Pareto optimization of multi-pass turning of grey cast iron with practical constraints using a deterministic approach

Abstract

For a given workpiece material, in addition to the cutting tool material used and its geometry, a set of adopted cutting parameters significantly affect the actual turning process. With the ultimate aim of improving machining efficiency while ensuring the specified part quality and lowest possible energy consumption and costs, the optimization of the turning regimes is of great importance. Therefore, a multi-objective optimization model for the multi-pass turning of grey cast iron was developed in the present research. Part production costs and consumed energy were both considered as conflicting objective functions, while several practical constraints related to the part quality, machine tool limitations, and product specifications in finishing and roughing were also included in the optimization model. The formulation of the objective functions was based on the analytical model for the unit production time whose validation was performed using toolpath simulation in SinuTrain and FeatureCAM software. In order to obtain Pareto compromise solutions in a reasonable computational time as well as to avoid getting stuck in local optima in the optimization hyper-space, a deterministic approach based on the application of the brute force optimization algorithm is proposed to solve the developed multi-objective optimization problem with several constraints of the equality and inequality type. The obtained optimization results were validated experimentally and through a comparison with related analytical and empirical turning optimization studies.