摘要：The wear behavior of multi-walled carbon nano-tubes(MWCNTs)reinforced copper metal matrix composites(MMCs)processed through powder metallurgy(PM)route was focused on and further investigated for varying MWCNT quantity viaexperimental,statistical and artificial neural network(ANN)*** increases with increment in *** loss against varying load and sliding distance was analyzed as per L16orthogonal array using a *** parameter optimization by Taguchi’s method revealed that wear loss was affected to a greater extent by theintroduction of MWCNT;this wear resistant property of newer composite was further analyzed and confirmed through analysis ofvariance(ANOVA).MWCNT content(76.48%)is the most influencing factor on wear loss followed by applied load(12.18%)andsliding distance(9.91%).ANN model simulations for varying hidden nodes were tried out and the model yielding lower MAE valuewith3-7-1network topology is identified to be *** model predictions with R value of99.5%which highly correlated withthe outcomes of ANOVA were successfully employed to investigate individual parameter’s effect on wear loss of Cu?MWCNTMMCs.