×
Home Current Archive Editorial board About the Journal For Authors Editorial Policy Contact
Review paper

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

By
Milijana Živković ,
Milijana Živković
Maša Žujović ,
Maša Žujović
Jelena Milošević
Jelena Milošević

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

1.
Jimeng Y, Yi C, Weidong H, Yun L. Survey on artificial intelligence for additive manufacturing. 2017;1–6.
2.
Zeqing J, Zhizhou Z, Demir Kahraman G, Grace X. 2020;(5):1541–56.
3.
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.
4.
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.
5.
Engineering Research Journal. 2019;119–37.

Citation

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.