Investigating impacts of FDM printing parameters and geometrical features on void formation in 3D printed automotive components

Abstract

Additive manufacturing (AM) has opened a world of new possibilities in the automotive industry by offering high flexibility in design, shortening production time, and producing lightweight and customizable parts. Despite these advantages, the high risk of defect formation associated with AM processes and the difficulty of defect detection in quality control stages have hindered the rapid adoption of AM in the automotive industry. Mechanical tests are destructive tests which are usually used for quality control of conventionally fabricated components. However, they are not practical for quality control of AM parts since, due to the higher risk of defects, a higher number of AM parts should be mechanically tested which is time-consuming and expensive. Hence, rather than destructive mechanical tests, automakers require non-destructive imaging techniques for AM parts to characterize defects for a high number of samples at the quality control stage. This study aims to examine the impact of printing parameters and geometrical features on the void formation of an automotive component (car window holder). These outcomes will be helpful in the establishment of non-invasive quality control for the window car holder which is based on imaging techniques. For this purpose, a window car holder was printed with varying printing parameters using the FDM technique. Based on the geometry of the component, two regions with distinct geometrical features were specified and analyzed using Micro-CT. Results indicate that by increasing printing speed (30 to 60 mm/min) and temperature (230 °C to 250 °C), voids fraction decreased. Conversely, when increasing the printing layer thickness (0.1 to 0.3 mm), the void fraction increased. It was also concluded that void formation in regions with curved surfaces and overhang structures is significantly higher compared to edges with an angle of 90 ° to 60 °. These results offer a platform to reduce the risk of defect formation in 3D-printed automotive parts, improving quality control.