Prediction of Delamination Defects in Drilling of Carbon Fiber Reinforced Polymers Using a Regression-Based Approach

Carbon fiber-reinforced polymer (CFRP) structures have been increasingly used in various aerospace sectors due to their outstanding mechanical properties in recent years. However, the poor machinability of CFRP plates, combined with the inhomogeneous behavior of fibers, poses a challenge for manufacturers and researchers to define the critical factors and conditions necessary to ensure the quality of holes in CFRP structures. This study aims to analyze the effect of drilling parameters on CFRP delamination and to predict hole quality using a regression-based approach. The design of the experiment (DOE) was conducted using Taguchi’s L9 3-level orthogonal array. The input drilling variables included the feed rate, spindle speed, and three different drill types. A regression-based model using partial least squares (PLS) was developed to predict delamination defects during the drilling of CFRP plates. The PLS model demonstrated high accuracy in predicting delamination defects, with a Mean Squared Error (MSE) of 0.0045, corresponding to an accuracy of approximately 99.6%, enabling the rapid estimation of delamination. The model’s predictions were closely aligned with the experimental results, although some deviations were observed due to tool inefficiencies, particularly with end mill cutters. These findings offer valuable insights for researchers and practitioners, enhancing the understanding of delamination in CFRPs and identifying areas for further investigation.