ANALYSIS, MODELLING AND OPTIMIZATION OF CHIP COMPRESSION RATIO IN MEDIUM TURNING OF C45E STEEL

Abstract

Given the multiple significance of chip compression ratio (CCR) for machinability assessment, this study focuses on the analysis of CCR in medium longitudinal turning of C45E steel. The standard 23 full factorial design was used to arrange three main cutting parameters, i.e., depth of cut, feed rate and cutting speed, at two levels. Based on experimental data, a quasi-linear CCR prediction model was developed for better understanding of the main and interaction effects of the considered cutting parameters. The obtained results suggest the dominant main effect of depth of cut and the interaction effect of cutting speed and feed rate. In addition to modelling, a Pareto multi-objective optimization problem was formulated and solved using a multi-objective genetic algorithm (MOGA). CCR and material removal rate were set as objective functions, and surface roughness and chip slenderness ratio as functional constraints. The analysis of Pareto sets revealed that the turning parameters of the highest significance are depth of cut and cutting speed. A perfect linear relationship between material removal rate and CCR was also identified.