Almazán-Lázaro, Juan AntonioLópez-Alba, ElíasDíaz-Garrido, Francisco Alberto2024-09-262024-09-262018-12-051996-1944doi:10.3390/ma11122469https://hdl.handle.net/10953/3237T2 Q2 (145/361 Materials Science, Multidisciplinary, IF 2018 = 2.467)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.engAtribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/CompositeTensileOptimizationAutomotiveLightweight designinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccess