Taguchi-Grey multi-response optimization of wear parameter of new nanocomposite formulation of Al–Si–Mg alloy reinforced with synthesis carbon nanotube and periwinkle shell nanoparticles

The Taguchi-Grey relational method was used to determine the optimal setting of wear behavior of Al–Si–Mg alloy reinforced with synthesis carbon nanotube derived from rice husk (CNTs-derived RH) and periwinkle shell nanoparticle (PWSnp) nanocomposites for friction material. The applied load, sliding speed, sliding time, and abrasive mesh were the wear parameters, and coefficient of friction and wear rate were used in the multi-response for the study. The minimum coefficient of friction and wear rate were obtained at the optimal parameter of applied load (20 N), sliding speed (1.5 m/s), sliding time (60 min), and abrasive mesh (1000 grit). The coefficient of friction rises as applied load increases and decreased with an increase in sliding speed, sliding time, and abrasive mesh. The Taguchi-Grey approach can be used in multi-response optimization of Al–Si–Mg/CNTs-derived RH and PWSnp nanocomposites since the experimental values are within the limit of predicted values. Hybrid nanocomposites of A356 alloy 0.5 wt% CNTs derived from RH and PWSnp can be used in brake applications.