USE OF ARTIFICIAL NEURAL NETWORKS IN BALL BURNISHING PROCESS FOR THE PREDICTION OF SURFACE ROUGHNESS OF AA 7075 ALUMINUM ALLOY

Burnishing is a plastic deformation process, and it has become more popular as a finishing process. Thus, it is especially crucial to select the burnishing parameters to reduce the surface roughness. In the present study, a surface roughness prediction model using artificial neural network (ANN) is developed to investigate the effects of burnishing conditions during machining, of AA 7075 aluminum material. The ANN model of surface roughness parameters (R-a) is developed considering the conditions its burnishing force, number of tool passes, feed rate and burnishing speed. The experimental results were trained in an ANN program and the results were compared with experimental values. It is observed that the experimental results coincided with ANN results.