Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486145
Title: Prioritisation of proactive sewer maintenance using serviceability as a key performance indicator
Author: Duncan, Helen
Awarding Body: Heriot-Watt University
Current Institution: Heriot-Watt University
Date of Award: 2007
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Abstract:
In sewerage asset management, there has been a concerted move away from primarily assessing system capacity, to focus on 'serviceability' as a key performance indicator. In the UK, water regulators have imposed an expectation on water companies to significantly lower the risk posed to customer serviceability from the sewerage industry. Proactive maintenance is the main vehicle by which asset managers aim to achieve this outcome. This thesis outlines the development of a methodology which ranks network pipes in order of risk to serviceability. The tool is base on the Failure Mode, Effect and Criticality Analysis (FMECA) principle that risk is a function of failure consequence and likelihood and in exception to other recently developed tools, this method focuses the analysis towards data which is readily available within the industry and aims to avoid data where reliability is in doubt, such as records of past events. The tool consists of an initial screening process to eliminate those pipes which are at a significantly reduced likelihood of flooding before each remaining pipe is scored according to various factors which affect consequence and likelihood of flooding. Final risk scores, and therefore rankings are then achieved through the combination of consequence and likelihood scores. Appropriate scores and weightings have been achieved through customer research, discussion with industry representatives and the completion of an additional study into trends in failure likelihood. The methodology is a decision support tool developed to aid sewerage asset managers in their role in balancing risk to customer serviceability against cost of intervention, by providing a measure of risk which is not dependent on poor quality data.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.486145  DOI: Not available
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