Machine learning assisted investigation on properties of TiO2 reinforced aluminium metal matrix composites

The aim of this study is to investigate deeply about the properties of AA7075 aluminum alloy with varying stirring speed, temperature and different weight percentage of Titanium oxide reinforced with aluminum alloy using machine learning. Machine learning give consistent result with quantitative research.Taguchi method was effectively employed to find the optimal values of the input variables for the maximized values of hardness, impact strength and tensile strength. Stirring speed of 600 rpm, temperature of 600 °C and 9 wt% of TiO2 was finally found as the optimal parameters from this investigation. The model is perfectly fit as R square value is 99.5 %. The maximum brinell hardness is attained for the set of parameter (i) temperature 660 °C (ii) stirring speed 600 rpm and (iii) percentage of reinforcement is 6 wt%.