Evaluation Through SEM Image Processing of the Volumetric Fiber Content in Continuos Fiber-Reinforced Additive Manufacturing Composites

This work shows the estimation of the volumetric fiber content (Vf) using image processing techniques. The Vf is needed to establish mechanical properties of composites using the rule of mixtures or other more advanced prediction models for the mechanical properties. The proposed method is tested with images acquired for carbon, Kevlar, and fiberglass fiber bundles used in the fiber deposition modeling (FDM) in the additive manufacturing process. The fiber bundles are provided by Markforged ?? and are used in the Markforged Two ?? printer. Then, different gray threshold and segregation algorithms are convolved with the digitized images to to isolate matrix from fibers such that a separate fiber and matrix area counting can be done and an appropriate Vf can be established. Results obtained with image analysis are close to values reported using technical standards, hence validating the proposed method.

Automated summary

This study demonstrates the estimation of volumetric fiber content using image processing techniques, which is essential for predicting the mechanical properties of composites. By analyzing images of carbon, Kevlar, and fiberglass fiber bundles, the method successfully separates fibers from matrix to establish accurate Vf values, validating the proposed approach.