INTELLIGENT TOOLS FOR LARGE-SCALE 3D PRINTING: A SCOPING REVIEW

Milijana Živković; Maša Žujović; Jelena Milošević

doi:10.62683/zrgaf38.88-99

Review paper

Published: 25.12.2023.

<< Prev | Next >>

PDF

https://doi.org/10.62683/zrgaf38.88-99

INTELLIGENT TOOLS FOR LARGE-SCALE 3D PRINTING: A SCOPING REVIEW

Abstract

In recent decades, building methods such as 3D printing have been increasingly researched for the design and fabrication of various architectural elements. Artificial Intelligence is another rapidly developing technology whose potential in the buildingindustry is continuously being explored. This paper’s objective lies in mapping out the field of existing Artificial Intelligence tools for large-scale 3D printing, searching for possible applications throughout the different development stages including the prefabrication phase with structural design, optimization, behavior simulations, and predictions, as well as the production phase through the real-time monitoring of the process. In this study, different types of Artificial Intelligence (such as machine learning, deep learning, and computer vision), have been identified regarding their role in 3D printing to assess its potentials, limitations, and the present research gaps. Finally, potential research directions and emerging topics are presented. The study's findings increase the understanding of Artificial Intelligence techniques and applications in the 3D printing process and can aid in choosing and implementing the most promising ones in further research.

References

Jimeng Y, Yi C, Weidong H, Yun L. Survey on artificial intelligence for additive manufacturing. 2017;1–6.

Zeqing J, Zhizhou Z, Demir Kahraman G, Grace X. 2020;(5):1541–56.

Joost K, Boers N, Egbert, Walter K, Van Der Putten A, Peter P, et al. Artificial Intelligence: Definitions, Trends, Techniques, and Cases. An Insight into the Encyclopedia of Life Support Systems. 2002;1095–107.

Amos D, Albert C, P, Michael A, Edwards David A, Hosseini J, et al. Artificial intelligence in the AEC industry: Scientometric analysis and visualization of research activities. Automation in Construction. 2020;103081.

Engineering Research Journal. 2019;119–37.

Citation

Copyright

Articles are published under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). This licence allows anyone to copy, redistribute, remix, transform and build upon the material in any medium or format, for any purpose, including commercially, provided that appropriate credit is given to the original authors and source, a link to the licence is provided, and any changes made are indicated.