usually realized through a multi-pass roughing and single-pass finishing. In this paper, multi-objective optimization of turning operation which consists of multi-pass roughing and single-pass finishing AISI 1064 steel with carbide cutting tool, in terms of material removal rate and machining cost, was studied. For multi-pass roughing, optimization problem with two objectives (material removal rate and machining cost), three factors (depth of cut, feed and cutting speed), and five machining constraints (cutting force, torque, cutting power, tool life, and cutting ratio) was studied. For single-pass finishing, optimization problem with two objectives (material removal rate and machining cost), four factors (tool nose radius, depth of cut, feed, and cutting speed), and three machining constraints (surface roughness, tool life, and cutting ratio) was studied. The optimization problem is solved using three techniques: (i) iterative search method, (ii) multi-objective genetic algorithm (MOGA), and (iii) genetic algorithm (GA). With the iterative search method, the values of objectives for all combinations of factor levels were calculated and an optimal solution was selected. With a multi-objective genetic algorithm, a set of optimal solutions named “Pareto optimal set” was defined and an optimal solution was selected. With a genetic algorithm, the optimal solution was determined by using the weighted-sum-type objective function.