Advanced quality assessment and damage monitoring in 3D-printed plastic and composite beams using machine learning

Key Points

• 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.