Abstract
In 3D printing of cement-based materials, it is imperative to ensure geometrical consistency of the print with the as-designed/modeled system. Time-dependent, deformable systems like concrete present multiple challenges in ensuring appropriate post-print quality. This paper presents a suite of point cloud comparison techniques, which can be used individually or in combination, to quantify the amount of mismatch between the as-designed and as-printed systems, using morphological analysis. A semi-quantitative error distance method is proposed, which can be easily accomplished using direct mapping of the actual and reference point clouds. A print accuracy index (PAI) based on centroidal distances is proposed as a global quantifier of the print quality. Furthermore, a topological set theory (TST)-based approach is used to determine layer-wise overlap, which helps in isolating localized inconsistencies. The methods are tested on a variety of small cuboids, and further verified using a larger mortar print. It is expected that these methodologies can be suitably adapted to indicate the efficiency of the print, after the fact, or during printing. The latter facilitates in-line quality checks, that can in turn lead to real-time alterations in the materials or processes.
Original language | English (US) |
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Article number | 102499 |
Journal | Additive Manufacturing |
Volume | 49 |
DOIs | |
State | Published - Jan 2022 |
Keywords
- 3D printed concrete
- Error distance
- Mathematical morphology quality control
- Point cloud analysis
- Print accuracy index
ASJC Scopus subject areas
- Biomedical Engineering
- General Materials Science
- Engineering (miscellaneous)
- Industrial and Manufacturing Engineering