The present study examined the effects of drilling parameters such as spindle speed (N), feed rate (f), diameter of the tools (d) and drill geometry such as twist drills (HSS-TiN) and brad and spur drills (BSD) used on delamination damage in a biosandwich structure consisting of an epoxy matrix reinforced with bidirectional jute fibres and cork (JFCE). Response surface methodology (RSM) and artificial neural networks (ANNs) were exploited to evaluate the influence and interaction of the cutting parameters on the delamination factor (F_d) at the output during drilling. In addition, several optimization methods, such as desirability-based RSM, the genetic algorithm (GA) and the fmincon function, were applied to validate the optimal combination of cutting parameters (f, N and d) in the structures studied in biosandwiches during this research. According to the experimental results, severe damage was indeed observed with the BSD tool (F_d = 1.684) compared to the HSS-TiN tool (F_d = 1.555) for the same cutting conditions. To obtain the minimum F_d, the optimum conditions obtained by GA were respectively 1397.54 rev/min, 51.162 mm/min and 5.981 mm for HSS-TiN for f, N and d.

本研究考察了钻孔参数的影响，如主轴转速 ( N )、进给率 ( f )、刀具直径 ( d ) 和钻头几何形状，如麻花钻 (HSS-TiN) 和平头钻和直钻 (BSD)用于修复由双向黄麻纤维和软木 (JFCE) 增强的环氧树脂基体组成的生物夹层结构中的分层损坏。响应面方法 (RSM) 和人工神经网络 (ANN) 被用来评估切削参数对分层因子 ( F _d) 在钻孔过程中的输出。此外，还应用了几种优化方法，如基于合意性的 RSM、遗传算法 (GA) 和 fmincon 函数，以验证生物夹心研究结构中切割参数 ( f , N和d )的最佳组合。研究。根据实验结果，在相同的切削条件下，与 HSS-TiN 刀具（F _d = 1.555）相比，BSD 刀具（F _d = 1.684）确实观察到了严重的损坏。为了获得最小F _d，GA 获得的最佳条件分别为 1397.54 rev/min、51.162 mm/min 和 5.981 mm，对于f, N和d。