BIM-Based Integrated Management System for Intelligent Timber Structure Construction Factories: Production Optimization and Carbon Emission Monitoring

Long Zhang; Guowen Zhang; Wentao Qiao; Yiqiang Li; Qingqing Xiong

doi:10.6919/ICJE.202609_12(9).0019

Authors

Long Zhang Hebei University of Engineering Science, Shijiazhuang 050091, China;School of Civil Engineering, Shi Jiazhuang Tiedao University, Shijiazhuang 050043, China
Guowen Zhang School of Civil Engineering, Shi Jiazhuang Tiedao University, Shijiazhuang 050043, China
Wentao Qiao School of Civil Engineering, Shi Jiazhuang Tiedao University, Shijiazhuang 050043, China;Key Laboratory of Roads and Railway Engineering Safety Control (Shijiazhuang Tiedao University), Ministry of Education, Shijiazhuang, Hebei 050043, China
Yiqiang Li Hebei University of Engineering Science, Shijiazhuang 050091, China
Qingqing Xiong School of Civil Engineering, Shi Jiazhuang Tiedao University, Shijiazhuang 050043, China

DOI:

https://doi.org/10.6919/ICJE.202609_12(9).0019

Keywords:

Intelligent Timber Construction; Building Information Modeling; Carbon Footprint Tracking; Factory Management System.

Abstract

Driven by the carbon peaking and carbon neutrality goals, the construction industry is facing an increasingly urgent demand for low-carbon transformation. As a major form of green building, timber structures require improved digital collaboration in production and more refined carbon emission management. To address this issue, this study proposes a novel integrated management system for the intelligent management of smart timber construction factories. The system develops a BIM-driven production and fabrication mode, constructs an integrated management architecture combining refined production management and carbon emission monitoring, and establishes a corresponding management platform. The platform enables full-process digital closed-loop management from raw material procurement to finished-product shipment, as well as full-chain carbon emission quantification. A practical application in a prefabrication factory demonstrates the feasibility, effectiveness, and engineering applicability of the proposed method and system.

Downloads

Download data is not yet available.

References

[1] IPCC. (2022). Climate change 2022: Impacts, adaptation and vulnerability. Cambridge University Press.

[2] Ramage, H. M., Burridge, H., Busse-Wicher, M., et al. (2017). The wood from the trees: The use of timber in construction. Renewable and Sustainable Energy Reviews, 68, 333–359.

[3] Gong, X., Nie, Z., Wang, Z., et al. (2012). Life cycle energy consumption and carbon dioxide emission of residential building designs in Beijing. Journal of Industrial Ecology, 16(4), 576–587.

[4] Tollefson, J. (2017). The wooden skyscrapers that could help to cool the planet. Nature, 545(7654), 280–282.

[5] Macinnis-Ng, C., Wyse, V. S., Webb, T., et al. (2017). Sustained carbon uptake in a mixed age southern conifer forest. Trees, 31(3), 967–980.

[6] He, M., Li, Z., Lam, F., et al. (2014). Experimental investigation on lateral performance of timber-steel hybrid shear wall systems. Journal of Structural Engineering, 140(6), 04014029.

[7] Hao, D., Xiamin, H., Zhong, X., et al. (2021). Experimental and analytical investigation on fire resistance of glulam-concrete composite beams. Journal of Building Engineering, 44.

[8] Hao, D., Xiamin, H., Guohui, H., et al. (2021). Experimental and analytical investigation on flexural behaviour of glulam-concrete composite beams with interlayer. Journal of Building Engineering, 38.

[9] Lamothe, S., Sorelli, L., Blanchet, P., et al. (2020). Engineering ductile notch connections for composite floors made of laminated timber and high or ultra-high performance fiber reinforced concrete. Engineering Structures, 211, 110415.

[10] Opgenorth, N., Locatelli, N. D., Leder, S., et al. (2024). Multi-scalar robotic fabrication system for on-site press gluing in multi-storey timber buildings. Automation in Construction, 168, 105774.

[11] Jakob, H. W., Martin, A., Ondrej, K., et al. (2020). Flexible and transportable robotic timber construction platform – TIM. Automation in Construction, 120, 103400.

[12] Regina, P. A. L., Elisabeth, B., Tim, S., et al. (2023). Automated on-site assembly of timber buildings on the example of a biomimetic shell. Automation in Construction, 156.

[13] Mikael, E., Dahniel, J., & David, S. (2021). AI-Based quality control of wood surfaces with autonomous material handling. Applied Sciences, 11(21), 9965.

[14] Babič, Č. N., Podbreznik, P., & Rebolj, D. (2009). Integrating resource production and construction using BIM. Automation in Construction, 19(5), 539–543.

[15] Abanda, F., Tah, J., & Cheung, F. (2017). BIM in off-site manufacturing for buildings. Journal of Building Engineering, 14, 89–102.

[16] Yin, X., Liu, H., Chen, Y., et al. (2019). Building information modelling for off-site construction: Review and future directions. Automation in Construction, 101, 72–91.

[17] Li, X., Shen, Q. G., Wu, P., et al. (2019). Integrating Building Information Modeling and Prefabrication Housing Production. Automation in Construction, 100, 46–60.

[18] Martinez, E. V., Pablo, M., & Rafiq, A. (2024). Target-path planning and manufacturability check for robotic CLT machining operations from BIM information. Automation in Construction, 158.

[19] Jang, S., & Lee, G. (2018). Process, productivity, and economic analyses of BIM–based multi-trade prefabrication-A case study. Automation in Construction, 89, 86–98.

[20] Wang, S., Wan, J., Zhang, D., et al. (2016). Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Computer Networks, 101, 158–168.

[21] Coronado, U. D. P., Lynn, R., Louhichi, W., et al. (2018). Part data integration in the Shop Floor Digital Twin: Mobile and cloud technologies to enable a manufacturing execution system. Journal of Manufacturing Systems, 48, 25–33.

[22] Zhang, H., Qing, Q., & Tao, F. (2022). A multi-scale modeling method for digital twin shop-floor. Journal of Manufacturing Systems, 62, 417–428.

[23] Zhang, M., Tao, F., & Nee, A. (2020). Digital twin enhanced dynamic job-shop scheduling. Journal of Manufacturing Systems.

[24] Fan, Y., Yang, J., Chen, J., et al. (2021). A digital-twin visualized architecture for Flexible Manufacturing System. Journal of Manufacturing Systems, 60, 176–201.

[25] Guo, D., Zhong, Y. R., Lin, P., et al. (2020). Digital twin-enabled Graduation Intelligent Manufacturing System for fixed-position assembly islands. Robotics and Computer-Integrated Manufacturing, 63, 101917.

[26] Guo, W., Li, Y., Tang, D., et al. (2022). Using real-time manufacturing data to schedule a smart factory via reinforcement learning. Computers & Industrial Engineering, 171.

[27] Ding, Z., Liu, S., Luo, L., et al. (2020). A building information modeling-based carbon emission measurement system for prefabricated residential buildings during the materialization phase. Journal of Cleaner Production, 264.

[28] Tao, X., Mao, C., Xie, F., et al. (2018). Greenhouse gas emission monitoring system for manufacturing prefabricated components. Automation in Construction, 93, 361–374.

[29] Liu, G., Chen, R., Xu, P., et al. (2020). Real-time carbon emission monitoring in prefabricated construction. Automation in Construction, 110, 102945.

[30] Xu, J., Teng, Y., Pan, W., et al. (2022). BIM-integrated LCA to automate embodied carbon assessment of prefabricated buildings. Journal of Cleaner Production, 374.

[31] Xu, J., Zhang, Q., Teng, Y., et al. (2023). Integrating IoT and BIM for tracking and visualising embodied carbon of prefabricated buildings. Building and Environment, 242, 110492.

[32] Wang, X., Truijens, M., Hou, L., et al. (2014). Integrating Augmented Reality with Building Information Modeling: Onsite construction process controlling for liquefied natural gas industry. Automation in Construction, 40, 96–105.

[33] GB/T 51366-2019. (2019). Standard for building carbon emission calculation. China Architecture & Building Press.