Semester of Graduation

Summer 2024

Degree

Master of Science in Electrical Engineering (MSEE)

Department

Division of Electrical & Computer Engineering

Document Type

Thesis

Abstract

Extrusion-based construction 3D printing (C3DP) is an innovative and emerging technology aiming at the modernization of the construction industry. It uses robots and computer control to reduce the need for human labor and to decrease construction time and cost. C3DP creates elements layer by layer without using formworks, and it is critical to detect layer defects and deformations to ensure that each layer is printed with the desired dimensions. These defects can lead to a variety of issues during or after the construction process, including the collapse of freshly printed elements. In order to detect such deformations and to enable automated process adjustments, the extrudate must be inspected during the process and relevant data need to be collected. The purpose of this thesis is to provide two real-time systems of differing technologies, using LiDAR and structured laser light vision to encourage the progression of quality control in C3DP. Based on the quantitative data and measurement results, the LiDAR technique is able to continuously perform extrudate width and height and measurements with an average error less than 1.2 mm and a maximum error below 1.5 mm. The structured laser light vision system outperforms the LiDAR technique with a maximum error of less than 0.96 mm and an average error under 0.69 mm. The findings of this thesis also provide new insights into the influence of several parameters, such as the data collection cycle (LiDAR technique), extrudate size, number of layers, and extruder traversal speed on the performance of the proposed systems.

Date

7-19-2024

Committee Chair

Kargarian, Amin M.

DOI

https://doi.org/10.31390/gradschool_theses.6009

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Available for download on Tuesday, July 15, 2025

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