Improving composite tensile properties during resin infusion based on a computer vision flow-control approach

Abstract

Liquid composite manufacturing techniques, mainly applied in the transport industry, have been studied and optimized for decades while defect analysis and its minimization have been a goal to increase reliability and mechanical performance. Researchers have found that many process parameters have a strong influence on the mechanical behavior of composite structures where the flow front velocity, closely related to voids, plays a considerable role. In this work, the optimal flow front velocity was evaluated and controlled using a computer vision system for different laminates improving the mechanical tensile properties and void content. Enhanced mechanical tensile properties were found using a feedback flow-controller vision system which was able to keep the optimal flow front velocity constant to reduce the air traps among tows and fibers. Tensile strength was enhanced up to 18% for fiber orientation at 0◦ and 3.3% at 90◦, whereas tensile modulus was increased up to 18.4% for fibers at 0◦ and 8.7% at 90◦. A novel methodology is presented through this work, aiming to improve the robustness of resin film infusion (RFI) processes while ensuring the quality of the composite material.