Risk-based prioritization of sewer pipe inspection from infrastructure asset management perspective

Jeonghun Lee, Chan Young Park, Seungwon Baek, Seung H. Han, Sungmin Yun

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number7213
JournalSustainability (Switzerland)
Volume13
Issue number13
DOIs
Publication statusPublished - 2021 Jul 1

Bibliographical note

Funding Information:
Funding: This work was supported by the 2016 Yeungnam University Research Grant.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Environmental Science (miscellaneous)
  • Energy Engineering and Power Technology
  • Management, Monitoring, Policy and Law

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