Influence of structural deterioration over time on the optimal time interval for inspection and maintenance of structures

Tolentino, Dante; Ruiz, Sonia E.

doi:10.1016/j.engstruct.2014.01.012

Cited by 13 publications

(13 citation statements)

References 27 publications

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“…In this study, the timings are obtained based on periodic maintenance intervention policy, which is widely adopted in the literature, because periodic interventions are more easy to be implemented from a management perspective. 27,28,34 Also, the input parameters of the probabilistic crack growth model in Section 2 can affect the results of optimal maintenance decision making. The values of these parameters are inputs of this study and represent existing or prior knowledge about the fatigue crack growth phenomenon.…”

Section: Discussionmentioning

confidence: 99%

Bayesian maintenance decision optimisation based on computing the information value from condition inspections

Zou

Banisoleiman

González

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.

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Section: Discussionmentioning

confidence: 99%

Bayesian maintenance decision optimisation based on computing the information value from condition inspections

Zou

Banisoleiman

González

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…Herein, a periodic inspection policy following [55,[73][74][75][76][77][78] is adopted. The latter specifies that inspections are carried out at equal intervals, e.g.…”

Section: Decision Variables In Maintenance Planningmentioning

confidence: 99%

A holistic approach to risk-based decision on inspection and design of fatigue-sensitive structures

Zou

Faber

González

et al. 2020

Engineering Structures

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Design and operation of large welded structural systems (e.g. ship and offshore structures) are challenging due to numerous fatigue-sensitive details, limited available budgets, uncertainties in fatigue damages, inspection & maintenance activities, etc. Traditionally, fatigue design and maintenance planning have been almost disconnected, which restricts coherent decision-making and optimum safety management. Structural design optimization, without quantitatively incorporating the effects of operational maintenance, can hardly result in a structural plan that is optimum in terms of life cycle costs. Also, if the design of a structure is not optimum, maintenance optimization alone cannot yield a really optimum maintenance plan. As operational inspections and maintenance are essential, there are merits to utilize their effects to structural design and meanwhile optimize them at the initial design stage when impacts of decisions are greater. This paper proposes a riskbased approach to holistic decision-making enveloping decisions and uncertainties affecting design, inspection and maintenance of fatigue-sensitive components. Decisions variables in structural scantling and operational maintenance are obtained holistically at the structural design stage by risk based optimization, based on quantitative assessment of the effectiveness of both structural scantling and maintenance interventions. Optimum fatigue reliability level is also obtained, informed by the effects of uncertainties and failure consequences. The method captures combined benefits of structural scantling and operational maintenance to fatigue reliability and risk mitigation and achieves optimum resource utilization and life cycle cost reduction. Advantages of the proposed method have been demonstrated via a numerical example, In comparison to alternative methods.

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“…For example, from the perspective of logistics and management, it may be more convenient to adopt an equal inspection interval, e.g. to carry out inspections at equal-distant times, as adopted by (Zio and Compare 2013, Huynh, Grall, and Bérenguer 2017, Scarf, Wang, and Laycock 1996, Mendes, Coit, and Ribeiro 2014, Cronvall et al 2012, Zou et al 2018, Tolentino and Ruiz 2014. With this constraint, the possible solutions are greatly reduced.…”

Section: Probabilistic Maintenance Optimization Approachmentioning

confidence: 99%

“…In this section, two maintenance interventions are planned in lifetime and the repair criteria are optimized with respect to and . A periodic inspection policy is applied (Zio and Compare 2013, Huynh, Grall, and Bérenguer 2017, Scarf, Wang, and Laycock 1996, Mendes, Coit, and Ribeiro 2014, Cronvall et al 2012, Zou et al 2018, Tolentino and Ruiz 2014 and the time intervals for interventions are ∆ = 6 years. Following the approach proposed in Section 6, the derived optimum results are provided in Tables 11 and 12.…”

Section: Optimum Planning For Multiple Interventionsmentioning

confidence: 99%

An integrated probabilistic approach for optimum maintenance of fatigue-critical structural components

et al. 2019

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Inspection and maintenance are important means to validate or recover reliability of metallic structural systems, which usually degrade over time due to fatigue, corrosion and other mechanisms. These inspection and maintenance actions generally account for a large part of lifetime costs, which necessitate an efficient maintenance strategy to satisfy the requirements on reliability and costs. Most often, an optimum maintenance/repair crack size criterion is derived by probabilistic cost-benefit analysis, e.g. by minimization of expected lifetime costs, which are assessed based on cost models. This paper proposes an integrated approach to derive an optimum range for maintenance criterion using both reliability-based and cost-based optimization. It is found that an optimum repair (crack size) criterion exists which leads to the maximum lifetime fatigue reliability. A smaller repair criterion than the reliability-optimum do not lead to a higher lifetime fatigue reliability but leads to higher lifetime costs. Hence, a limit for repair criterion is defined by the reliability-optimum criterion, which can be obtained without cost models. The reliability-optimum criterion is found to be smaller than the costoptimum criterion and thus an optimum range between the reliability-optimum and cost-optimum criterion is established.

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Influence of structural deterioration over time on the optimal time interval for inspection and maintenance of structures

Cited by 13 publications

References 27 publications

Bayesian maintenance decision optimisation based on computing the information value from condition inspections

Bayesian maintenance decision optimisation based on computing the information value from condition inspections

A holistic approach to risk-based decision on inspection and design of fatigue-sensitive structures

An integrated probabilistic approach for optimum maintenance of fatigue-critical structural components

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