The Prediction and Optimization of the Effects of Abrasive Waterjet Cutting Parameters On Kerf

In this study, Inconel 718 material, which is widely used in space aircraft and defense industry and is difficult to be processed by traditional methods, has been cut off with abrasive water-jet. The effects of cutting parameters such as pressure, cutting speed, abrasive consumption and cutting height on kerf have been studied. The input levels needed to be used to obtain the minimum kerf have been determined through Taguchi analysis and the experimental test. The setup of experiment was modelled using linear regression model and an artificial neural network and the results were compared. It was seen that the artificial neural network model gives better results when compared to regression model. The results of experimental test to which the related models were applied are satisfactory