Abstract
X-ray computed tomography (CT) is a non-destructive measuring technique that allows performing measurements of outer as well as inner geometries and features. This work addresses the application of CT in the field of fiber-reinforced polymers, which are increasingly used in industry to manufacture products with enhanced mechanical properties and lightweight. In particular, when fiber-reinforced components are fabricated for example using the injection molding process, the presence of long and well-oriented fibers is necessary to achieve good mechanical properties of the products, but the process itself often leads to relevant fiber breakage and complex fiber orientation. In this context, for optimizing the process, adequate and accurate measuring techniques are needed to correlate the injection molding process parameters with the fiber geometrical characteristics. Metrological CT is the only available three-dimensional measuring technique capable of evaluating in a non-destructive way the relevant fiber geometrical characteristics, including fiber length and fiber orientation. The conventional methods are in fact commonly based on optical measurements, which require destructive operations. CT data are already successfully used to evaluate the fiber orientation, whereas the fiber length measurement is more complex because it needs the individual fibers to be identified and segmented. Despite the inherent difficulty of the latter operations, there are already software tools able to measure the fiber length from high-resolution CT data. However, the accuracy of CT fiber length measurements has not been thoroughly investigated so far. This work proposes an experimental methodology for the accuracy evaluation and enhancement of fiber length measurements performed by means of X-ray computed tomography on injection molded components characterized by a polymer matrix reinforced with glass fibers. The work lays the foundations for establishing CT as a tool to be effectively used for quality improvement of injection molding processes and products, as well as for enhancing process simulations and modelling in the Industry 4.0 context.
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