Optimization of the Stirring Parameters of AZ91Mg-based Stir Casted Hybrid Composites using Taguchi and ANN

Singh, Kamal Kant; Mangal, Dharamvir

Abstract

In the current research, the fabricated Mg hybrid composites amalgamate with the vacuum-based squeezed stir casting process having TiC and Al2O3 reinforcement’s in which AZ91Mg-alloy is the base material. The study includes the processing parameters of the vacuum-based squeezed stir casting method (such as stirring time, stirrer depth, and stirring speed) that have been varied and then investigates their influential effect by using the L16 orthogonal Taguchi approach. By considering these parameters, the tribo-mechanical properties are also optimized like porosity, ultimate strength, and rate of wear loss of Mg-hybrid composites. The result reveals a significant association between processing parameters and optimized tribo-mechanical properties. The results signify that the processing parameters are best optimized at processing parameters of 500 rpm of stirring speed, 5 min of stirring time, and 50 mm of stirrer depth and the optimized tribo-mechanical properties are 0.4% porosity, 245 MPa of ultimate strength, and 0.0011 mm3 per min is the loss of wear rate. However, the ANOVA results contribute that the stirrer depth has the most significant processing parameter compared to other optimized parameters. This research also includes an artificially designed networking model which validates the designated set of empirical data. Thus due to their suitability for abrasion wear AZ91-hybrid composite gives a new divergence towards the designing parts of minuscule airplanes used in surveillance applications such as ailerons and wing flaps.


Keyword(s)

Artificial neural network, Mg-Hybrid composites, Stirrer optimize, VSSC technique, Taguchi approach


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