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.

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