https://doi.org/10.24928/2023/0243

Unleashing the Power of Chatgpt for Lean Construction: An Early Outlook

Makram Bou Hatoum1 & Hala Nassereddine2

1Ph.D. Candidate, Department of Civil Engineering, University of Kentucky, Lexington, KY, USA, [email protected], orcid.org/0000-0002-8824-3941.
2Assistant Professor, Department of Civil Engineering, University of Kentucky, Lexington, KY, USA, [email protected], orcid.org/0000-0001-7952-5034.

Abstract

Artificial Intelligence (AI) is one of the core technologies that was brought forward by the fourth industrial revolution. This technology is disrupting industries all around the globe, and the construction industry is no exception. Research targeting AI in construction has grown exponentially in the last decade as researchers investigate how to leverage AI across the project lifecycle. With the recent release of ChatGPT, AI research is expected to grow even more as the construction industry navigates this breakthrough and understands its impact. This paper focuses on AI in the context of Lean Construction and has two main objectives. First, the paper reviews the database for the International Group of Lean Construction (IGLC) to identify AI-related publications, summarize their findings, and detect the research trends. A total of nineteen papers were identified, presenting various theoretical and practical aspects of AI in Lean Construction. Second, the paper provides an early outlook into ChatGPT and experiments with its capabilities through three simple use cases that explore ChatGPT’s ability to educate and train on Lean aspects, perform conceptual analysis, and develop Lean applications. The early interaction with ChatGPT showed promising potential for the construction industry with encouraging results that can empower the Lean community.

Keywords

Lean Construction, Artificial Intelligence, ChatGPT, Construction 4.0.

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Reference

Hatoum, M. B. & Nassereddine, H. 2023. Unleashing the Power of Chatgpt for Lean Construction: An Early Outlook, Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31) , 208-219. doi.org/10.24928/2023/0243

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