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Identification of waterways maintenance significant units using secondary data and Multi-Attribute Utility Theory

Abstract Due to the progressive aging of existing infrastructures and insufficient investment in their maintenance, the backlog of maintenance work is growing steadily. Consequently, the identification of maintenance significant units, which are system elements linked with higher risk, is of paramount importance. However, risk assessment of infrastructure systems is a complex task, since risk has multiple dimensions and its assessement requires information from several system levels. In this paper, the Multi-Attribute Utility Theory is applied in order to assess the risk of neglecting maintenance and identify the maintenance significant units in a system of locks of the German waterways network. The advantages of this approach are to aggregate risk factors having different unit measures and contributing differently to risk, and to supplement value judgments with objective measurements. The aim of this paper is also to highlight the potential of secondary databases for performing early risk assessment and planning more detailed analyses.