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Effectiveness of it applications on consumer complaint for improvement of water supply: a case study with cluster analysis

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dc.contributor.author Fernando, GDP
dc.contributor.author De Silva, PKC
dc.contributor.editor Mallikarachchi, C
dc.contributor.editor Hettiarachchi, P
dc.contributor.editor Herath, S
dc.contributor.editor Fernando, L
dc.date.accessioned 2023-10-03T09:20:09Z
dc.date.available 2023-10-03T09:20:09Z
dc.date.issued 2023-09-27
dc.identifier.citation ** en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/21489
dc.description.abstract One of the most significant concerns of humankind has been the provision of adequate quantities and quality of water. Unfortunately, modern water distribution networks are complex and challenging to manage due to increased levels of urbanisation, varying consumer demands, and limited resources. Therefore, authorities must make critical decisions to solve problems associated with different phases and time frames of water distribution networks. Most of the management issues are challenging to solve using conventional problem-solving techniques. One of the versatile approaches for solving these management problems is to use customer complaints to develop optimisation techniques. National Water Supply & Drainage Board (NWSDB) receives various complaints about their services. This thesis presents a case study on the Biyagama water supply scheme, focusing on analysing leakage occurrence in the pipeline network. The study utilised a dataset collected by the National Water Supply and Drainage Board (NWSDB) for three years. Aim is to investigate the factors influencing leak occurrence in the Biyagama water supply scheme and develop a comprehensive understanding of pipe network vulnerability, with the objective of informing targeted maintenance strategies and improving the overall reliability and efficiency of the water supply system. The primary objective was to investigate the factors influencing leakages in the network and develop a comprehensive understanding of pipe network vulnerability. The research employed the Kmeans algorithm, implemented using the Python programming language, to conduct a cluster analysis of the dataset. The analysis incorporated factors, including age, inner diameter, and hydraulic parameters, such as pressure and velocity, to identify patterns and correlations associated with leak occurrence. The cluster analysis results revealed that age physical characteristics and hydraulic parameters alone were insufficient to explain the variations in leak frequency among the clusters. To account for this, additional factors were considered, including pipe material, installation quality, maintenance practices, temperature, soil condition, traffic load and environmental conditions. Incorporating hydraulic parameters, such as pressure and velocity, provided valuable insights into the relationship between fluid dynamics and leak vulnerability. High fluid velocities also correlated with leak occurrence. The findings emphasise the complexity of pipe network vulnerability and highlight the importance of considering multiple factors in assessing leakage occurrence. By gaining a comprehensive understanding of the factors influencing leaks, stakeholders can develop targeted maintenance strategies and improve the overall reliability and efficiency of the water supply system. This research contributes to the field of water supply management by providing insights into the vulnerabilities of pipe networks and the factors influencing leak occurrence. The findings can inform decision-making processes for infrastructure maintenance and support the development of sustainable water management strategies. en_US
dc.language.iso en en_US
dc.publisher Department of Civil Engineering en_US
dc.subject Water supply en_US
dc.subject Leakage occurrence en_US
dc.subject Cluster analysis en_US
dc.subject K-means algorithm en_US
dc.subject Pipe network vulnerability en_US
dc.title Effectiveness of it applications on consumer complaint for improvement of water supply: a case study with cluster analysis en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Department of Civil Engineering en_US
dc.identifier.year 2023 en_US
dc.identifier.conference Civil Engineering Research Symposium 2023 en_US
dc.identifier.place University of Moratuwa, Katubedda, Moratuwa. en_US
dc.identifier.pgnos pp. 99-100 en_US
dc.identifier.proceeding Proceedings of Civil Engineering Research Symposium 2023 en_US


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