No abstract

Optimal maintenance of marine structures is challenging due to numerous fatigue-prone components, serious failure consequences, high maintenance costs, harsh sea environments, difficult access, and uncertainties in fatigue loading, resistance, and inspection and maintenance activities. Time-based maintenance (TBM) is convenient to implement. However, condition-based maintenance (CBM) is proved to be more cost-effective. This paper assesses the value of information (VoI) by inspections in CBM, compared to TBM, and investigates the conditions for CBM to outperform TBM in terms of fatigue reliability. A probabilistic maintenance optimization method and a life cycle cost analysis framework are established to derive optimal CBM and TBM strategies with the objective of maximizing lifetime reliability and evaluating their life cycle costs. The advantages of CBM, in comparison to TBM, and the VoI depends strongly on the inspection time. The CBM can achieve higher reliability with fewer maintenance costs than the TBM. An illustrative example is provided using the established probabilistic method and framework to support optimal maintenance planning. This example serves as a basis to explain the benefits of CBM to lifetime fatigue reliability and cost reduction, the conditions when CBM is more beneficial than TBM, the conditions for beneficial, ineffective and unbeneficial repair, and the VoI by inspections.

In this compilation, the contributions published as extended abstracts of the 16th International Probabilistic Workshop 2018 in Vienna are collected. This article is also published in the Wiley Online Library (WOL) at https://doi.org/10.1002/best.201800059. In addition to these Extended Abstracts, all contributions can be found online as a Full Paper on the same doi in the corresponding and so called Supporting Information.

No abstract

Fatigue cracks increase structural failure risk and timely maintenance is very important. Maintenance planning is often formulated as a probabilistic optimization problem, considering uncertainties in structural and load modelling, material properties, damage measurements, etc. A decision rule or strategy, e.g. condition based maintenance (CBM), needs to be set up, and then an optimal maintenance criterion or threshold is derived via solving the optimization problem. This paper develops a probabilistic maintenance optimization approach exploiting value of information (VoI) and Bayesian decision optimization. The VoI based approach explicitly quantifies added values from future inspections, and gives an optimal decision (or strategy) by direct modelling decision alternatives and evaluating their expected outcomes, rather than a pre-defined strategy. A comparative study on VoI, life cycle cost (LCC) and reliability based optimization approaches is conducted. It is shown that the VoI based approach takes all available maintenance strategies into account (both with and without inspections), and can reliably yield optimal maintenance strategies, whether the VoI is larger than or equal to zero. When the VoI is equal to zero, LCC and reliability based CBM optimization can result in suboptimal maintenance strategies. The differences in the approaches are illustrated on fatiguesensitive components in a marine structure.