Prediction And Optimization Of En8 Mild Steel Material Removal Rate And Surface Roughness Using Response Surface Methodology

Abstract

The demand for EN8 mild steel in the industry is high due to its integral mechanical properties. However, conventional machining of EN8 mild steel is a challenging task. In this research work, prediction and optimization of EN8 mild steel Material Removal Rate (MRR) and Surface Roughness (Ra) using Response Surface Methodology (RSM) was investigated. The dimension of the EN8 mild steel material was 120 mm diameter and 80 mm in length. The turning operation of the ENS mild steel was carried out using a M42 HSS single point cutting tool. To minimize any form of error, the machining operation was done in a dry environment. A TR 100 Surface Roughness Tester was used to carry out the surface roughness measurement of the EN8 mild steel in a transverse direction. This process was repeated three times and the average value of three measurements recorded. The data generated was analyzed using Response Surface Methodology. The results obtained revealed an R² value of 0.9985 and 0.9978 for Material Removal Rate (MRR) and Surface Roughness (Ra) respectively. Besides, it was observed that the feed rate, spindle speed, and depth of cut, had significant influence on material removal rate.  Nevertheless, unlike the other parameters evaluated, it was only feed rate that had significant influence on surface roughness. The results obtained from the numerical optimization solution revealed that optimum machining setting of spindle speed of 220 rpm, feed rate of 0.14 mm/min and a depth of cut of 1.5 mm will result in a turning process with an optimum material removal rate of 12598.5 mm³/min and surface roughness of 0.87785 µm, and with a composite desirability value of 98.9%.