Optimization of Cutting Parameters for Cutting Force Minimization in Helical Ball End Milling of Inconel 718 by Using Genetic Algorithm

Abstract

Inconel 718 presents great opportunities in aerospace, space exploration, automobile and chemical industries due to their specific mechanical and thermal properties are superior to conventional materials. Despite their outstanding properties, their use is limited due to the machining difficulties. It is therefore necessary to determine the appropriate machining process window. Ball end milling is a rapidly growing process used for manufacturing of mechanical structural components of Inconel 718. The selection of optimal cutting conditions play an important role in reduction of cutting forces during ball end milling which governs the power consumption, machine stability, product quality and hence productivity. The paper mainly deals with the development of genetic algorithm to obtain optimum cutting conditions for minimization of cutting forces in helical ball end milling of Inconel 718 by using recorded cutting forces and regression model. The experiments were conducted using Taguchi L8 orthogonal array to analyze the effect of machining environment, cutting speed, feed, axial depth of cut and number of passes on cutting force magnitude. The obtained results show that the developed model fits very well with the experimental data. The developed model can be used for the prediction and estimation of cutting forces, optimization of cutting parameters in helical ball end milling of Inconel 718. The integration of the proposed method will lead to ensure machine stability, reduction in power consumption and cost along with flexibility in machining parameter selection.