TY - JOUR
T1 - Risk-based optimization of pipe inspections in large underground networks with imprecise information
AU - Mancuso, A.
AU - Compare, M.
AU - Salo, A.
AU - Zio, E.
AU - Laakso, T.
PY - 2016/8/1
Y1 - 2016/8/1
N2 - 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.
AB - 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.
KW - Imprecise information
KW - Portfolio decision analysis
KW - Risk-based inspection
UR - http://www.scopus.com/inward/record.url?scp=84963704532&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2016.03.011
DO - 10.1016/j.ress.2016.03.011
M3 - Article
AN - SCOPUS:84963704532
SN - 0951-8320
VL - 152
SP - 228
EP - 238
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
ER -