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Advanced quality assessment and damage monitoring in 3D-printed plastic and composite beams using machine learning | Synapse
March 3, 2026
Advanced quality assessment and damage monitoring in 3D-printed plastic and composite beams using machine learning
GP
GIa Hoang Phan
Puntos clave
Improved damage monitoring enhances the reliability of 3D-printed composite beams, ensuring better performance.
Machine learning models effectively assess quality, showing a significant reduction in detection time.
Observational analysis focused on multiple beam types using 3D printing techniques, maximizing insights on their structural integrity.
Highlights the potential need for integrating advanced technologies to improve monitoring processes in manufacturing.
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GIa Hoang Phan (Thu,) studied this question.
synapsesocial.com/papers/69a767bbbadf0bb9e87e220e
https://doi.org/https://doi.org/10.1007/s40964-025-01514-6
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