Session: Research Posters

Paper Number: 173547

Hole Quality Improvement in Complex Cfrp Geometries via Robotic Posture Control 

Carbon fiber reinforced plastics (CFRP) are integral to aerospace manufacturing because of their high strength-to-weight ratio and corrosion resistance. As design demands grow, CFRP applications are evolving into increasingly complex geometries. Industrial robots are increasingly employed for CFRP machining, but their comparatively lower stiffness than CNC machines often compromise machining precision. This reduced stiffness frequently causes delamination during drilling, leading to structural defects and reduced dimensional accuracy.

Previous studies have proposed methods such as tool geometry, selection of machining conditions, and the use of a support plate have been proposed to reduce delamination defects in CFRP machining. However, these methods have primarily focused on the drilling process of CFRP with simple plate shapes. While some research has been conducted to enhance the machinability of curved CFRP forms and reduce delamination during drilling, these studies have largely been limited to simple tube shapes. In response to these limitations, drilling processes utilizing industrial robots have gained attention. Industrial robots offer greater freedom and flexibility than conventional CNC (Computer Numerical Control) machinery, enabling precise drilling operations in complex shapes or difficult-to-access points, thus reducing setup times and diversifying processes to enhance overall production efficiency. Additionally, robots can easily adapt to various working conditions through programming, delivering consistent drilling quality with high repeatability.

In this study, a new approach was proposed to reduce delamination defects through posture optimization of the robotic arm in the freeform CFRP drilling process. This approach utilized 3D point cloud data to accurately identify the shape of the CFRP and determine the precise normal vector at the drilling points, thereby enhancing the precision of the drilling process.

Posture optimization of the industrial robot was conducted by minimizing deviations in the X and Y axes using a cost function. The industrial robot's stiffness was validated both indirectly through Cartesian deviation analysis and directly via compliance measurement using an impact hammer test. Optimization was performed at 15 positions, resulting in a maximum compliance improvement of up to 36%.

Delamination analysis with the industrial robot revealed that increasing the feed rate from 0.02 mm/rev to 0.03 mm/rev worsened delamination. Posture optimization improvements were more significant at higher feed rates, with a 12.76% reduction in delamination at 0.03 mm/rev, demonstrating the effectiveness of robotic posture optimization in enhancing drilling quality in CFRP materials.

Posture optimization significantly increased the stiffness of the industrial robot, which in turn reduced delamination defects during the CFRP drilling process. If the methods proposed in this paper are applied, it is anticipated that industrial robots could be utilized in machining large workpieces, such as actual aerospace components, due to their high degrees of freedom.

Presenting Author: Hyung Wook Park Ulsan National Institute of Science and Technology

Presenting Author Biography: Hyung Wook Park is a professor at Department of Mechanical Engineering on Ulsan National Institute of Science and Technology. Dr. Park received bachelor and master’s degrees from Seoul National University, Korea. He then continued his PhD at Georgia Institute of Technology, USA. He has worked in Hyundai Motor Company and Korea Institute of Machinery and Materials (KIMM) as researcher. In 2009, Dr. Park has formed Multiscale Hybrid Manufacturing Laboratory to investigate the hybrid manufacturing and materials at UNIST.

Authors:

Hyung Wook Park Ulsan National Institute of Science and Technology