An experimental investigation of machinability properties of the compacted graphite iron in milling and modelling by using artificial neural networks

This experimental research contains the mechanical properties and the milling of Compacted Graphite Iron. The results of the experimental investigation have been modeled with artificial neural networks (ANN) and Regression Analysis Method. As milling parameters various lead angles, cutting speeds and the maximum chip thickness were used. In this study TiCN and Al2O3 coated carbide inserts and silicon nitrate based ceramic inserts were utilized. During the face milling process, the effects of cutting parameters on the surface roughness, milling forces and tool wear were investigated. The following mechanical properties for the material used in the experiments were measured. The hardness of Vickers is 280 HV, the ultimate tensile strength is 508 MPa, the yield strength is 284 MPa, and an impact strength of 8,6 joules. The lowest cutting tool wear for the coated carbide insert (VB = 0,12) was realized with 45° lead angle, 215 m/min cutting speed and 492 mm/min table feed rate. The highest tool wear (VB=0,87 mm) was realized with 88° lead angle, 290 m/min cutting speed and 704 mm/min table feed rate. Between the maximum and the minimum cutting tool wear exists a difference of 725,0%. An increase of the angle value 45°, 60°, 75°, 88° results in a higher decrease of the cutting tool life. The lowest cutting tool wear for the ceramic cutting insert (VB=0,11) was realized with 45° lead angle. The highest cutting tool wear for the ceramic cutting insert (VB=1,1) was realized with 88° lead angle. Between the maximum and minimum cutting tool wear exists a difference of 982,0%. Using cutting oil in the experiments shows a decrease of the cutting forces between 1,0% - 15,33% at the lead angles of 45° and 60°. In comparison to that an increase of the cutting forces between 1,0% and 16,0% occurs at the lead angles of 75° and 88°. When using the coated carbide insert as cutting material for milling, surface roughness values were improved while increasing the lead angle from 45° to 88°. But when using the ceramic inserts as cutting material, the surface roughness values were worsened while increasing the lead angle from 45° to 88 because of micro fractures on the cutting tool. Face milling process has been studied by other researchers with different lead angle before. This is a new and different approach which has been developed through an experimental study for machinability of CGI. This study is considered helpful in predicting the wear mechanism, cutting forces and surface roughness of the coated carbide insert and ceramic inserts in the milling of compacted graphite iron. The present method greatly reduces the cost of time and of machining to find the optimum machining solution.Key Words : Compacted graphite cast iron, mechanical features, machinability, tool life, tool wear, cutting force, surface roughness, predictive modelling, artificial neural network, regression analysis.