The manufacturing process of robotic coreless filament winding has great potential for efficient material usage and automation for long-span lightweight construction applications. Design methods and quality control rely on an adequate digital representation of the fabrication parameters. The most influencing parameters are related to the resin impregnation of the fibers and the applied fiber tension during winding. The end-effector developed in this study allows efficient resin impregnation, which is controlled online by monitoring the induced fiber tension. The textile equipment was fully integrated into an upscaled nine-axis robotic winding setup. The cyber-physical fabrication method was verified with an application-oriented large-scale proof-of-concept demonstrator. From the subsequent analysis of the obtained datasets, a characteristic pattern in the winding process parameters was identified.

Digitization and automation are essential tools to increase productivity and close significant added-value deficits in the building industry. Additive manufacturing (AM) is a process that promises to impact all aspects of building construction profoundly. Of special interest in AM is an in-depth understanding of material systems based on their isotropic or anisotropic properties. The presented research focuses on fiber-reinforced polymers, with anisotropic mechanical properties ideally suited for AM applications that include tailored structural reinforcement. This article presents a cyber-physical manufacturing process that enhances existing robotic coreless Filament Winding (FW) methods for glass and carbon fiber-reinforced polymers. Our main contribution is the complete characterization of a feedback-based, sensor-informed application for process monitoring and fabrication data acquisition and analysis. The proposed AM method is verified through the fabrication of a large-scale demonstrator. The main finding is that implementing AM in construction through cyber-physical robotic coreless FW leads to more autonomous prefabrication processes and unlocks upscaling potential. Overall, we conclude that material-system-aware communication and control are essential for the efficient automation and design of fiber-reinforced polymers in future construction.