Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148291
Title: Improving surface finish quality in extrusion-based 3D concrete printing using machine learning-based extrudate geometry control
Authors: Lao, Wenxin
Li, Mingyang
Wong, Teck Neng
Tan, Ming Jen
Tjahjowidodo, Tegoeh
Keywords: Engineering::Mechanical engineering
Issue Date: 2020
Source: Lao, W., Li, M., Wong, T. N., Tan, M. J. & Tjahjowidodo, T. (2020). Improving surface finish quality in extrusion-based 3D concrete printing using machine learning-based extrudate geometry control. Virtual and Physical Prototyping, 15(2), 178-193. https://dx.doi.org/10.1080/17452759.2020.1713580
Journal: Virtual and Physical Prototyping 
Abstract: 3D Concrete Printing (3DCP) has been gaining popularity in the past few years. Due to the nature of line-by-line printing and the slump of the material deposition in each extruded line, 3D printed structures exhibit obvious lines or marks at the layer interface, which affects surface finish quality and potentially affect bonding strength between layers. This makes it necessary to control the extrudate formation in 3DCP. However, it is difficult to directly analyse the extrudate formation process because the extrudate shape depends on many parameters. In this paper, a machine learning technique is applied to correlate the formation of the extrudate to the printing parameters using an Artificial Neural Network model. The training data for the model development was obtained from extrudates printed in 3DCP experiments. The performance of the trained model was experimentally validated and the predicted extrudate geometry resulting from the developed model showed good agreement to the actual extrudate geometry. Subsequently, the developed model was used to find proper nozzle shapes to produce designated extrudate geometries. Significant improvement on the printing quality was demonstrated using nozzle shapes generated from the model on 3D printed objects consisting a vertical wall, an inclined wall and a curved part.
URI: https://hdl.handle.net/10356/148291
ISSN: 1745-2767
DOI: 10.1080/17452759.2020.1713580
Rights: This is an Accepted Manuscript of an article published by Taylor & Francis in Virtual and Physical Prototyping on 5 Feb 2020, available online: http://www.tandfonline.com/10.1080/17452759.2020.1713580
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SC3DP Journal Articles

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