DEVELOPMENT AND ANALYSIS OF SURFACE ROUGHNESS MODEL IN DRY LONGITUDINAL TURNING OF C45E STEEL

Abstract

Development of predictive models is essential for better understanding and analysis of machining processes. As surface roughness is one of the most important quality characteristics in machining, in this study an empirical model was developed for prediction of arithmetic mean roughness in dry straight turning of C45E steel using a coated carbide insert. The application of classical factorial design considered the effects of three parameters, i.e., feed rate, cutting speed and depth of cut. Upon determination of the main and interaction effects, and their statistical assessment, a quasi-linear mathematical model for prediction of surface roughness was developed. With the application of 3D surface plots, a more detailed analysis of the parameter effects was performed in order to compare the observations with the previously reported results. The obtained results suggest the dominant effect of feed rate and depth of cut, while the effect of cutting speed is the least pronounced. In addition to modeling, a potential application of the developed surface roughness model for formulating a turning optimization problem with constraints was illustrated. The verification experimental trial under the determined optimized turning conditions showed a high level of agreement with model predictions.