Full Description

This paper describes a mains maintenance (MM) application that will provide a robust rationale for the identification and prioritization of mains for maintenance. Developed and deployed for the United Kingdom water company United Utilities, according to that Company's conceptual specification, the use of the MM computer application will lead to improved DG3 reporting in that unplanned interruptions will be minimized. The MM application will prioritize system maintenance on a quantitative basis. It will take into account customers impacted by mains' failure, mains' condition and ways of operating systems to mitigate such failures. To date, mains' rehabilitation at United Utilities has been water quality-based and generally targeted at distribution mains. In future, quantitative analysis will be required to justify investment for the maintenance of larger mains. The MM application will enable the Company to carry out the necessary detailed and structured analysis and will prioritize mains' maintenance. The application will support the high-level whole life infrastructure modelling techniques being used by the Company. The MM application is an example of UUSD's intelligent asset management techniques and associated risk management methods being developed to ensure compliance with the UK's regulatory approach to risk management within the water industry. The application ranks mains according to their relative importance in the system. It uses a scoring mechanism based on burst and leak histories and the vulnerability of customers to outage (partial or complete). The paper discusses the intelligent asset management approach as applied to mains' maintenance, the risk and reliability-based ranking used and technical considerations that impact on the process. The paper also considers the application's role within mains' maintenance investment and the operational benefits that will arise as a result of its development. Includes tables, figures.

Product Details

Edition: Vol. - No. Published: 04/18/2004 Number of Pages: 19 File Size: 1 file , 560 KB