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A Design for Safety (DFS) Framework for Automated Inspection Risks in Metro Stations by Integrating a Knowledge Base and Building Information Modeling

Author

Listed:
  • Ping Liu

    (School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

  • Yongtao Shang

    (School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

  • Lei Zhang

    (Smart City Research Center, Nanjing Tech University, Nanjing 210096, China)

Abstract

Safety issues have always been of great concern to the metro construction industry. Numerous studies have shown that safety issues are closely related to the design phase. Many safety problems can be solved or improved by developing the design. This study proposes a structured identification method for safety risks based on the metro design specifications, journal literature, and expert experience. A safety knowledge base (KB) for the design was established to realize safety knowledge sharing and reusing. The KB has been developed into Building Information Modeling (BIM) software as an inspection plug-in to achieve automated analysis and retrieval of safety risks. The designers are provided with a visualization of risk components to locate and improve the pre-control measures of the design. Subsequently, the process of design for safety (DFS) database creation was demonstrated with a metro station project, and the feasibility of applying the KB to safety checking in BIM was verified. In response to the inspection results, safety risks in the construction phases can be eliminated or avoided by standardizing and improving the design.

Suggested Citation

  • Ping Liu & Yongtao Shang & Lei Zhang, 2023. "A Design for Safety (DFS) Framework for Automated Inspection Risks in Metro Stations by Integrating a Knowledge Base and Building Information Modeling," IJERPH, MDPI, vol. 20(6), pages 1-19, March.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:6:p:4765-:d:1091003
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    References listed on IDEAS

    as
    1. Ping Liu & Qiming Li & Jing Bian & Liangliang Song & Xiaer Xiahou, 2018. "Using Interpretative Structural Modeling to Identify Critical Success Factors for Safety Management in Subway Construction: A China Study," IJERPH, MDPI, vol. 15(7), pages 1-18, June.
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