Investigation of delamination and surface roughness in end milling of glass fibre reinforced polymer composites using Fuzzy Model and Grey wolf Optimizer

This work deals with the end milling operation on glass fibre (± 45° orientation) reinforced polymer (GFRP) composites using three different end mill cutters with four flutes of 6 mm diameter. Three factors such as end-milling cutters, cutting speed (CS) and feed rate (FR) are considered whereas delamination (Fd) and surface roughness (SR) are the measures for this machining. Box Behnken design (BBD) of response surface methodology (RSM) is adopted for designing the trial runs, regression modelling and fuzzy inference prediction analysis were carried out. Analysis of Variance shows that for SR and Fd, all the considered inputs are significant. Bi-directional glass fibres are bonded well with the epoxy matrix and no pores or voids are seen in micrographs. The reason why SR rises as CS and FR rise is high friction between tool and workpiece, increasing the FR drastically increases the Fd whereas at lower and higher CS lower Fd is achieved. The maximum deviation between experimental and regression predicted value is 7.48% for SR and 0.71% for Fd, Among fuzzy and experimental results the deviation is 4.99% for SR and 1.04% for Fd. Nature inspired metaheuristic algorithm grey wolf optimizer (GWO) produces the optimum condition 60 rpm of CS and FR of 0.05 mm/rev for a combined objective function value towards minimization of 1.2875 for TiAlCN end mill cutter. Thus, the experimental, regression and fuzzy inference models are thoroughly examined and presented.