A structured Prompt Engineering Framework for Modular Construction Design Using Generative AI
Document Type
Conference Proceeding
Publication Date
1-1-2026
Abstract
The modular construction industry requires early and tightly coupled reasoning across spatial layout, structural systems, module interfaces, and building services under fabrication, transportation, and assembly constraints. With recent advances in generative artificial intelligence (AI) and the emergence of large language models (LLMs), there is growing interest in leveraging these technologies to support design reasoning through natural language interaction. However, existing studies lack domain-specific methodologies that systematically translate modular design reasoning into effective prompts for generative AI systems. This study addresses this gap by introducing a reasoning-oriented taxonomy of modular construction design tasks and a structured prompt engineering framework tailored to modular design contexts. The proposed framework formalizes prompt construction through standardized blocks and demonstrates its application using representative prompts grounded in a modular residential case study. The proposed framework provides a methodological foundation for reasoning-aware human-AI interaction in early-stage modular construction design.
Publication Title
Proceedings of the International Symposium on Automation and Robotics in Construction
ISBN
[9780645832235]
Recommended Citation
Alwashah, Z.,
Xiao, B.,
Liu, H.,
Shao, X.,
&
Wang, X.
(2026).
A structured Prompt Engineering Framework for Modular Construction Design Using Generative AI.
Proceedings of the International Symposium on Automation and Robotics in Construction, 2110-2117.
http://doi.org/10.22260/ISARC2026/0269
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p2/2929