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Classification and Automated Quality Assurance of 3D Concrete Printed Surfaces (2024-05)

10.1016/j.autcon.2024.105467

 Otto Jens, Maiwald Patrick
Journal Article - Automation in Construction, Vol. 164, No. 105467

Abstract

The additive manufacturing of concrete components has made significant progress in the last 10 years. The increasing application of 3D printing in practice now also requires a categorization of the quality of the printed concrete surfaces that remain visible after printing. The quality of visible surfaces of additively manufactured components can be assessed according to the quality of formwork-exposed concrete surfaces. A suitable basis for this assessment is provided by the applicable regulations for exposed concrete surfaces in Germany and other international standards. In this publication, characteristics and requirements of individual concrete filaments as well as printed components are developed. These evaluate geometric, optical and structural properties of printed concrete surfaces. These can be used as a basis for further standardization of quality requirements for 3D-printed surfaces and for automated algorithms, fully automated manufacturing and monitoring of printed concrete components.

9 References

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BibTeX 
@article{otto_maiw.2024.CaAQAo3CPS,
  author            = "Jens Otto and Patrick Maiwald",
  title             = "Classification and Automated Quality Assurance of 3D Concrete Printed Surfaces",
  doi               = "10.1016/j.autcon.2024.105467",
  year              = "2024",
  journal           = "Automation in Construction",
  volume            = "164",
  pages             = "105467",
}
Formatted Citation

J. Otto and P. Maiwald, “Classification and Automated Quality Assurance of 3D Concrete Printed Surfaces”, Automation in Construction, vol. 164, p. 105467, 2024, doi: 10.1016/j.autcon.2024.105467.

Otto, Jens, and Patrick Maiwald. “Classification and Automated Quality Assurance of 3D Concrete Printed Surfaces”. Automation in Construction 164 (2024): 105467. https://doi.org/10.1016/j.autcon.2024.105467.