Statistical Analysis of Drilling-Induced Delamination in Glass–Nylon Fiber-Reinforced Polyester Composites

Abstract This research employed statistical and experimental design techniques to minimize drilling-induced delamination in a hybrid composite composed of eight alternating layers of glass and nylon fibers combined with a polyester matrix, fabricated using the hand layup method. The drill diameter, spindle speed, and feed rate were considered as input variables, while the delamination factor ( F d ) at entry and exit surfaces served as the response. Taguchi L27 orthogonal array was used to design the experiments, and the influence of each parameter was analyzed using the signal-to-noise ratio, ANOVA, Pareto, and graphical methods. Results showed that the drill diameter had the most significant effect, contributing over 60% to delamination variation with a p -value below 0.05, followed by feed rate and spindle speed. Delamination increased with larger drill sizes, higher feed rates, and lower spindle speeds, with more damage observed at the exit surface. The optimal drilling conditions of a 6-mm drill diameter, 1,250 rpm spindle speed, and 50 mm / min feed rate resulted in minimal delamination. These trends were validated through main effect plots, surface plots, and contour graphs. The regression-based model provided a reasonable fit to the experimental data, with an R 2 value above 0.95 and an average prediction error of about 0.3%. This research demonstrates that comprehensive statistical analysis and process optimization enhance drilling performance and reduce damage in hybrid composites, offering benefits for advanced manufacturing and civil engineering applications.