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Abdalazeem, M E, Hassan, H, Asawa, T and Mahmoud, H (2024) Green roofs and thermal comfort: a comparative study of soil layers’ seasonal thermal performance integrated with ventilation in hot climate. Architectural Engineering and Design Management, 20(02), 358–89.
Altay, B and Salcı, E (2024) Exploring designers’ finishing materials selection for residential interior spaces. Architectural Engineering and Design Management, 20(02), 269–86.
Aslay, S E and Dede, T (2024) Reduce the construction cost of a 7-story RC public building with metaheuristic algorithms. Architectural Engineering and Design Management, 20(02), 214–29.
EL-Mahdy, D and Ali, M (2024) Assessing the solar radiation performance of self-shaded 3D-printed clay-based façades. Architectural Engineering and Design Management, 20(02), 249–68.
Fan, C (2024) Using convolutional neural networks to identify illegal roofs from unmanned aerial vehicle images. Architectural Engineering and Design Management, 20(02), 390–410.
Gokyigit Arpaci, E Y, Eksi Akbulut, D and Yildiz, O (2024) Enhancing water resistance of earthen buildings by using admixture materials. Architectural Engineering and Design Management, 20(02), 320–36.
Pérez-Valcárcel, J, Aragón, J, Muñiz, S, Freire-Tellado, M and Mosquera, E (2024) Transportable temporary homes with folding roof. Architectural Engineering and Design Management, 20(02), 337–57.
Ren, S, Qiang, G, Tang, S, Zhang, C, Seo, H and Wu, K (2024) An automatic design-feedback process for structural prefabricated components quantity take-off calculation using BIM. Architectural Engineering and Design Management, 20(02), 287–302.
Sohani, H, Hosseini Nourzad, S H and Saghatforoush, E (2024) The optimized form of building made from the reused elements. Architectural Engineering and Design Management, 20(02), 191–213.
Wang, C, Gao, F, Cui, B, Huang, M M, Wu, M, Mao, L and Zheng, A (2024) Geometric quality assessment of precast concrete (PC) elements based on 3D structural light scanning. Architectural Engineering and Design Management, 20(02), 303–19.
Yuan, Z, Wang, H, Yang, Y, Yi, C, Huang, D and Yu, D (2024) Improving the construction accuracy of precast components in prefabricated buildings by analyzing relevant factors from the perspective of supply chain: a system dynamics model. Architectural Engineering and Design Management, 20(02), 230–48.
- Type: Journal Article
- Keywords: Prefabricated building; precast component; construction accuracy; system dynamics; supply chain;
- ISBN/ISSN: 1745-2007
- URL: https://doi.org/10.1080/17452007.2023.2286303
- Abstract:
The construction accuracy of precast components in prefabricated buildings has received sufficient attention in the context of the high-quality development of the construction industry. However, various unknown factors in the production, transportation, and installation stages lead to significant deviations in construction, and have not been systematically identified and dynamically analyzed in previous studies. This study aims to improve the construction accuracy of precast components by unlocking the causal relationships among these factors and revealing top-sensitive factors among them. Thus, based on the theory of system dynamics (SD), an SD model is established from the perspective of a supply chain consisting of the production, transportation, and installation stages. The 14 factors and their causal relationships involved in the SD model are identified through literature review and expert consultation methods. The sensitivity analysis method based on dynamic simulation is adopted to analyze the data output from the SD model. Finally, a real prefabricated building project is used for demonstrating and validating this SD model. The significant findings indicate that the installation stage is the most critical stage affecting the construction accuracy of precast components, and the precision of cast-in-situ structure is the most sensitive factor. The formwork system of cast-in-situ structure and construction personnel quality are the root causes of the precision of cast-in-situ structure. The suggestions corresponding to these findings are made. These findings and suggestions can facilitate general contractors in allocating relevant resources to more critical factors for efficiently improving the construction accuracy of precast components.