Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach

Author:

Almazán-Lázaro Juan-Antonio,López-Alba Elías,Díaz-Garrido Francisco-AlbertoORCID

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.

Publisher

MDPI AG

Subject

General Materials Science

Reference43 articles.

1. Vehicle weight is the key driver for automotive composites

2. Textile composites in the automotive industry

3. Guiding selection for reduced process development time in RTM

4. Hybrid structures consisting of sheet metal and fibre reinforced plastics for structural automotive applications;Lauter,2013

5. Development of advanced vacuum-assisted resin transfer molding technology for use in an MRJ empennage box structure;Yamashita;Mitsubishi Heavy Ind. Tech. Rev.,2008

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