Machining performance optimization of graphene carbon fiber hybrid composite using TOPSIS-Taguchi approach

Abstract

AbstractOptimization of process factors plays a significant role in process efficiency and effectiveness. In this context, an attempt has been made to access the optimized machining factors for polymer nanocomposites including Graphene oxide (GO)/Carbon fiber (CF). To do this, graphene concentration (wt%), feed rate (FR), and spindle speed (SS) have been chosen as governing factors and their performances have been characterized by delamination value (DV) and thrust force (TF). After defining the levels for these factors, the Taguchi experiment design method was used to obtain the experimental trial series. A TiAlN SiC-coated 06 mm drill bit was used in a CNC machine configuration to drill holes. Their corresponding performance values were noted down as DV and TF. TOPSIS method has been incorporated for accessing the measured performance dataset and relative closeness values have been calculated. These relative closeness values have been further subjected to Taguchi’s signal-to-noise ratio (S/N ratio) leading to the evaluation of an optimized parametric combination. 2 wt% of graphene, 100 mm/min of feed rate (FR), and 2100 rpm of spindle speed (SS) make up the ideal machining configuration. The mean response table indicated the SS as the most influential governing contrariant on the TF and DV. In addition, an assessment was conducted to determine the suitability of the model, and it was determined that the stated model does not exhibit any deficiencies or complications.