Share:


The application of BIM in the AECO industry

    Clyde Zhengdao Li Affiliation
    ; Yu Zhen Affiliation
    ; Hengqin Wu Affiliation
    ; Zhe Chen Affiliation
    ; Bing Xiao Affiliation
    ; Vivian W. Y. Tam Affiliation

Abstract

Building information Modeling (BIM) has been applied to the whole life cycle planning of construction projects, becoming the latest “engineering brain”. Currently, researches on BIM involve various stages, but most of the review fields are relatively single and lack of systematic review and analysis. In order to comprehensively analyze the research trend of BIM in the field of engineering management, this paper takes the holistic analysis method as the framework. In the first stage, 2066 research projects were quantitatively analyzed by bibliometrics to clarify their research environment. In the second stage, scientometric analysis method is adopted to identify scholars, countries, key words and journal sources that have achieved fruitful results and influence in BIM research, and to clarify the research environment. In the last stage, indepth qualitative discussion is carried out to achieve three objectives: (1) to divide the whole life cycle of the article and summarize the research hotspots in each stage; (2) identify BIM application problems; (3) determine the future research direction. This work is helpful for researchers and practitioners in this field to quickly find influential and fruitful research or journals, and to understand the current research hot spots and trends for the next research planning.

Keyword : building information modeling, life cycle management, categorisation, research trend, visualization

How to Cite
Li, C. Z., Zhen, Y., Wu, H., Chen, Z., Xiao, B., & Tam, V. W. Y. (2023). The application of BIM in the AECO industry. Journal of Civil Engineering and Management, 29(3), 202–222. https://doi.org/10.3846/jcem.2023.18076
Published in Issue
Feb 15, 2023
Abstract Views
1514
PDF Downloads
745
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Ahmad, Z., Thaheem, M. J., & Maqsoom, A. (2018). Building information modeling as a risk transformer: An evolutionary insight into the project uncertainty. Automation in Construction, 92, 103–119. https://doi.org/10.1016/j.autcon.2018.03.032

Ahmed, A. L., & Kassem, M. (2018). A unified BIM adoption taxonomy: Conceptual development, empirical validation and application. Automation in Construction, 96, 103–127. http://doi.org/10.1016/j.autcon.2018.08.017

Akanbi, L. A., Oyedele, L. O., Omoteso, K., Bilal, M., Akinade, O. O., Ajayi, A. O., Delgado, J. M. D., & Owolabi, H. A. (2019). Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy. Journal of Cleaner Production, 223, 386–396. http://doi.org/10.1016/j.jclepro.2019.03.172

Akin, S., Ergun, O., Surer, E., & Dino, I. G. (2022). An immersive performative architectural design tool with daylighting simulations: A building information modeling-based approach. Engineering, Construction and Architectural Management, 28(4), 1319–1344. http://doi.org/10.1108/ecam-07-2020-0562

Akinade, O. O., Oyedele, L. O., Bilal, M., Ajayi, S. O., Owolabi, H. A., Alaka, H. A., & Bello, S. A. (2015). Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS). Resources Conservation and Recycling, 105(A), 167–176. http://doi.org/10.1016/j.resconrec.2015.10.018

Arslan, M., Cruz, C., & Ginhac, D. (2019a). Semantic trajectory insights for worker safety in dynamic environments. Automation in Construction, 106, 102854. http://doi.org/10.1016/j.autcon.2019.102854

Arslan, M., Cruz, C., & Ginhac, D. (2019b). Visualizing intrusions in dynamic building environments for worker safety. Safety Science, 120, 428–446. http://doi.org/10.1016/j.ssci.2019.07.020

Azhar, S., Carlton, W. A., Olsen, D. & Ahmad, I. (2011). Building information modeling for sustainable design and LEED(R) rating analysis. Automation in Construction, 20(2SI), 217–224. http://doi.org/10.1016/j.autcon.2010.09.019

Bakchan, A., & Faust, K. M. (2019). Construction waste generation estimates of institutional building projects: Leveraging waste hauling tickets. Waste Management, 87, 301–312. http://doi.org/10.1016/j.wasman.2019.02.024

Banihashemi, S., Tabadkani, A., & Hosseini, M. R. (2018). Integration of parametric design into modular coordination: A construction waste reduction workflow. Automation in Construction, 88, 1–12. http://doi.org/10.1016/j.autcon.2017.12.026

Bilal, M., Oyedele, L. O., Akinade, O. O., Ajayi, S. O., Alaka, H. A., Owolabi, H. A., Qadir, J., Pasha, M., & Bello, S. A. (2016). Big data architecture for construction waste analytics (CWA): A conceptual framework. Journal of Building Engineering, 6, 144–156. http://doi.org/10.1016/j.jobe.2016.03.002

Boje, C., Guerriero, A., Kubicki, S., & Rezgui, Y. (2020). Towards a semantic Construction Digital Twin: Directions for future research. Automation in Construction, 114, 103179. http://doi.org/10.1016/j.autcon.2020.103179

Bortolini, R., Formoso, C. T., & Viana, D. D. (2019). Site logistics planning and control for engineer-to-order prefabricated building systems using BIM 4D modeling. Automation in Construction, 98, 248–264. http://doi.org/10.1016/j.autcon.2018.11.031

Braun, A., & Borrmann, A. (2019). Combining inverse photogrammetry and BIM for automated labeling of construction site images for machine learning. Automation in Construction, 106, 102879. http://doi.org/10.1016/j.autcon.2019.102879

Braun, A., Tuttas, S., Borrmann, A., & Stilla, U. (2020). Improving progress monitoring by fusing point clouds, semantic data and computer vision. Automation in Construction, 116, 103210. http://doi.org/10.1016/j.autcon.2020.103210

Cang, Y., Luo, Z. X., Yang, L., & Han, B. (2020). A new method for calculating the embodied carbon emissions from buildings in schematic design: Taking “building element” as basic unit. Building and Environment, 185, 107306. http://doi.org/10.1016/j.buildenv.2020.107306

Cerovsek, T. (2011). A review and outlook for a “Building Information Model” (BIM): A multi-standpoint framework for technological development. Advanced Engineering Informatics, 25(2), 224–244. http://doi.org/10.1016/j.aei.2010.06.003

Chen, X., Liu, C., & Wu, I. (2018). A BIM-based visualization and warning system for fire rescue. Advanced Engineering Informatics, 37, 42–53. http://doi.org/10.1016/j.aei.2018.04.015

Cheng, M., & Chang, N. (2019). Dynamic construction material layout planning optimization model by integrating 4D BIM. Engineering with Computers, 35(2), 703–720. http://doi.org/10.1007/s00366-018-0628-0

Cheng, J. C. P., Chen, W. W., Chen, K. Y., & Wang, Q. (2020). Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms. Automation in Construction, 112, 103087. http://doi.org/10.1016/j.autcon.2020.103087

Choe, S., & Leite, F. (2017). Construction safety planning: Site-specific temporal and spatial information integration. Automation in Construction, 84, 335–344. http://doi.org/10.1016/j.autcon.2017.09.007

Costa, G., & Sicilia, A. (2020). Alternatives for facilitating automatic transformation of BIM data using semantic query languages. Automation in Construction, 120, 103384. http://doi.org/10.1016/j.autcon.2020.103384

Ding, L., Jiang, W. G., Zhou, Y., Zhou, C., & Liu, S. (2020a). BIM-based task-level planning for robotic brick assembly through image-based 3D modeling. Advanced Engineering Informatics, 43, 100993. http://doi.org/10.1016/j.aei.2019.100993

Ding, Z., Liu, S., Luo, L. W., & Liao, L. H. (2020b). A building information modeling-based carbon emission measurement system for prefabricated residential buildings during the materialization phase. Journal of Cleaner Production, 264, 121728. http://doi.org/10.1016/j.jclepro.2020.121728

Ding, Z., Niu, J. D., Liu, S., Wu, H. Y., & Zuo, J. (2020c). An approach integrating geographic information system and building information modelling to assess the building health of commercial buildings. Journal of Cleaner Production, 257, 120532. http://doi.org/10.1016/j.jclepro.2020.120532

Doumbouya, L., Guan, C. S., Gao, G., & Pan, Y. (2017). Application of BIM technology in design and construction: A case study of pharmaceutical industrial base of amino acid building project. In L. Malinovska, & V. Osadcuks (Eds.), 16th International Scientific Conference on Engineering for Rural Development (pp. 1495–1502). Latvia University of Agriculture, Faculty of Engineering, Jelgava, Latvia. http://doi.org/10.22616/ERDev2017.16.N338

Dutta, S., Cai, Y. Y., Huang, L. H., & Zheng, J. M. (2020). Automatic re-planning of lifting paths for robotized tower cranes in dynamic BIM environments. Automation in Construction, 110, 102998. http://doi.org/10.1016/j.autcon.2019.102998

El Ammari, K., & Hammad, A. (2019). Remote interactive collaboration in facilities management using BIM-based mixed reality. Automation in Construction, 107, 102940. http://doi.org/10.1016/j.autcon.2019.102940

Eleftheriadis, S., Duffour, P., Stephenson, B., & Mumovic, D. (2018). Automated specification of steel reinforcement to support the optimisation of RC floors. Automation in Construction, 96, 366–377. http://doi.org/10.1016/j.autcon.2018.10.005

Fu, M., & Liu, R. (2020). BIM-based automated determination of exit sign direction for intelligent building sign systems. Automation in Construction, 120, 103353. http://doi.org/10.1016/j.autcon.2020.103353

Fu, M., Liu, R., Qi, B., & Issa, R. R. (2020). Generating straight skeleton-based navigation networks with Industry Foundation Classes for indoor way-finding. Automation in Construction, 112, 103057. http://doi.org/10.1016/j.autcon.2019.103057

Getuli, V., Capone, P., Bruttini, A., & Isaac, S. (2020). BIM-based immersive Virtual Reality for construction workspace planning: A safety-oriented approach. Automation in Construction, 114, 103160. http://doi.org/10.1016/j.autcon.2020.103160

Ghaffarianhoseini, A., Tookey, J., Ghaffarianhoseini, A., Naismith, N., Azhar, S., Efimova, O., & Raahemifar, K. (2017). Building Information Modelling (BIM) uptake: Clear benefits, understanding its implementation, risks and challenges. Renewable & Sustainable Energy Reviews, 75, 1046–1053. http://doi.org/10.1016/j.rser.2016.11.083

Guerra, B. C., Bakchan, A., Leite, F., & Faust, K. M. (2019). BIM-based automated construction waste estimation algorithms: The case of concrete and drywall waste streams. Waste Management, 87, 825–832. http://doi.org/10.1016/j.wasman.2019.03.010

Gui, N., Wang, C. H., Qiu, Z. F., Gui, W. H., & Deconinck, G. (2019). IFC-based partial data model retrieval for distributed collaborative design. Journal of Computing in Civil Engineering, 33(3), 040190163. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000829

Guo, J., Wang, Q., & Park, J. (2020). Geometric quality inspection of prefabricated MEP modules with 3D laser scanning. Automation in Construction, 111, 103053. http://doi.org/10.1016/j.autcon.2019.103053

Hamidavi, T., Abrishami, S., & Hosseini, M. R. (2020). Towards intelligent structural design of buildings: A BIM-based solution. Journal of Building Engineering, 32, 101685. http://doi.org/10.1016/j.jobe.2020.101685

Hollberg, A., Genova, G., & Habert, G. (2020). Evaluation of BIM-based LCA results for building design. Automation in Construction, 109, 102972. http://doi.org/10.1016/j.autcon.2019.102972

Hosny, A., Nik-Bakht, M., & Moselhi, O. (2020). Workspace planning in construction: Non-deterministic factors. Automation in Construction, 116, 103222. http://doi.org/10.1016/j.autcon.2020.103222

Jeon, J., Lee, J., & Ham, Y. (2019). Quantifying the impact of building envelope condition on energy use. Building Research and Information, 47(4), 404–420. http://doi.org/10.1080/09613218.2018.1448959

Kameli, M., Hosseinalipour, M., Sardroud, J. M., Ahmed, S. M., & Behruyan, M. (2021). Improving maintenance performance by developing an IFC BIM/RFID-based computer system. Journal of Ambient Intelligence and Humanized Computing, 12(2), 3055–3074. http://doi.org/10.1007/s12652-020-02464-3

Kang, T. (2020). BIM-Based Human Machine Interface (HMI) framework for energy management. Sustainability, 12(21), 886121. http://doi.org/10.3390/su12218861

Khalili-Araghi, S., & Kolarevic, B. (2016). Development of a framework for dimensional customization system: A novel method for customer participation. Journal of Building Engineering, 5, 231–238. http://doi.org/10.1016/j.jobe.2016.01.001

Khalili-Araghi, S., & Kolarevic, B. (2020). Variability and validity: Flexibility of a dimensional customization system. Automation in Construction, 109, 102970. http://doi.org/10.1016/j.autcon.2019.102970

Lawrence, M., Pottinger, R., Staub-French, S., & Nepal, M. P. (2014). Creating flexible mappings between Building Information Models and cost information. Automation in Construction, 45, 107–118. http://doi.org/10.1016/j.autcon.2014.05.006

Lee, Y., Solihin, W., & Eastman, C. M. (2019). The mechanism and challenges of validating a building information model regarding data exchange standards. Automation in Construction, 100, 118–128. http://doi.org/10.1016/j.autcon.2018.12.025

Lei, Y., Rao, Y. P., Wu, J. M., & Lin, C. S. (2020). BIM based cyber-physical systems for intelligent disaster prevention. Journal of Industrial Information Integration, 20, 100171. http://doi.org/10.1016/j.jii.2020.100171

Li, C. T., Cheng, J. C. P., & Chen, K. (2020). Top 10 technologies for indoor positioning on construction sites. Automation in Construction, 118, 103309. http://doi.org/10.1016/j.autcon.2020.103309

Lu, X., Yang, Z. B., Xu, Z., & Xiong, C. (2020). Scenario simulation of indoor post-earthquake fire rescue based on building information model and virtual reality. Advances in Engineering Software, 143, 102792. http://doi.org/10.1016/j.advengsoft.2020.102792

Lu, Y., Le, V. H., & Song, X. (2017). Beyond boundaries: A global use of life cycle inventories for construction materials. Journal of Cleaner Production, 156, 876–887. http://doi.org/10.1016/j.jclepro.2017.04.010

Lundeen, K. M., Kamat, V. R., Menassa, C. C., & McGee, W. (2017). Scene understanding for adaptive manipulation in robotized construction work. Automation in Construction, 82, 16–30. http://doi.org/10.1016/j.autcon.2017.06.022

Lundeen, K. M., Kamat, V. R., Menassa, C. C., & McGee, W. (2019). Autonomous motion planning and task execution in geometrically adaptive robotized construction work. Automation in Construction, 100, 24–45. http://doi.org/10.1016/j.autcon.2018.12.020

Ma, G., & Du, Q. (2020). Optimization on the intellectual monitoring system for structures based on acoustic emission and data mining. Measurement, 163, 107937. http://doi.org/10.1016/j.measurement.2020.107937

Ma, G., & Wu, Z. (2020). BIM-based building fire emergency management: Combining building users’ behavior decisions. Automation in Construction, 109, 102975. http://doi.org/10.1016/j.autcon.2019.102975

Ma, Z., Cai, S. Y., Mao, N., Yang, Q. L., Feng, J. G., & Wang, P. Y. (2018). Construction quality management based on a collaborative system using BIM and indoor positioning. Automation in Construction, 92, 35–45. http://doi.org/10.1016/j.autcon.2018.03.027

Ma, Z., Ren, Y., Xiang, X. L., & Turk, Z. (2020). Data-driven decision-making for equipment maintenance. Automation in Construction, 112, 103103. http://doi.org/10.1016/j.autcon.2020.103103

Ma, Z., Wei, Z., & Zhang, X. (2013). Semi-automatic and specification-compliant cost estimation for tendering of building projects based on IFC data of design model. Automation in Construction, 30, 126–135. http://doi.org/10.1016/j.autcon.2012.11.020

Marmo, R., Polverino, F., Nicolella, M., & Tibaut, A. (2020). Building performance and maintenance information model based on IFC schema. Automation in Construction, 118, 103275. http://doi.org/10.1016/j.autcon.2020.103275

Marzouk, M., & Al Daour, I. (2018). Planning labor evacuation for construction sites using BIM and agent-based simulation. Safety Science, 109, 174–185. http://doi.org/10.1016/j.ssci.2018.04.023

Marzouk, M., Azab, S., & Metawie, M. (2018). BIM-based approach for optimizing life cycle costs of sustainable buildings. Journal of Cleaner Production, 188, 217–226. http://doi.org/10.1016/j.jclepro.2018.03.280

Miettinen, R., & Paavola, S. (2014). Beyond the BIM utopia: Approaches to the development and implementation of building information modeling. Automation in Construction, 43, 84–91. http://doi.org/10.1016/j.autcon.2014.03.009

Olawumi, T. O., & Chan, D. W. M. (2019). Building information modelling and project information management framework for construction projects. Journal of Civil Engineering and Management, 25(1), 53–75. http://doi.org/10.3846/jcem.2019.7841

Patacas, J., Dawood, N., & Kassem, M. (2020). BIM for facilities management: A framework and a common data environment using open standards. Automation in Construction, 120, 103366. http://doi.org/10.1016/j.autcon.2020.103366

Rebolj, D., Pucko, Z., Babic, N. C., Bizjak, M., & Mongus, D. (2017). Point cloud quality requirements for Scan-vs-SIM based automated construction progress monitoring. Automation in Construction, 84, 323–334. http://doi.org/10.1016/j.autcon.2017.09.021

Rehman, A., Hussain, M, Farooq, A, & Akram, M. (2019). Consensus-based multi-person decision making with incomplete fuzzy preference relations using product transitivity. Mathematics, 7(2), 185. https://doi.org/10.3390/math7020185

Rezaei, F., Bulle, C., & Lesage, P. (2019). Integrating building information modeling and life cycle assessment in the early and detailed building design stages. Building and Environment, 153, 158–167. http://doi.org/10.1016/j.buildenv.2019.01.034

Santos, R., Costa, A. A., & Grilo, A. (2017). Bibliometric analysis and review of Building Information Modelling literature published between 2005 and 2015. Automation in Construction, 80, 118–136. http://doi.org/10.1016/j.autcon.2017.03.005

Santos, R., Costa, A. A., Silvestre, J. D., & Pyl, L. (2020). Development of a BIM-based environmental and economic life cycle assessment tool. Journal of Cleaner Production, 265, 121705. https://doi.org/10.1016/j.jclepro.2020.121705

Sibenik, G., & Kovacic, I. (2020). Assessment of model-based data exchange between architectural design and structural analysis. Journal of Building Engineering, 32, 101589. http://doi.org/10.1016/j.jobe.2020.101589

Sidani, A., Dinis, F. M., Sanhudo, L., Duarte, J., Baptista, J. S., Martins, J. P., & Soeiro, A. (2021). Recent tools and techniques of BIM-based virtual reality: A systematic review. Archives of Computational Methods in Engineering, 28(2), 449–462. http://doi.org/10.1007/s11831-019-09386-0

Succar, B., & Poirier, E. (2020). Lifecycle information transformation and exchange for delivering and managing digital and physical assets. Automation in Construction, 112, 103090. http://doi.org/10.1016/j.autcon.2020.103090

Vigneault, M., Boton, C., Chong, H. Y., & Cooper-Cooke, B. (2020). An innovative framework of 5D BIM solutions for construction cost management: A systematic review. Archives of Computational Methods in Engineering, 27(4), 1013–1030. http://doi.org/10.1007/s11831-019-09341-z

Wei, Y., & Akinci, B. (2019). A vision and learning-based indoor localization and semantic mapping framework for facility operations and management. Automation in Construction, 107, 102915. http://doi.org/10.1016/j.autcon.2019.102915

Won, J., Czerniawski, T., & Leite, F. (2020). Semantic segmentation of point clouds of building interiors with deep learning: Augmenting training datasets with synthetic BIM-based point clouds. Automation in Construction, 113, 103144. http://doi.org/10.1016/j.autcon.2020.103144

Xu, J., Shi, Y., Xie, Y. C., & Zhao, S. W. (2019). A BIM-based construction and demolition waste information management system for greenhouse gas quantification and reduction. Journal of Cleaner Production, 229, 308–324. http://doi.org/10.1016/j.jclepro.2019.04.158

Xu, Z., Zhang, Z. C., Lu, X. Z., Zeng, X., & Guan, H. (2018). Post-earthquake fire simulation considering overall seismic damage of sprinkler systems based on BIM and FEMA P-58. Automation in Construction, 90, 9–22. http://doi.org/10.1016/j.autcon.2018.02.015

Xue, F., & Lu, W. (2020). A semantic differential transaction approach to minimizing information redundancy for BIM and blockchain integration. Automation in Construction, 118, 103270. http://doi.org/10.1016/j.autcon.2020.103270

Yuan, Z., Sun, C., & Wang, Y. (2018). Design for manufacture and assembly-oriented parametric design of prefabricated buildings. Automation in Construction, 88, 13–22. http://doi.org/10.1016/j.autcon.2017.12.021

Zhang, L., & Dong, L. (2019). Application sudy on Building Information Model (BIM) standardization of Chinese engineering breakdown structure (EBS) coding in life cycle management processes. Advances in Civil Engineering, 2019, 1581036. http://doi.org/10.1155/2019/1581036

Zhang, Z., Cheng, X. J., Yang, B. L., & Yang, D. (2020). Exploration of indoor barrier-free plane intelligent lofting system combining BIM and multi-sensors. Remote Sensing, 12(20), 3306. http://doi.org/10.3390/rs12203306

Zhao, X. (2017). A scientometric review of global BIM research: Analysis and visualization. Automation in Construction, 80, 37–47. https://doi.org/10.1016/j.autcon.2017.04.002

Zhou, X., Xie, Q. S., Guo, M. Z., Zhao, J. C., & Wang, J. (2020). Accurate and efficient indoor pathfinding based on building information modeling data. IEEE Transactions on Industrial Informatics, 16(12), 7459–7468. https://doi.org/10.1109/TII.2020.2974252

Zhou, X., Zhao, J. C., Wang, J., Su, D. D., Zhang, H. Y., Guo, M., Guo, M. Z., & Li, Z. (2019). OutDet: An algorithm for extracting the outer surfaces of building information models for integration with geographic information systems. International Journal of Geographical Information Science, 33(7), 1444–1470. http://doi.org/10.1080/13658816.2019.1572894

Zhu, J., Wang, X. Y., Chen, M. C., Wu, P., & Kim, M. J. (2019). Integration of BIM and GIS: IFC geometry transformation to shapefile using enhanced open-source approach. Automation in Construction, 106, 102859. http://doi.org/10.1016/j.autcon.2019.102859