IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v181y2019icp156-166.html
   My bibliography  Save this article

Optimal pipe inspection paths considering inspection tool limitations

Author

Listed:
  • Chen, Thomas Ying-Jeh
  • Guikema, Seth David
  • Daly, Craig Michael

Abstract

The inspection of deteriorating water distribution pipes is an important process for utilities. It helps them gain a better understanding of the condition of their buried conveyance systems and aids better decision making for risk-based asset management. In-pipe continuous inspection tools provide high resolution and accurate data, but they have seen relatively limited use due to cost and operational constraints. To facilitate-cost efficient deployment of these technologies and maximal information gain, a process that finds high risk pipes to inspect while accounting for the limitations of the tools at hand is needed. This paper shows how to incorporate these considerations within an optimization formulation, and examines the use of Evolutionary Programming, Simulated Annealing, and Greedy Search heuristics to identify inspection paths. Case studies performed on both synthetic and real world networks demonstrate that Evolutionary Programs are the most effective. While only three factors are used to characterize tool limitations, the method presented in this paper can be extended to include technology-specific complexities in real world applications.

Suggested Citation

  • Chen, Thomas Ying-Jeh & Guikema, Seth David & Daly, Craig Michael, 2019. "Optimal pipe inspection paths considering inspection tool limitations," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 156-166.
    • Handle: RePEc:eee:reensy:v:181:y:2019:i:c:p:156-166
    DOI: 10.1016/j.ress.2018.09.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017314473
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2018.09.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Aven, Terje, 2010. "On how to define, understand and describe risk," Reliability Engineering and System Safety, Elsevier, vol. 95(6), pages 623-631.
    2. Emily M. Zechman, 2011. "Agent‐Based Modeling to Simulate Contamination Events and Evaluate Threat Management Strategies in Water Distribution Systems," Risk Analysis, John Wiley & Sons, vol. 31(5), pages 758-772, May.
    3. Francis, Royce A. & Guikema, Seth D. & Henneman, Lucas, 2014. "Bayesian Belief Networks for predicting drinking water distribution system pipe breaks," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 1-11.
    4. Laporte, Gilbert, 1992. "The traveling salesman problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(2), pages 231-247, June.
    5. Mancuso, A. & Compare, M. & Salo, A. & Zio, E. & Laakso, T., 2016. "Risk-based optimization of pipe inspections in large underground networks with imprecise information," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 228-238.
    6. Yamijala, Shridhar & Guikema, Seth D. & Brumbelow, Kelly, 2009. "Statistical models for the analysis of water distribution system pipe break data," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 282-293.
    7. E. Downey Brill, Jr. & Shoou-Yuh Chang & Lewis D. Hopkins, 1982. "Modeling to Generate Alternatives: The HSJ Approach and an Illustration Using a Problem in Land Use Planning," Management Science, INFORMS, vol. 28(3), pages 221-235, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Thomas Ying-Jeh & Riley, Connor Thomas & Van Hentenryck, Pascal & Guikema, Seth David, 2020. "Optimizing inspection routes in pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    2. Ruiz Muñoz, G.A. & Sørensen, J.D., 2020. "Probabilistic inspection planning of offshore welds subject to the transition from protected to corrosive environment," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    3. Jensen, H.A. & Jerez, D.J., 2019. "A Bayesian model updating approach for detection-related problems in water distribution networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 100-112.
    4. Chen, Thomas Ying-Jeh & Guikema, Seth David, 2020. "Prediction of water main failures with the spatial clustering of breaks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Robles-Velasco, Alicia & Cortés, Pablo & Muñuzuri, Jesús & Onieva, Luis, 2020. "Prediction of pipe failures in water supply networks using logistic regression and support vector classification," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    2. Kabir, Golam & Tesfamariam, Solomon & Sadiq, Rehan, 2015. "Predicting water main failures using Bayesian model averaging and survival modelling approach," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 498-514.
    3. Rifaai, Talha M. & Abokifa, Ahmed A. & Sela, Lina, 2022. "Integrated approach for pipe failure prediction and condition scoring in water infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    4. Chen, Thomas Ying-Jeh & Riley, Connor Thomas & Van Hentenryck, Pascal & Guikema, Seth David, 2020. "Optimizing inspection routes in pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. Zheng Tang & Yijia Li & Xiaofeng Hu & Huanggang Wu, 2019. "Risk Analysis of Urban Dirty Bomb Attacking Based on Bayesian Network," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    6. Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
    7. Niels Agatz & Paul Bouman & Marie Schmidt, 2018. "Optimization Approaches for the Traveling Salesman Problem with Drone," Transportation Science, INFORMS, vol. 52(4), pages 965-981, August.
    8. Kusum Deep & Hadush Mebrahtu & Atulya K. Nagar, 2018. "Novel GA for metropolitan stations of Indian railways when modelled as a TSP," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(3), pages 639-645, June.
    9. Fan, Xudong & Wang, Xiaowei & Zhang, Xijin & ASCE Xiong (Bill) Yu, P.E.F., 2022. "Machine learning based water pipe failure prediction: The effects of engineering, geology, climate and socio-economic factors," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    10. Schuijbroek, J. & Hampshire, R.C. & van Hoeve, W.-J., 2017. "Inventory rebalancing and vehicle routing in bike sharing systems," European Journal of Operational Research, Elsevier, vol. 257(3), pages 992-1004.
    11. Majeed Abimbola & Faisal Khan, 2018. "Dynamic Blowout Risk Analysis Using Loss Functions," Risk Analysis, John Wiley & Sons, vol. 38(2), pages 255-271, February.
    12. Caputo, Antonio C. & Federici, Alessandro & Pelagagge, Pacifico M. & Salini, Paolo, 2023. "Offshore wind power system economic evaluation framework under aleatory and epistemic uncertainty," Applied Energy, Elsevier, vol. 350(C).
    13. Tang, Lixin & Liu, Jiyin & Rong, Aiying & Yang, Zihou, 2000. "A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex," European Journal of Operational Research, Elsevier, vol. 124(2), pages 267-282, July.
    14. Castellano, Davide & Gallo, Mosè & Grassi, Andrea & Santillo, Liberatina C., 2019. "The effect of GHG emissions on production, inventory replenishment and routing decisions in a single vendor-multiple buyers supply chain," International Journal of Production Economics, Elsevier, vol. 218(C), pages 30-42.
    15. Gagliardi, Jean-Philippe & Ruiz, Angel & Renaud, Jacques, 2008. "Space allocation and stock replenishment synchronization in a distribution center," International Journal of Production Economics, Elsevier, vol. 115(1), pages 19-27, September.
    16. Kafle, Nabin & Zou, Bo & Lin, Jane, 2017. "Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 62-82.
    17. Aven, Terje, 2013. "A conceptual framework for linking risk and the elements of the data–information–knowledge–wisdom (DIKW) hierarchy," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 30-36.
    18. Terje Aven & Ortwin Renn, 2015. "An Evaluation of the Treatment of Risk and Uncertainties in the IPCC Reports on Climate Change," Risk Analysis, John Wiley & Sons, vol. 35(4), pages 701-712, April.
    19. Mengtang Li & Guoku Jia & Xun Li & Hao Qiu, 2023. "Efficient Trajectory Planning for Optimizing Energy Consumption and Completion Time in UAV-Assisted IoT Networks," Mathematics, MDPI, vol. 11(20), pages 1-19, October.
    20. Nguyen, Son & Chen, Peggy Shu-Ling & Du, Yuquan & Shi, Wenming, 2019. "A quantitative risk analysis model with integrated deliberative Delphi platform for container shipping operational risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 203-227.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:181:y:2019:i:c:p:156-166. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.