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Purpose-Driven Evaluation of Operation and Maintenance Efficiency and Safety Based on DIKWP

Author

Listed:
  • Yanfei Liu

    (College of Intelligence and Computing, Tianjin University, Tianjin 300072, China
    Information Security Department, Chongqing Police College, Chongqing 401331, China)

  • Wentao Wang

    (School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China)

  • Wenjun Wang

    (College of Intelligence and Computing, Tianjin University, Tianjin 300072, China
    Georgia Tech Shenzhen Institute, Tianjin University, Shenzhen 518055, China)

  • Chengbo Yu

    (School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China)

  • Bowen Mao

    (College of Intelligence and Computing, Tianjin University, Tianjin 300072, China)

  • Dongfang Shang

    (College of Intelligence and Computing, Tianjin University, Tianjin 300072, China)

  • Yucong Duan

    (School of Computer Science and Technology, Hainan University, Haikou 570228, China)

Abstract

In large-scale public security equipment projects, long-term equipment operation often leads to equipment failures and other problems, so it is particularly important to choose the appropriate operation and maintenance (O&M) scheme based on the content of the equipment work orders. However, there are a variety of equipment models in the work orders; not only is the data complex, but also due to the long project cycle, there are often problems such as loss of content, which bring great challenges to the O&M work. This paper defines these problems as “3-No problems”: inconsistency, inaccuracy, and incompleteness. In this paper, an improved DIKWP model is proposed and combined with a random forest classifier to construct data graphs, information graphs, knowledge graphs, and wisdom graphs. Through the above model, the 3-No problem in equipment work orders can be solved, and the importance of each equipment model can be obtained. Eventually, combined with the purpose graph, the selection of models, the bid score calculation, and the selection of O&M schemes are carried out based on the obtained conclusion in a purpose-driven manner to achieve the evaluation of O&M efficiency and safety. Finally, an example is assumed to illustrate the application of the method in actual projects, which provides a certain reference value for the selection of an O&M scheme for large-scale equipment projects.

Suggested Citation

  • Yanfei Liu & Wentao Wang & Wenjun Wang & Chengbo Yu & Bowen Mao & Dongfang Shang & Yucong Duan, 2023. "Purpose-Driven Evaluation of Operation and Maintenance Efficiency and Safety Based on DIKWP," Sustainability, MDPI, vol. 15(17), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:13083-:d:1229112
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    References listed on IDEAS

    as
    1. Betti, Alessandro & Crisostomi, Emanuele & Paolinelli, Gianluca & Piazzi, Antonio & Ruffini, Fabrizio & Tucci, Mauro, 2021. "Condition monitoring and predictive maintenance methodologies for hydropower plants equipment," Renewable Energy, Elsevier, vol. 171(C), pages 246-253.
    2. Lorentziadis, Panos L., 2020. "Competitive bidding in asymmetric multidimensional public procurement," European Journal of Operational Research, Elsevier, vol. 282(1), pages 211-220.
    3. Han Peng & Songyin Li & Linjian Shangguan & Yisa Fan & Hai Zhang, 2023. "Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research," Sustainability, MDPI, vol. 15(10), pages 1-35, May.
    4. Mara Del Baldo & Federica Palazzi, 2023. "High-Growth Benefit Corporations: Leveraging on Intangibles—Insights from Italy," Sustainability, MDPI, vol. 15(14), pages 1-20, July.
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