Demonstrates improved error detection in 3D printing, suggesting enhanced automation in manufacturing.
As an additive manufacturing process, 3D printing offers a very wide range of applications in industrial use. From prototype construction to small series production, components that are needed at short notice can be made available quickly without long set-up times. The industrial use of AI methods for quality assurance in Industry 4.0 processes increases the efficiency of manufacturing processes. For automated additive manufacturing, the implementation of AI systems specifically for error monitoring is essential. The selection and training of a suitable AI language model enables reliable and early detection of 3D printing errors, thus facilitating automation and integration into existing manufacturing processes.
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Abdrabouh et al. (2026) studied this question.
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