Risk-based optimization of pipe inspections in large underground networks with imprecise information. (August 2016) - Mancuso, A.; Compare, M.; Salo, A.; Zio, E.; Laakso, T.
Abstract: In this paper, we present a novel risk-based methodology for optimizing the inspections of large underground infrastructure networks in the presence of incomplete information about the network features and parameters. The methodology employs Multi Attribute Value Theory to assess the risk of each pipe in the network, whereafter the optimal inspection campaign is built with Portfolio Decision Analysis (PDA). Specifically, Robust Portfolio Modeling (RPM) is employed to identify Pareto-optimal portfolios of pipe inspections. The proposed methodology is illustrated by reporting a real case study on the large-scale maintenance optimization of the sewerage network in Espoo, Finland. Highlights: Risk-based approach to optimize pipe inspections on large underground networks. Reasonable computational effort to select efficient inspection portfolios. Possibility to accommodate imprecise expert information. Feasibility of the approach shown by Espoo water system case study.