Nowadays, the additive manufacturing of multifunctional materials is booming. The fused deposition modeling (FDM) process is widely used thanks to the ease with which multimaterial parts can be printed. The main limitation of this process is the mechanical properties of the parts obtained. New continuous-fiber FDM printers significantly improve mechanical properties. Another limitation is the repeatability of the process. This paper proposes to explore the feasibility of printing parts in continuous carbon fiber and using this fiber as an indicator thanks to the electrical properties of the carbon fiber. The placement of the fiber in the part is based on the paths of a strain gauge. The results show that the resistivity evolves linearly during the elastic period. The gauge factor (GF) increases when the number of passes in the manufacturing plane is low, but repeatability is impacted. However, no correlation is possible during the plastic deformation of the sample. For an equivalent length of carbon fiber, it is preferable to have a strategy of superimposing layers of carbon fiber rather than a single-plane strategy. The mechanical properties remain equivalent but the variation in the electrical signal is greater when the layers are superimposed.

This study investigates the feasibility and effectiveness of two non-destructive testing methods, active thermography and shearography, on 3D-printed thermoplastic (TP) composites reinforced with continuous carbon fiber. Artificial defects were introduced into the composite plate to benchmark the detection capabilities of these non-destructive testing techniques (NDT). Active thermography produced a thermogram that highlighted defects through variations in surface temperature. Although effective for identifying defects ranging from 3 to 10 mm in size at four different depths, specifically 1 mm, 1.25 mm, 1.5 mm, and 1.75 mm, through the thickness of a 2.8 mm plate, the method encountered some limitations. It faced challenges in detecting deeper defects and accurately determining their shapes. Shearography, which utilizes fringe pattern distortions to detect surface displacement anomalies, successfully identified near-surface defects within the same size range. However, it required more expertise for accurate interpretation and struggled with detecting smaller and deeper defects. The complementary strengths and limitations of these methods suggest that employing both could offer a more comprehensive solution for defect detection in 3D-printed TP composites.

The presented article analyzes the impact of internal defects on the modal responses of polyamide parts subjected to bending. Samples with defects of various sizes (0, 3, 5, 7, and 10 mm) located at the neutral bending line were tested. Modal properties were measured via an acoustic and a vibration sensor, using impulse excitation and fast Fourier transform (FFT) analysis. Modal properties include peak frequency, damping and amplitude. Non-defective samples show lower peak frequency and stronger amplitude for both detectors. Moreover, defects larger than 3 mm have minimal impact on peak frequency. The vibration detector is more sensitive to delamination presented at 7 and 10 mm defects. In addition, elevated peak frequency at 3 mm is the result of local hardening at the defect edge. Moreover, a neutral line position reduces damping when the defect size approaches 5 mm. Conversely, acoustic detectors ignore delamination and reveal lower damping and amplitude at 7 and 10 mm defects. Furthermore, internal sound diffusion from 3 and 5 mm defects enhances air losses and damping. Acoustic detectors only evaluate fault size and position, whereas vibrational detectors may detect local reinforcement and delamination more easily. These results highlight the importance of choosing the right detector according to the location, size, and specific modal characteristics of defects.