Modelling and optimization of experimental parameters for porosity in friction stir processed aluminum foam using response surface methodology

Aluminium foams are an emerging multifunctional material with a distinct structure and unique properties. However, controlling the porosity and pore morphology is still challenging because of the dependency on a number of the process parameters. This study uses a statistical approach to control porosity and influence of each parameter on porosity in a friction-stir processed aluminium plate. A second-order Response Surface Methodology (RSM) model is developed, and relationship among porosity and process parameters like Weight % TiH2, Weight % Al2O3, number of passes, tool rpm, and foaming temperature has been established and influence of each parameter on porosity is investigated. Experimental results validate the model, optimising 80-85% porosity for multifunctional applications. The optimal parameters are 1.2 wt% TiH2, 2.3 wt% Al2O3, 3 passes, 3000 tool rpm, and 738 degrees C foaming temperature. It was observed from the ANOVA that most influencing parameter is tool rpm, number of passes, followed by foaming temperature. The Scanning electron microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDS) analyses of the fabricated foam at its optimised condition confirm the uniform distribution of pores and the elements. This statistical optimisation model minimises experimental time and resource usage, demonstrating substantial technical and industrial significance.