Corrosionrate prediction model using Box-Cox transformation of friction stir processed Al-Si alloy

Abstract

In the present work ,the impact of friction stir processing (FSP) process parameters such as traverse feed rate, rotational speed and the type of pin profile tool (form and threaded cylindrical pin profiled tool geometry) on the pitting corrosion rate of A356 cast aluminum alloy was statistically investigated .Potentio dynamic polarization testing was conducted to determine the corrosion properties of the base alloy and the FSPed samples. It is found that, the most important parameter impacting pitting corrosion rate is the rotational speed, while the pin profile tool geometry has a second ranking parameter. The traverse feed rate has no statistical significant impact on corrosion rate .In addition to, the form tool pin profile produces a better pitting corrosion resistance of the stir zones compared to the threaded cylindrical pin profiled tool.Regression model was firstly used to develop the corrosion rate of FS processed A356 cast Al alloy .Then ,the plotting of residuals versus fitted values indicated a non-constant variance of this initial model, Box-Cox transformation was used to improve regression prediction model to the data and eliminate these drawbacks.