Surface Roughness Prediction Model in Machining of Carbon Steel by Carbide Coated Cutting Tools

In machining of parts, surface quality is one of the most specified customer requirements. Finish turning allows manufacturers to simplify their process and still achieve the desired surface finish quality. Out of so many parameters, cutting speed, feed rate, depth of cut and tool nose radius are known to have a large impact on surface quality. In order for manufacturers to maximize their gains from utilizing dry turning, an accurate surface roughness model in the turning ofEN24 steel was developed in terms of the above parameters. Four - factors, five - level factorial central composite rotatable design has been used to conduct the experiments and the surface roughness is measured using Profilometer. These models were tested for adequacy using analysis of variance techniques and validated using scatter diagrams and conformity tests. The established equation shows that the feed rate was found to be main influencing factor on the surface roughness. It increased with increasing feed rate and nose radius, but decreased with increasing the cutting speed and depth of cut. The direct effect of parameters on surface roughness is presented in the graphical form and discussed. The predicted surface roughness of the samples was found to He close to that of the experimentally observed ones with 95% confident levels.