Machine learning reveals vulnerabilities in 3D-printed carbon-fiber composites

Components made of glass- and carbon- fiber reinforced composites, soaring in high-performance applications, can be 3D printed. A team of researchers has found that the printer head toolpaths are easy to reproduce -- and therefore steal -- with machine learning (ML) tools applied to the microstructures of the part obtained by a CT scan.

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