Experimental study on optimisation of cutting parameters in abrasive waterjet machine

This work contains experimental analysis of metallic surfaces generated by abrasive waterjet (AWJ) machine for Al 7075 alloy which is often used as structural material in aerospace and automobile industries. Water pressure, traverse speed and stand-off distance are the three factors considered in most of the studies. In this study, thickness of the material is added as another factor and effects of these four parameters on cutting performance (surface roughness and kerf geometry) are investigated. For this purpose, a total of 81 cuts are performed according to three-level full factorial design of experiment method and results are discussed by drawing main effect and interaction effect plots. Empirical models for surface roughness and kerf taper angle are then established for the prediction and optimisation of AWJ performance by using artificial neural network (ANN) and response surface methodology (RSM). Finally, the models are compared to each other on the basis of commonly used statistical parameters.