The research investigates the dry sliding wear characteristics of Al7475 alloy-based composites reinforced with three dissimilar powders (SiC, TiB2, and Flyash) in the context of solid waste management. The aim of this paper to analyze the effect of selected parameters such as Reinforcements (RT), sliding distance (SE) and sliding speed (SD) on specific wear rate (SWR). Three different Al composites (Al7475/3 wt% of RT, Al7475/6 wt% of RT, Al7475/9 wt% of RT) are produced by squeeze casting process. As per L27 orthogonal array design, the wear tests were performed on Pin on Disk (POD) apparatus under dry conditions. SEM and EDS tests are performed to analyze the surface morphologies of wear test samples. The influence of various parameters on wear behavior was investigated using S/N ratio and ANOVA test. The regression and experimental results are compared to estimate the predicted error, coefficient of correlation. ANN is employed to predict the model to analyze SWR of wear parameters. The experiment and perdition model (3–10–1) developed from ANN are interrelated with the correlation factor of 0.99527 or 99.527% for the training algorithm of LM technique. The closeness value between the ANN and experiment results improves the scope of predicting the SWR of the developed composite. The model is designed to assist engineers in forecasting component failures in automobile and manufacturing industries resulting in cost and time savings.
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