https://doi.org/10.24928/2023/0236

Using Low-Code and Artificial Intelligence to Support Continuous Improvement in the Construction Industry

Eder Martinez¹ & Diego Cisterna²

¹Professor, School of Architecture, Civil Engineering and Geomatics, University of Applied Sciences and Arts Northwestern Switzerland (FHNW), Hofackerstrasse 30, 4132 Muttenz, Switzerland, [email protected], orcid.org/0000-0001-7918-9421
²Research Fellow. Karlsruhe Institute of Technology (KIT), Institute of Technology and Management in Construction, 76131 Karlsruhe, Germany, [email protected], orcid.org/0000-0003-4282-1141

Abstract

Low-code is a new technology paradigm used to support digitalization in different industries. Nevertheless, there are no studies analyzing the implications of this technology in the construction industry context. Through action research, this paper explores the potential of lowcode to support continuous improvement of construction processes. The authors present the development and implementation of a low-code/artificial intelligence (AI)-based solution to automate data processing from paper delivery notes on-site. The as-is process was measured and compared against the low-code/AI powered process to verify efficiency gains. The development process of the digital solution was also analyzed to derive the findings of the study. The implementation of the digital solution resulted in 78% process time savings. The study also reveals the importance of involving people closer to operations in the development process, which resulted in efficient elicitation of requirements and the delivery of a solution meeting the needs of the end users. This paper highlights the potential of low-code productive development practices to support the digitalization in the construction industry. It also enlightens areas for further research and encourages the development of additional case studies to provide evidence of the benefits and limitations of using low-code to support continuous improvement in the construction industry.

Keywords

Low-code, no-code, artificial intelligence, lean construction, continuous improvement

Files

Reference

Martinez, E. & Cisterna, D. 2023. Using Low-Code and Artificial Intelligence to Support Continuous Improvement in the Construction Industry , Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31) , 197-207. doi.org/10.24928/2023/0236

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