Mathematical morphology-based point cloud analysis techniques for geometry assessment of 3D printed concrete elements

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 asprinted 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 realtime alterations in the materials or processes.

Automated summary

This paper presents a suite of point cloud comparison techniques for 3D printing of cement-based materials, which can be used to quantify the mismatch between the designed and printed systems. It also proposes a print accuracy index and a topological set theory-based approach to evaluate the print quality.