Berat Barış Buldum

Effect of ball-burnishing parameters on surface roughness and surface hardness of aluminum alloy 6013

Abstract Burnishing, or the chipless finishing process, can be effectively utilized in order to improve the surface roughness and surface hardness of a workpiece. This paper focuses on the effect of ball-burnishing parameters (burnishing speed, burnishing force, burnishing feed and number of passes) on the surface roughness and hardness of aluminum alloy 6013. The Taguchi method was utilized to specify the most influential parameters for surface roughness and surface hardness. In this study, the optimum ball-burnishing parameters for surface roughness were obtained for a single number of passes, a burnishing force of 150 N, a burnishing speed of 200 rpm and a feed rate of 0.1 mm × min−1. By contrast, the optimum ball-burnishing parameters for surface hardness were also obtained for a single number of passes, a burnishing force of 150 N, a burnishing speed of 400 rpm and a feed rate of 0.25 mm × min−1.

ANN surface roughness prediction of AZ91D magnesium alloys in the turning process

Abstract This contribution presents an approach for the modeling and prediction of surface roughness in the turning of AZ91D magnesium alloys using an artificial neural network. The experiments were conducted with CCGT, DCGT and VCGT cutting tools under minimum quantity lubrication and dry machining conditions. AZ91D alloys were machined at different cutting speeds and feed rates, and the depth of cut was kept constant. 15 out of 18 experimental data points were used for the training of the artificial neural network model and the remaining 3 were used for the testing process. The average percentage error was calculated as 0.000815 % and 0.663 % for training and testing, respectively. The model and target results were found to have extremely low error rates.