Minimizing lifetime structural costs: Optimizing for production and maintenance under service life uncertainty

Temple, Dylan; Collette, Matthew

doi:10.1016/j.marstruc.2014.10.006

Cited by 11 publications

(3 citation statements)

References 20 publications

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“…Probabilistic modelling has been acknowledged as a strong tool to treat uncertainties consistently and widely adopted in structural maintenance optimization (Ang and Tang 2007). Based on probabilistic models, structural reliability methods have been developed to consider the effects of uncertainties in the fatigue and fracture limit state, and reliability has been used as a performance indicator for maintenance optimization (Ayala-Uraga and Moan 2007, Temple and Collette 2015, Lotsberg et al 2016. Risk analysis methods extend the scope to incorporate failure consequences, in addition to failure probabilities.…”

Section: Introductionmentioning

confidence: 99%

Fatigue inspection and maintenance optimization: A comparison of information value, life cycle cost and reliability based approaches

et al. 2021

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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.

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Section: Introductionmentioning

confidence: 99%

Fatigue inspection and maintenance optimization: A comparison of information value, life cycle cost and reliability based approaches

et al. 2021

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“…Maintenance actions are scheduled at specific points in time to prevent significant failures during lifetime, and maintenance times and methods are optimized to reduce lifetime maintenance costs by time-variant reliability/risk analysis utilizing as-built and operational structural information (Temple and Collette 2015, Rinaldi et al 2017 Nowadays, condition-based maintenance (CBM) is gaining a wide range of attention as a result of developments in non-destructive (NDT) testing techniques, sensing and monitoring technology, system identification algorithms, and data science. Information on structural responses and damage conditions is collected during operations to assist rational maintenance decision-making.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic investigations into the value of information: A comparison of condition-based and time-based maintenance strategies

et al. 2019

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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.

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“…The agreed on budget in the bidding process will not only have an impact on the production of the vessels, but will also be relevant for the life cycle of the project and the need to extend the lifespan of the ships [7]. At the same time, these budgets will be crucial in order to define the company's competitiveness [8] and the risks they are able to take in reducing the sale price of their ships [9].…”

Section: Introductionmentioning

confidence: 99%

Obtaining the Budget Contingency Reserve Through the Monte Carlo Method: Study of a Ferry Construction Project

Para‐González

Mascaraque‐Ramírez

Madrid³

2018

brod

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The naval sector of new construction is characterised by high cost programmes and a low degree of definition in the stages of tendering. With these requirements, an initial, highlycompetitive budget should be developed with acceptable risk. For this reason, it is usual in this field for a budget Contingency Reserve to be defined, in order to cover probable range increments, as well as probable deviations that could trigger economic losses. The budget Contingency Reserve estimate is usually carried out based on shipyard experience. However, problems arise when the shipyard does not have enough experience in the concrete type of vessel to be built. In this research, the use of an extension of the triangular Monte Carlo distribution model is proposed, with the aim of calculating the likelihood of complying with the calculated budget. From this result, a Contingency Reserve that provides enough security to execute the project within the limits of the economic risk defined by the organization can be calculated. The proposal introduced in this study allows managers to obtain a more optimal estimate of the Contingency Reserve, therefore reducing economic risks.

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Minimizing lifetime structural costs: Optimizing for production and maintenance under service life uncertainty

Cited by 11 publications

References 20 publications

Fatigue inspection and maintenance optimization: A comparison of information value, life cycle cost and reliability based approaches

Fatigue inspection and maintenance optimization: A comparison of information value, life cycle cost and reliability based approaches

Probabilistic investigations into the value of information: A comparison of condition-based and time-based maintenance strategies

Obtaining the Budget Contingency Reserve Through the Monte Carlo Method: Study of a Ferry Construction Project

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