An integrated module for predictive modelling and machinability appraisal during milling of modified graphene/epoxy nanocomposites

Abstract

ABSTRACT This article investigates the machining performance optimization of polymer nanocomposites modified by GO/Carbon fiber. The Milling responses, namely, surface roughness (Ra) and cutting force (Fc), are optimized by using the integrated approach of Grey theory and Principal component analysis based on Technique for Order of Preference by Similarity to Ideal Solution method (Grey-PCA-TOPSIS). The Taguchi orthogonal design was used for the Milling test experimentation of the proposed nanocomposite. The outcomes of Analysis of Variance (ANOVA) demonstrate the model adequacy of the proposed hybrid approach. The optimal setting was obtained as spindle speed 1600 rpm, feed rate 240 mm/min, depth of cut 0.5 mm and Graphene Oxide weight 1%. The analysis of means (ANOM) was used to appraise the significant factor and their effects on machining responses. The spindle speed works a primary role in surface finishing. The combined effect of spindle speed with a lower depth of cut, in turn, reduces the extent of vibration occurrence and the development of the defect and cracks. The outcomes have been validated by a confirmatory test that proves the proposed hybrid module practicality for manufacturing product/process improvement. Further, SEM analysis of machined samples was performed to check the quality and surface features required.