The optimization of the curing process is significantly improved using deep learning techniques—indicating enhanced performance in composite laminates.
Deep learning achieved a reduction in curing time by up to 30% during the analysis of scarf-repaired laminates, enhancing efficiency.
Assessment using surrogate modeling and optimization algorithms identified crucial parameters affecting the curing process—providing valuable insights.
The findings highlight the potential of deep learning in improving the manufacturing processes of composite materials—calling for further industry applications.