Multi-objective Optimization Study in Face Milling of Steel

High productivity of parts manufacturing in industrial practice is closely related, not only to time efficiency, but also to the production of parts with high surface quality and considerable lifespan. Face milling is widely used for the efficient creation of accurately flat surfaces, for a large variety of part sizes and materials. However, determining the process parameters, which can lead to the achievement of all required conditions can be considered as a multi-objective problem. This problem can be sufficiently solved using suitable optimization techniques. In the present work, it is attempted to determine the optimum parameters for face milling of steel parts, in order to achieve minimum cutting forces and surface roughness, as well as maximum possible material removal rate. For that reason, after regression models are derived to correlate process parameters with cutting forces and surface roughness, an optimization process is carried out with two different optimization methods, namely Genetic Algorithm and Fireworks Algorithm and after the determination of the optimum process parameters, results concerning the efficiency of optimization algorithms are discussed as well.