Kerf modelling in abrasive waterjet milling using evolutionary computation and ANOVA techniques

Abstract

Many researchers demonstrated the capability of Abrasive Waterjet (AWJ) technology for precision milling operations. However, the concurrence of several input parameters along with the stochastic nature of this technology leads to a complex process control, which requires a work focused in process modelling. This research work introduces a model to predict the kerf shape in AWJ slot milling in Aluminium 7075-T651 in terms of four important process parameters: the pressure, the abrasive flow rate, the stand-off distance and the traverse feed rate. A hybrid evolutionary approach was employed for kerf shape modelling. This technique allowed characterizing the profile through two parameters: the maximum cutting depth and the full width at half maximum. On the other hand, based on ANOVA and regression techniques, these two parameters were also modelled as a function of process parameters. Combination of both models resulted in an adequate strategy to predict the kerf shape for different machining conditions. © 2012 American Institute of Physics.