Manufacturing thick laminates using a layer by layer curing approach

The work presented in this paper puts forward a manufacturing strategy for the processing of thermosetting composites based on Layer by Layer (LbL) curing. The process operates additively with sublaminates placed in a heated press, partially cured while consolidating, followed by loading of the next sublaminate and repeating the cycle until part completion. Coupled consolidation-cure simulation was utilised to design the process and establish its capabilities showing that halving the cure time is possible for thick parts. Mechanical testing showed that for pre-cure of placed layers below the gelation degree of cure, interlaminar properties are equivalent to those of conventionally manufactured material. A trial was carried out demonstrating successfully the LbL process. On-line measurements of temperature and compaction matched the predictions of the simulation, whilst the quality of the material produced is equivalent to that of conventionally produced composites.Engineering and Physical Sciences Research Council (EPSRC)This work was supported by the Engineering and Physical Sciences Research Council (grant number EP/P006701/1) through the EPSRC Future Composites Manufacturing Research Hub.Composites Part A: Applied Science and Manufacturin

Model based data-driven optimisation of automated fibre placement set up

The composites manufacturing industry relies heavily on manual hand layup, unsuitable for increasing demands. Automated Fiber Placement (AFP) offers a solution, but setup complexity and extensive trials inflate costs. Digital tools promise to expedite development, but CPU-intensive simulations limit large-scale parameter optimisation. This paper introduces Gaussian Process (GP) models for understanding AFP parameters’ relationship with nip-point temperature. The GP emulator streamlines optimisation, offering accurate power curves with minimal simulations. An efficient method to enhance emulator performance through sequential design is also proposed, providing a cost-effective decision tool for AFP optimisation