Effect of ZnO nano materials on grinding surface finishing

Surface roughness is a variable often used to describe the quality of ground surfaces as well as to evaluate the competitiveness of the overall grinding system. The subject of this paper is a grinding process performed on P20 tool steel by changing the grinding conditions, including the depth of cut, the grinding passes, the type of wheel, and the cutting fluid supply in the experiment. The main objective was to investigate the effect of ZnO nanofluid on the grinding surface finishing and wheel wear. The machined surface of selected specimens underwent SEM to assess the surface integrity. An artificial neural network was used to predict the surface roughness and recognize the trend of the surface roughness. The result showed the reduction of 47 % surface roughness value in grinding with ZnO nanofluid. The neural network made accurate predictions and could recognize the roughness trend.