Experimental investigation for machinability aspects of graphene oxide/carbon fiber reinforced polymer nanocomposites and predictive modeling using hybrid approach
Jogendra Kumar, Rajesh Kumar Verma
Abstract
This article explores the drilling behavior of polymer nanocomposites reinforced by Graphene oxide/Carbon fiber using a hybrid method of Grey theory and Principal component analysis (GR-PCA). An online digital dynamometer was employed for the evaluation of Thrust Force and Torque. The image processing technique computes the delamination. Response surface methodology (RSM) considers the parameters, namely, drilling speed (S), feed rate (F), Graphene Oxide wt.% (G) in designing the experimentation array. Principal component analysis (PCA) was used to tackle the response priority weight during the combination of multiple functions. Analysis of variance (ANOVA) scrutinized the influence of parameters and intended the regression models to predict the response. GR-PCA evaluated the optimal parametric setting and remarked that feed rate acts as the most predominant factor. The higher feed rate and wt.% of G is responsible for surface damages like fiber pull-out, fiber fracture and cracks. A significant improvement in drilling responses has been obtained and also validates through confirmatory test and microstructure investigations.