Development of Building Component Combination Algorithms for Generative Design-based DfMA Applications

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Abstract

The AEC industry faces challenges such as low productivity, high carbon emissions, labor shortages, and construction site accidents. To address these issues, the industry focuses on MMC and DfMA based on BIM. This research paper develops building component combination algorithms for generative design-based applications. Using GD, the proposed method optimises the layout and selection of building components while considering construction costs and a specified budget range. A case study of a five-component building system with four types of components demonstrates the method's ability to generate diverse design alternatives. Designers can efficiently explore and evaluate these alternatives based on economic and design criteria. However, the method has limitations, such as the exclusion of MEP facilities as GD parameters and the focus on optimising the budget as a single goal. Nevertheless, this study lays the foundation for applying DfMA in the early design stage and utilizing GD technology in construction projects.

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Hong, S. M., Kim, G., Gu, H., Kim, T., & Choo, S. (2023). Development of Building Component Combination Algorithms for Generative Design-based DfMA Applications. In Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe (Vol. 2, pp. 207–216). Education and research in Computer Aided Architectural Design in Europe. https://doi.org/10.52842/conf.ecaade.2023.2.207

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