2021
DOI: 10.2166/hydro.2021.068
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Data-driven asset management in urban water pipe networks: a proposed conceptual framework

Abstract: Analytical tools used in infrastructure asset management of urban water pipe networks are reliant on asset data. Traditionally, data required by analytical tools has not been collected by most water utilities because it has not been needed. The data that is collected might be characterised by low availability, integrity and consistency. A process is required to support water utilities in assessing the accuracy and completeness of their current data management approach and defining improvement pathways in relat… Show more

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Cited by 15 publications
(6 citation statements)
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References 43 publications
(60 reference statements)
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“…The risk-based I&R model can prioritize hundreds of SCs in a distribution network based on their potential risk of leakage. Such data-driven decision-making tools not only enhance the service life of infrastructure but these tools also provide a low-cost solution to water loss control [49]. It is suggested that a small team of two to three field personnel can visit and inspect the SCs with "high" priority and make or plan (if the required parts are not available on the same day) the desired repair.…”
Section: Discussionmentioning
confidence: 99%
“…The risk-based I&R model can prioritize hundreds of SCs in a distribution network based on their potential risk of leakage. Such data-driven decision-making tools not only enhance the service life of infrastructure but these tools also provide a low-cost solution to water loss control [49]. It is suggested that a small team of two to three field personnel can visit and inspect the SCs with "high" priority and make or plan (if the required parts are not available on the same day) the desired repair.…”
Section: Discussionmentioning
confidence: 99%
“…The results are unusual as NSGA-II is often criticised within the literature for its multi-objective optimisation performance with three or more objectives (Elarbi et al 2017). For the MCDA criterion weightings for this case study a literature survey on suggested MCDA frameworks based on the work by Okworia et al (2021) and an evaluation team of wastewater managers at DCWW analysed the needs, goals and limitations of water companies, to decide on the evaluation criteria. The evaluation team decided that priority score was the criteria they wished to prioritise the most.…”
Section: Case Study Descriptionmentioning
confidence: 99%
“…On one side, the network data is hard to obtain. In a large number of urban areas, there is no complete data on the pipeline network [15,16]. There are a number of reasons for this, including the fact that the relevant information has been missing from the outset or has been lost over a long period of time for one reason or another, especially given that in some places the pipeline network was constructed decades ago [17].…”
Section: Introductionmentioning
confidence: 99%