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Risk-Based Prioritization of Sewer Pipe Inspection from Infrastructure Asset Management Perspective

Author

Listed:
  • Jeonghun Lee

    (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

  • Chan Young Park

    (Intelligent Construction Automation Center, Kyungpook University, Daegu 41566, Korea)

  • Seungwon Baek

    (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

  • Seung H. Han

    (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

  • Sungmin Yun

    (Department of Civil Engineering, Yeungnam University, Gyeongsan 38541, Korea)

Abstract

The escalating number of aging sewer pipes necessitates an infrastructure asset management approach to achieve an efficient budget allocation for maintenance. This study suggests a risk-based prioritization framework for sewer pipe inspection considering the predicted condition of sewer pipes and the criticality of the economic, social and environmental impacts associated with them. The results from both models can be used to evaluate the risk of sewer pipes by classification into risk groups. A risk matrix is used for the classification, and it divides the sewer pipes into five risk groups. The results of this study show an improvement in the accuracy of finding sewer pipes in a bad condition using this framework. The condition prediction model can successfully find sewer pipes with a bad condition with over 70% precision. High-risk sewer pipes are highlighted using the differences in the environmental features as well as in the physical features associated with other sewer pipes. Additionally, through the combination of both the condition and criticality of sewer pipes, the framework systemically prioritizes needed maintenance for sewer pipes with a very bad condition. This prioritization framework is expected to help the process of deciding which sewer pipes should be prioritized within a constrained budget.

Suggested Citation

  • Jeonghun Lee & Chan Young Park & Seungwon Baek & Seung H. Han & Sungmin Yun, 2021. "Risk-Based Prioritization of Sewer Pipe Inspection from Infrastructure Asset Management Perspective," Sustainability, MDPI, vol. 13(13), pages 1-21, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7213-:d:583646
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    References listed on IDEAS

    as
    1. Kiyeon Kim & Joonyoung Kim & Tae-Young Kwak & Choong-Ki Chung, 2018. "Logistic regression model for sinkhole susceptibility due to damaged sewer pipes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(2), pages 765-785, September.
    2. Kabir, Golam & Balek, Ngandu Balekelayi Celestin & Tesfamariam, Solomon, 2018. "Consequence-based framework for buried infrastructure systems: A Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 290-301.
    3. Marc Ribalta & Carles Mateu & Ramon Bejar & Edgar Rubión & Lluís Echeverria & Francisco Javier Varela Alegre & Lluís Corominas, 2021. "Sediment Level Prediction of a Combined Sewer System Using Spatial Features," Sustainability, MDPI, vol. 13(7), pages 1-15, April.
    4. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
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