Modelling of tool wear incorporating various feeds in micro-drilling of carbon fibre-reinforced polymer (CFRP) composites

Micro-drilling of carbon fibre-reinforced polymer (CFRP) composites is gaining importance in high-end applications like aerospace to optimize the aerodynamic properties of structural components. However, the micro-drilling process in CFRPs remains challenging, particularly due to the complex and underexplored wear mechanisms of micro-drills. In the case of micro-drilling, the size effect plays a significant role, the ploughing dominancy is considerable and affects the chip formation mechanisms and the tool loading conditions, which are not strictly proportional to the rate of the tool wear. Consequently, the progression and modelling of wear of micro-drills in CFRPs cannot be directly implemented from macro-scale experiences. This study aims to develop a predictive model for flank wear of industrially used uncoated solid carbide micro-drills during CFRP machining. Thousands of holes were drilled to construct a general flank wear model, which was subsequently validated using additional experiments involving hundreds of holes. Tool wear was characterized through digital and scanning electron microscopy, while the influence of feed was analysed through analysis of variances (ANOVA). The developed general model incorporates feed and cutting length to predict micro-drills' flank wear accurately. The proposed model demonstrated high accuracy (maximum 13 % of main absolute percentage error) and robustness, offering a valuable tool for engineers to enhance process planning, maintain machining quality, predict remaining tool lifetime, and improve efficiency in composite micro-drilling operations.