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

Abstract

Optimization 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 (F _R), and spindle speed (S _S) have been chosen as governing factors and their performances have been characterized by delamination value (D _V) and thrust force (T _F). 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 D _V and T _F. 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 (F _R), and 2100 rpm of spindle speed (S _S) make up the ideal machining configuration. The mean response table indicated the S _S as the most influential governing contrariant on the T _F and D _V. 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.