Digital Process Twins for Automated Manufacturing of Thermoplastic Composites: Challenges and Opportunities.

Automated Fiber Placement (AFP) is transforming the fabrication of high-performance thermoplastic composites by enabling precision layup of fiber tows with spatially controlled heating and compaction. Yet, the interplay of radiative heating, heat diffusion, and material flow during AFP remains one of the least understood links between process parameters and structural performance. This seminar presents a unified experimental and modeling framework to unravel these coupled multi-scale multi-physics phenomena and advance the creation of digital process twins for advanced manufacturing of composites.

The discussion will begin with the design and thermal characterization of a Xenon-arc flash heating system developed for in-situ processing of CF-PAEK tows. High-resolution irradiance mapping and infrared thermography reveal the dynamic spatial nonuniformity of heat flux during laydown, providing direct insights into tow heating and cooling behavior. These experimental results are coupled with a physics-based “plug-flow” thermal model that captures the motion of the tow, its interaction with the roller and substrate, and the resulting anisotropic heat transfer under realistic AFP conditions.

The resulting digital process twin quantitatively predicts temperature evolution, nip-point bonding conditions, and crystallinity gradients; key factors governing consolidation quality and defect formation. By linking measured irradiance fields with validated numerical simulations, this framework offers a predictive capability for optimizing processing parameters to achieve consistent microstructure and interlayer adhesion. The seminar will conclude with perspectives on integrating these models with in-situ sensing and machine learning to enable smart, autonomous, defect-tolerant composite manufacturing.

Speaker : Dr. Paul Davidson

Biography:

Dr. Paul Davidson is an Assistant Professor of Mechanical and Aerospace Engineering at the University of Texas at Arlington, where he leads the Digital Design and Advanced Manufacturing of Composite Structures research though the Laboratory of Advanced Materials, Manufacturing and Analysis (LAMMA). His research integrates experimental mechanics, multiscale modeling, and machine learning to develop digital twins for automated composite fabrication and structural performance prediction. His work is supported by the Air Force Office of Scientific Research (AFOSR), the Air Force Research Laboratory (AFRL), the National Science Foundation (NSF), and the University of Texas System.