Risk-based inspection planning of deteriorating structures

Structural deterioration due to environmental and mechanical stressors is a major concern for civil and marine structures. Inspection actions can reduce uncertainties, facilitate decision-making on maintenance, and in general assist life-cycle management. Risk-based inspection (RBI) planning is a useful tool to minimize life-cycle cost while preserving safety margin of structures. This paper compares (a) static RBI (SRBI) planning where inspection schedule and maintenance criteria are time- and evidence-invariant and (b) adaptive RBI (ARBI) planning where decisions on inspection and maintenance (I&M) are made sequentially and reactively to I&M actions. Specifically, three RBI planning methods, i.e., SRBI with Monte Carlo simulation, ARBI based on Bayesian networks, and ARBI based on partially observable Markov decision processes (POMDP), are compared based on a generic Markovian deterioration model (MDM). In addition, it is demonstrated that ARBI planning can be extended from MDMs to many physics-based deterioration models such as corrosion and fatigue models. The advantages and disadvantages of different RBI planning methods are summarized. Potentials of ARBI planning are also discussed.