13. Material Characterization of Self-Sensing 3D Printed Parts

Additive manufacturing has seen a resurgence in recent years, mainly driven by its ability to produce parts with complex designs and incorporate multiple components into a single manufactured part. However, additive manufacturing still needs improvements to fabricate consistent and reliable parts. Some of the shortcomings of the process include the effects of build orientation on the material properties. Current structural health monitoring methods, such as visual photography and thermography, provide limited data to quantify the quality and reliability of printed part. In this study, 3D printed novel sensors were embedded within a part and were evaluated as an alternative method for structural health monitoring. The embedded sensors were composed of conductive filament and are intended as a non-intrusive method to monitor the structural health of the part during its service life. Filaments using novel materials, e.g. conductive polylactic acid, were evaluated for their material characteristics and suitability for sensor verification and validation. Specifically, the novel conductive filaments were evaluated for their performance in terms of mechanical and electrical properties. The Young’s modulus of the additively manufactured, polylactic acid part was determined by both tensile testing and cantilever testing; and temperature sensitivity was determined by resistance measurements during thermal cycling. Embedding of the sensor into the service part during the printing process can reduce the cost and production time for structural health monitoring and provide a new application area for additive manufacturing.