IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v197y2020ics0951832019306659.html
   My bibliography  Save this article

Data-driven safety enhancing strategies for risk networks in construction engineering

Author

Listed:
  • Chen, Fangyu
  • Wang, Hongwei
  • Xu, Gangyan
  • Ji, Hongchang
  • Ding, Shanlei
  • Wei, Yongchang

Abstract

Risk management is crucial and indispensable to the success of projects, while identifying critical risks is the fundamental step in devising the corresponding safety measures. To fully exploit the value of richly accumulated accidental cases, this paper presents a data-driven research framework for proposing effective safety enhancing strategies based on risk networks in construction engineering, spanning the whole process from extracting accident chains from accidents to construct a risk network to devising safety measures. Aiming at the weighted heterogeneity of the risk network, both the performance metrics at network level and critical-risk identification metrics at node level are deliberately designed. These metrics then enable the proposing of a series of safety-enhancing strategies. In the case study, based on the accident-related data in China’s bridge-and-tunnel hybrid projects, different safety-enhancing strategies are compared through simulation experiments and analyzed to verify their effectiveness on optimizing costs and improving safety. Finally, based on results from simulations, relevant managerial suggestions are proposed.

Suggested Citation

  • Chen, Fangyu & Wang, Hongwei & Xu, Gangyan & Ji, Hongchang & Ding, Shanlei & Wei, Yongchang, 2020. "Data-driven safety enhancing strategies for risk networks in construction engineering," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
  • Handle: RePEc:eee:reensy:v:197:y:2020:i:c:s0951832019306659
    DOI: 10.1016/j.ress.2020.106806
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832019306659
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2020.106806?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rao, Arjun H. & Marais, Karen, 2018. "High risk occurrence chains in helicopter accidents," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 83-98.
    2. You, Sangseok & Kim, Jeong-Hwan & Lee, SangHyun & Kamat, Vineet & Robert, Lionel, 2018. "Enhancing perceived safety in human–robot collaborative construction using immersive virtual environments," HEC Research Papers Series 1308, HEC Paris.
    3. Zhou, Ying & Li, Chenshuang & Zhou, Cheng & Luo, Hanbin, 2018. "Using Bayesian network for safety risk analysis of diaphragm wall deflection based on field data," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 152-167.
    4. Zhang, Limao & Wu, Xianguo & Skibniewski, Miroslaw J. & Zhong, Jingbing & Lu, Yujie, 2014. "Bayesian-network-based safety risk analysis in construction projects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 29-39.
    5. Sangseok You & Jeong-Hwan Kim & Sanghyun Lee & Vineet Kamat & Lionel Robert, 2018. "Enhancing Perceived Safety in Human–Robot Collaborative Construction Using Immersive Virtual Environments," Working Papers hal-02895952, HAL.
    6. Yongliang Deng & Liangliang Song & Zhipeng Zhou & Ping Liu, 2017. "An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network," Complexity, Hindawi, vol. 2017, pages 1-17, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fu, Lipeng & Wang, Xueqing & Zhao, Heng & Li, Mengnan, 2022. "Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    2. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    3. Usama Issa & Muwaffaq Alqurashi & Ibrahim Salama, 2021. "Qualitative Analysis of Risks Affecting the Delivery of Land Surveying Project Activities," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    4. Hai, Nan & Gong, Daqing & Liu, Shifeng & Dai, Zixuan, 2022. "Dynamic coupling risk assessment model of utility tunnels based on multimethod fusion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    5. Fatemeh Mostofi & Vedat Toğan & Yunus Emre Ayözen & Onur Behzat Tokdemir, 2022. "Construction Safety Risk Model with Construction Accident Network: A Graph Convolutional Network Approach," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    6. Lee, Junho & Kim, Ikjun & Kim, Hyomin & Kang, Juyoung, 2021. "SWOT-AHP analysis of the Korean satellite and space industry: Strategy recommendations for development," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    7. Ji, Chenyi & Su, Xing & Qin, Zhongfu & Nawaz, Ahsan, 2022. "Probability Analysis of Construction Risk based on Noisy-or Gate Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    8. Zhang, Hengqi & Geng, Hua, 2023. "A methodology to identify and assess high-risk causes for electrical personal accidents based on directed weighted CN," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    9. Wang, Ying & Zhang, Limao, 2021. "Simulation-based optimization for modeling and mitigating tunnel-induced damages," Reliability Engineering and System Safety, Elsevier, vol. 205(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Fan & Li, Heng & Dong, Chao & Ding, Lieyun, 2019. "Knowledge representation using non-parametric Bayesian networks for tunneling risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    2. Lin, Song-Shun & Shen, Shui-Long & Zhou, Annan & Xu, Ye-Shuang, 2021. "Novel model for risk identification during karst excavation," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    3. Shen, Shui-Long & Lin, Song-Shun & Zhou, Annan, 2023. "A cloud model-based approach for risk analysis of excavation system," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    4. Webster, Craig & Ivanov, Stanislav, 2021. "Tourists’ perceptions of robots in passenger transport," Technology in Society, Elsevier, vol. 67(C).
    5. Fu, Lipeng & Wang, Xueqing & Zhao, Heng & Li, Mengnan, 2022. "Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    6. Xiaoyan Jiang & Sai Wang & Jie Wang & Sainan Lyu & Martin Skitmore, 2020. "A Decision Method for Construction Safety Risk Management Based on Ontology and Improved CBR: Example of a Subway Project," IJERPH, MDPI, vol. 17(11), pages 1-23, June.
    7. Pan, Yue & Ou, Shenwei & Zhang, Limao & Zhang, Wenjing & Wu, Xianguo & Li, Heng, 2019. "Modeling risks in dependent systems: A Copula-Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 416-431.
    8. Wang, Lei & Liu, Qing & Dong, Shiyu & Guedes Soares, C., 2022. "Selection of countermeasure portfolio for shipping safety with consideration of investment risk aversion," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    9. Hieu T. T. L. Pham & Mahdi Rafieizonooz & SangUk Han & Dong-Eun Lee, 2021. "Current Status and Future Directions of Deep Learning Applications for Safety Management in Construction," Sustainability, MDPI, vol. 13(24), pages 1-37, December.
    10. Song, Haifeng & Liu, Jieyu & Schnieder, Eckehard, 2017. "Validation, verification and evaluation of a Train to Train Distance Measurement System by means of Colored Petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 10-23.
    11. Suo Qi & Wang Liyuan & Yao Tianzi & Wang Zihao, 2021. "Promoting Metro Operation Safety by Exploring Metro Operation Accident Network," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 455-468, August.
    12. Xue, Jie & Yip, Tsz Leung & Wu, Bing & Wu, Chaozhong & van Gelder, P.H.A.J.M., 2021. "A novel fuzzy Bayesian network-based MADM model for offshore wind turbine selection in busy waterways: An application to a case in China," Renewable Energy, Elsevier, vol. 172(C), pages 897-917.
    13. Liu, Wenli & Li, Ang & Fang, Weili & Love, Peter E.D. & Hartmann, Timo & Luo, Hanbin, 2023. "A hybrid data-driven model for geotechnical reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    14. Ali Namazian & Siamak Haji Yakhchali & Vahidreza Yousefi & Jolanta Tamošaitienė, 2019. "Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk," IJERPH, MDPI, vol. 16(24), pages 1-19, December.
    15. Guo, Qingjun & Amin, Shohel & Hao, Qianwen & Haas, Olivier, 2020. "Resilience assessment of safety system at subway construction sites applying analytic network process and extension cloud models," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    16. Zhang, Xiaoge & Mahadevan, Sankaran, 2021. "Bayesian network modeling of accident investigation reports for aviation safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    17. Zhou, Ying & Li, Chenshuang & Zhou, Cheng & Luo, Hanbin, 2018. "Using Bayesian network for safety risk analysis of diaphragm wall deflection based on field data," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 152-167.
    18. Rao, Arjun H. & Marais, Karen, 2020. "A state-based approach to modeling general aviation accidents," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    19. Vishnu Sivarudran Pillai & Kira Matus, 2019. "Regulation of AI Technologies in the Construction Industry," HKUST IEMS Working Paper Series 2019-65, HKUST Institute for Emerging Market Studies, revised May 2019.
    20. Alibeikloo, Mehrnaz & Khabbaz, Hadi & Fatahi, Behzad, 2022. "Random Field Reliability Analysis for Time-Dependent Behaviour of Soft Soils Considering Spatial Variability of Elastic Visco-Plastic Parameters," Reliability Engineering and System Safety, Elsevier, vol. 219(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:197:y:2020:i:c:s0951832019306659. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.