Machinability study and ANN-MOALO-based multi-response optimization during Eco-Friendly machining of EN-GJL-250 cast iron

The current work examines the performance of Minimum Quantity Lubrication when turning of EN-GJL-250 cast iron compared to dry and wet cooling methods. The Taguchi design L₃₆ has been chosen for the planification of experimentation. Then, ANOVA has been established after data acquisition in order to define the effect of cutting conditions such as the used inserts, cutting depth, feed rate and cutting speed on the studied factors. Furthermore, the surface roughness has been deeply studied using 3D roughness topography to evaluate the MQL effect. Finally, the approach ANN-MOALO was found to be helpful for future industrial applications for predicting part quality and power consumption with accurate results and optimizing cutting parameters that helps to achieve the best production control.