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On Risk Probability of Prefabricated Building Hoisting Construction Based on Multiple Correlations

Author

Listed:
  • Peng Wan

    (Engineering Management, School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China
    These authors contributed equally to this work.)

  • Junwu Wang

    (Engineering Management, School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China
    These authors contributed equally to this work.)

  • Ye Liu

    (Engineering Management, School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China)

  • Qizhi Lu

    (Engineering Management, School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China)

  • Chunbao Yuan

    (China Construction Seventh Engineering Division Corp. Ltd., Shenzhen 518000, China)

Abstract

With growing concern about environmental pollution and occupational safety in construction industry globally, prefabricated building has become a popular building model in sustainable society. In China, management specifications of prefabricated buildings are far from mature, and safety accidents occur frequently in construction. In order to comprehensively analyze risks in hoisting construction of prefabricated buildings, this study, in view of characteristics of hoisting construction process and correlations in complex system, summarizes risk factors and classifies them according to Wuli-Shili-Renli (WSR) system. From perspective of multiple correlations, evolution mechanism of multi-system correlation and multi-risk correlation is carried out, so as to explore risk probability of hoisting construction of prefabricated buildings. At the same time, this study extends Two Additive Choquet Integral (TACI) operator and Decision-making Trial and Evaluation Laboratory (DEMATEL) in dynamic stochastic environment to construct a two-stage model for risk probability research of hoisting construction, hoping to profoundly reveal influence of risk factors and their dynamic evolution. The results show that: (1) risk probability presented a seasonal, dynamic change trend, which meant rising first, then falling, and finally keeping rising, thus regular inspection and dynamic monitoring are required in hoisting construction in these regions in the first three quarters. (2) the influence of each risk factor demonstrated dynamic changes, and risk sources that need to prevent and defuse at different time points are varied, thus targeted measures catering to different risk sources are required. (3) the degree of risk controllability is in dynamic change, but classification of cause or result in the region at the period remains the same, thus necessitating targeted response measures aimed at various risk types. (4) Individual risks like hoisting job climated break out periodically, so the law of risk occurrence should be mastered and relative precautionary measures should be taken in advance.

Suggested Citation

  • Peng Wan & Junwu Wang & Ye Liu & Qizhi Lu & Chunbao Yuan, 2022. "On Risk Probability of Prefabricated Building Hoisting Construction Based on Multiple Correlations," Sustainability, MDPI, vol. 14(8), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4430-:d:789474
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    References listed on IDEAS

    as
    1. Terje Aven, 2018. "An Emerging New Risk Analysis Science: Foundations and Implications," Risk Analysis, John Wiley & Sons, vol. 38(5), pages 876-888, May.
    2. Jinjia Zhang & Kaili Xu & Greg You & Beibei Wang & Lei Zhao, 2019. "Causation Analysis of Risk Coupling of Gas Explosion Accident in Chinese Underground Coal Mines," Risk Analysis, John Wiley & Sons, vol. 39(7), pages 1634-1646, July.
    3. Zuo, Jian & Pullen, Stephen & Rameezdeen, Raufdeen & Bennetts, Helen & Wang, Yuan & Mao, Guozhu & Zhou, Zhihua & Du, Huibin & Duan, Huabo, 2017. "Green building evaluation from a life-cycle perspective in Australia: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 358-368.
    4. Hernandez-Fajardo, Isaac & Dueñas-Osorio, Leonardo, 2013. "Probabilistic study of cascading failures in complex interdependent lifeline systems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 260-272.
    5. Yelda Ayrim & Kumru Didem Atalay & Gülin Feryal Can, 2018. "A New Stochastic MCDM Approach Based on COPRAS," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 857-882, May.
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