Utilities throughout the world are faced with the challenge of how best to manage their existing asset stock to provide satisfactory customer service with limited funds. Effective asset management helps utilities to meet this challenge; however, this requires the utilization of cost-effective approaches for assessing asset condition, performance and remaining service life. A key component of these approaches requires an understanding of asset lifetimes. This paper discusses the role of asset lifetimes in asset management and the current state of the art for prediction of remaining life using different approaches. It discusses very simple approaches based on assumed lives, as well as sophisticated mathematical approaches using deterministic, statistical, physical/probabilistic and artificial intelligence models. In analysing both asset management strategies and lifetime prediction methodologies, a key factor identified as missing is a standardized technique for the incorporation of lifetime models into the probability side of risk analysis. For asset management to become a valued and readily utilized tool, this issue needs to be urgently addressed.

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