International conference on construction engineering and project management (국제학술발표논문집)

  • 2024.07a
  • /
  • Pages.550-557
  • /
  • 2024
  • /
  • 2508-9048(eISSN)
Korea Institute of Construction Engineering and Management (한국건설관리학회)
권호 표지
DOI QR코드

DOI QR Code

IFC Data Schema Extension for Railway Track Facility Management

  • Zeru Liu (Department of Architecture and Civil Engineering, City University of Hong Kong) ;
  • Wuhao Huang (Department of Architecture and Civil Engineering, City University of Hong Kong) ;
  • Hejun Xu (Department of Architecture and Civil Engineering, City University of Hong Kong) ;
  • Sining Li (Department of Architecture and Civil Engineering, City University of Hong Kong) ;
  • Jung In Kim (Department of Architecture and Civil Engineering, City University of Hong Kong)
  • Published : 2024.07.29
Download PDF
⟨ Previous Next ⟩

Abstract

Railway track facility management (FM) is an intricate and multifaceted discipline that necessitates precise data management and scheduling for ensuring the safety and efficiency of railway operations. Although the Industry Foundation Classes (IFC) version 4.3 has incorporated railway infrastructure into its data schema, it still falls short in catering to the specialized needs of track FM. This paper presents an exhaustive extension to the IFC schema, specifically designed to address the challenges and complexities inherent in railway track FM. A two-step approach was employed in the development of this extension. The initial phase involves the development of a Unified Modeling Language (UML)-based conceptual model, encapsulating four pivotal elements: "component" for track asset and condition identification, "action" for the related tasks during track FM, "resource" for required materials and equipment as well as involved actors, and "operation" for track operation information capturing. This conceptual model serves as an intricate blueprint, offering a comprehensive structure for various FM facets. Thus, the proposed IFC extension is developed and aligned consistently with the conceptual model, forming an integrated, interoperable data management framework that can be easily adapted into the openBIM environment. The efficacy and applicability of the proposed extension are substantiated through real-world case studies, thereby demonstrating its capability to significantly enhance data visualization, interoperability, and overall decision-making in railway track FM.

Keywords

Acknowledgement

The support of the General Research Fund of the University Grants Committee of Hong Kong (#11216422) and City University of Hong Kong (#7005972) is gratefully acknowledged.

References

  1. M. Landgraf and M. Enzi, "Smart Data for a Pro-active Railway Asset Management," Proceedings of 7th Transport Research Arena TRA 2018, 2018, doi: 10.5281/ZENODO.1445928.
  2. P. McMahon, T. Zhang, and R. Dwight, "Requirements for Big Data adoption for Railway asset Management," IEEE Access, vol. 8, pp. 15543-15564, 2020, doi: 10.1109/ACCESS.2020.2967436.
  3. M. Chun-ying and L. Biqing, "Software Design of a Railway Signal Monitoring System based on Optical Fiber Sensing," International Journal of Online Engineering (iJOE), vol. 14, no. 08, p. 134, Aug. 2018, doi: 10.3991/ijoe.v14i08.9180.
  4. S. Kaewunruen and Q. Lian, "Digital twin aided sustainability-based lifecycle management for railway turnout systems," J Clean Prod, vol. 228, pp. 1537-1551, Aug. 2019, doi: 10.1016/j.jclepro.2019.04.156.
  5. "openBIM Definition - buildingSMART International." Accessed: Dec. 20, 2023. [Online]. Available: https://www.buildingsmart.org/about/openbim/openbim-definition/
  6. "IFC4.3.2.0 Documentation." Accessed: Dec. 19, 2023. [Online]. Available: https://standards.buildingsmart.org/IFC/RELEASE/IFC4_3/
  7. H. Pu et al., "Extending IFC for multi-component subgrade modeling in a railway station," Autom Constr, vol. 141, p. 104433, Sep. 2022, doi: 10.1016/J.AUTCON.2022.104433.
  8. S. Jaud, S. Esser, A. Borrmann, L. Wikstrom, S. Muhic, and J. Mirtschin, "A critical analysis of linear placement in IFC models," in ECPPM 2021-eWork and eBusiness in Architecture, Engineering and Construction: Proceedings of the 13th European Conference on Product & Process Modelling (ECPPM 2021), 15-17 September 2021, Moscow, Russia, CRC Press, 2021, p. 12.
  9. T. H. Kwon, S. I. Park, Y. H. Jang, and S. H. Lee, "Design of railway track model with three-dimensional alignment based on extended industry foundation classes," Applied Sciences (Switzerland), vol. 10, no. 10, 2020, doi: 10.3390/app10103649.
  10. A. Ciccone, S. Di Stasio, D. Asprone, A. Salzano, and M. Nicolella, "Application of openBIM for the Management of Existing Railway Infrastructure: Case Study of the Cancello-Benevento Railway Line," Sustainability, vol. 14, no. 4, p. 2283, 2022, doi: 10.3390/su14042283.
  11. S. Kaewunruen, M. H. Osman, and W. Hao Cheng Eric, "Risk-Based Maintenance Planning for Rail Fastening Systems," ASCE ASME J Risk Uncertain Eng Syst A Civ Eng, vol. 5, no. 3, Sep. 2019, doi: 10.1061/AJRUA6.0001012.
  12. F. Ciccozzi, I. Malavolta, and B. Selic, "Execution of UML models: a systematic review of research and practice," Softw Syst Model, vol. 18, no. 3, pp. 2313-2360, Jun. 2019, doi: 10.1007/s10270-018-0675-4.
  13. H. Sobke, P. Peralta, K. Smarsly, and M. Armbruster, "An IFC schema extension for BIM-based description of wastewater treatment plants," Autom Constr, vol. 129, p. 103777, Sep. 2021, doi: 10.1016/j.autcon.2021.103777.
  14. S. Ait-Lamallam, R. Yaagoubi, I. Sebari, and O. Doukari, "Extending the ifc standard to enable road operation and maintenance management through openbim," ISPRS Int J Geoinf, vol. 10, no. 8, 2021, doi: 10.3390/ijgi10080496.
  15. F. Shalabi and Y. Turkan, "IFC BIM-Based Facility Management Approach to Optimize Data Collection for Corrective Maintenance," Journal of Performance of Constructed Facilities, vol. 31, no. 1, p. 04016081, 2017, doi: 10.1061/(asce)cf.1943-5509.0000941.
  16. V. J. L. Gan, T. Wang, D. Hu, and C. Yin, "Developing an Integrated Data Model based on IFC and SensorML for Post-COVID Facility Management," in 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys), IEEE, Dec. 2021, pp. 1845-1850. doi: 10.1109/HPCC-DSSS-martCity-DependSys53884.2021.00273.
  17. F. Mirahadi, B. McCabe, and A. Shahi, "IFC-centric performance-based evaluation of building evacuations using fire dynamics simulation and agent-based modeling," Autom Constr, vol. 101, pp. 1-16, May 2019, doi: 10.1016/J.AUTCON.2019.01.007.