ABSTRACT
Asset management can be defined as managing infrastructure capital assets to minimize the total cost of owning and operating them, while delivering the service levels to customers’ desire. Developed to promote more efficient financial and physical resource investments and to extend the life of infrastructure system components, asset management offers the potential to more than pay for itself over the long term.
It can also serve as a logical, cost-effective framework for making organizational changes to meet new environmental regulations and financial reporting requirements. Many of these large organizations base asset management planning on sophisticated information systems and extensive personnel resources.
The sewerage system in a region and all components associated with this system constitute a treatment and sewer asset. As with any other asset, it is important to invest in its maintenance in order to fulfill its task. However, the modeling of sewer pipe assets is one of complex issues. Such an asset is constituted of many components, it is subjected to a large number of different stresses such as being mainly situated underground and therefore not visible. Nevertheless, the maintenance and rehabilitation has to be carried out regardless of such incomplete and inaccurate information and knowledge about the condition of the asset. It is not financially feasible to monitor the evolution of the state of an asset on a regular basis. Information is fully available only when the sewer is laid. The knowledge about the state of the sewer pipe is only updated when an accident occurs and the sewer pipe is partially unearthed. Moreover the management of a sewer pipe must deal with administrative, environmental and social constraints upon the actions of the utilities company.
The complexity of the asset modeling problem calls for advanced methods. This report outlines residual life estimation for the analysis of the risk of collapse in sewer system. With reliable risk models, addressing the evolution of risk with aging asset, it is now possible to plan optimal rehabilitation or replacement strategies in advance, before a collapse actually occurs.