Enhancement of the hole quality of freeform CFRP with industrial robot posture optimization

Abstract

Carbon fiber-reinforced plastics (CFRP) are widely utilized in the aerospace industry owing to their exceptional strength-to-weight ratio and superior corrosion resistance. However, machining CFRP, particularly during drilling, remains challenging, often resulting in defects such as delamination and reduced precision. Industrial robots, which offer greater flexibility than traditional computer numerical control (CNC) machines, are increasingly used in CFRP machining. Nevertheless, their low stiffness can lead to machining quality issues, particularly during drilling processes, where external forces such as cutting forces induce tool tip vibrations. This study introduces a framework to improve hole quality in freeform CFRP drilling using industrial robots. A combination of an RGB-depth camera and a laser line scanner was employed to generate 3D point cloud data of the operational scene, enabling the precise determination of the shape of the CFRP and the normal vector at the drilling points. To further enhance drilling quality, posture optimization planning was applied to improve the stiffness of the robot at specific positions. Experimental results indicated that at a feed rate of 0.03 mm/rev, the average delamination factor decreased by 12.76%, with reductions reaching as high as 30%. Circularity improved by 15.28% under the same conditions. These findings demonstrate the potential of the proposed automated framework to achieve high-quality drilling in freeform CFRP applications, thereby addressing the key challenges in machining complex composite materials.