Taguchi optimization and modelling of stir casting process parameters on the percentage elongation of aluminium, pumice and carbonated coal composite

Author:

Ibrahim Tanimu Kogi,Yawas Danjuma Saleh,Dan-asabe Bashar,Adebisi Adetayo Abdulmumin

Abstract

AbstractAluminium matrix composites, which are a subclass of metal matrix composites, have characteristics including low density, high stiffness and strength, better wear resistance, controlled thermal expansion, greater fatigue resistance, and improved stability at high temperatures. The scientific and industrial communities are interested in these composites because they may be used to manufacture a broad variety of components for cutting-edge applications. This has study observed how the stirring speed, processing temperature, and stirring duration of the stir casting process affected the percentage elongation of Al-Pumice (PP)-Carbonized Coal Particles (CCP) hybrid composites. It also looked at the optimal weight of these natural ceramic reinforcements using the Taguchi optimization technique. While optimizing the percentage elongation property, the hard compound such as silica, iron oxide, and alumina, were discovered during the characterisation of the reinforcement, showing that PP and CCP can be used as reinforcement in metal matrix composite. The percentage of elongation of the hybrid composite was shown to be most affected by the PP, followed by processing temperature, stirring speed, CCP, and stirring time, using stir casting process parameter optimization. It was observed at 2.5 wt% of pumice particles, 2.5 wt% of carbonated coal particles, 700 °C processing temperature, 200 rpm stirring speed, and 5 min stirring time, the optimum percentage of elongation was discovered to be 5.6%, which is 25.43% lower than the percentage elongation of Al-alloy without reinforcing. The regression study developed a predictive mathematical model for the percentage elongation (PE) as a function of the stir casting process parameters and offered a high degree of prediction, with R-Square, R-Square (adj), and R-Square (pred) values of 91.60%, 87.41%, and 79.32% respectively.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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