Functional printing for main distortion points in cured composite parts

Advancements in printing technologies have facilitated the integration of sensors within composite parts for aeronautical applications. Sensor characteristics were rigorously analyzed to meet the specific requirements of phenomena such as springback, affecting composite parts after curing. In this study, a Design of Experiments (DoE) was conducted to generate substantial data for training a surrogate model, which predicts distortions in L-shaped structures, thereby eliminating dependency on Finite Element Method (FEM) software. Utilizing the acquired insights, the paper further investigates the experimental study on sensor requirements encompassing location, operational temperature range, sensing capabilities, and signal acquisition during curing processes. The equipment and experimental setup are detailed to outline additional requirements for future research. This paper presents a comprehensive methodological approach for the development and characterization of sensors optimized for the curing of composite parts.