Life-cycle maintenance of deteriorating structures by multi-objective optimization involving reliability, risk, availability, hazard and cost

Barone, Giorgio; Frangopol, Dan M.

doi:10.1016/j.strusafe.2014.02.002

Cited by 107 publications

(31 citation statements)

References 24 publications

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“…Previous research efforts have effectively performed risk analyses in a qualitative [2,3] and quantitative manner [4][5][6][7][8][9] under a multitude of hazards for various structures. In general, structural components that are under relatively high risk should receive priority for maintenance interventions.…”

Section: Introductionmentioning

confidence: 99%

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Sustainability-informed maintenance optimization of highway bridges considering multi-attribute utility and risk attitude

Sabatino

Frangopol

Dong

2015

Engineering Structures

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105

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Section: Introductionmentioning

confidence: 99%

“…Studies concerning the optimization of maintenance strategies based on reliability, risk, and/or redundancy have been conducted [8,[10][11][12]. Additionally, lifetime distributions have also been used within maintenance http://dx.doi.org/10.1016/j.engstruct.2015.07.030 0141-0296/Ó 2015 Elsevier Ltd. All rights reserved.…”

Section: Introductionmentioning

confidence: 99%

Sustainability-informed maintenance optimization of highway bridges considering multi-attribute utility and risk attitude

Sabatino

Frangopol

Dong

2015

Engineering Structures

Self Cite

105

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“…Several indicators have been proposed during recent years to represent the time dependent structural performance of deteriorating structures [9].Once the future condition of the device estimated effectively applying probability forecasting model, the equipment failure rate at a certain time, reliability function, or residual life distribution function has been obtained. A maintenance decision model can be established in accordance with the economy, equipment availability, risk and other criteria, and the optimal strategy [12].…”

Section: Hierarchy Of Avionics Systemmentioning

confidence: 99%

“…(2) According to the above results, by the calculation formula (9) and (10), gain matrix V + and loss matrix V − are constructed, respectively, i.e., …”

Section: Case Analysismentioning

confidence: 99%

Maintenance strategy decision for avionics system based on cognitive uncertainty information processing

Tu¹,

Sun²,

Zhang³

et al. 2015

Eksploatacja i Niezawodnosc - Maintenance and Reliability

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Maintenance strategy decision for avionics system based on cognitive uncertainty information processing. eksploatacja i niezawodnosc - Maintenance and Reliability 2015; 17 (2): 297-305, http://dx.doi.org/10.17531/ein.2015.2.18. Jiliang Tu Chengli Sun Xiangyang ZhAng hongliang PAn Ruofa ChengMaintenance strategy decision for avionics systeM based on cognitive uncertainty inforMation processing decyzja w zakresie strategii utrzyMania ruchu układu elektroniki lotniczej w oparciu o przetwarzanie inforMacji związanych z niepewnością kognitywną only by pilot error. In that sense, the importance of maintenance activity has increased due to its key role on improving system availability, performance efficiency, safety and reliability, etc. Thus in order to improve avionics considerations in general, maintenance managers (MM) should take decisions about the maintenance strategies to be implemented as well as the necessary resources to satisfy avionics system performances and requirements. Proper maintenance schedule is required to improve avionics systems reliability and safety. A decision approach to maintenance strategy remains a longstanding challenge in avionics system. With regard to fault diagnosis and equipment maintenance of avionics system, in which the equipment fault information are complex and uncertainty, a multi criteria of decision making method for avionics system based on cognitive uncertainty information processing is proposed to be used in the maintenance strategy decision. Firstly, vague set with three-parameters is introduced to make up for the shortage of the original vague set in expressing fuzzy information, a linguistic variables describing the qualitative indexes into three parameter vague of interval number is proposed. At the same time, due to risk psychological factors of maintenance policymakers that cause cognitive uncertainty are introduced into the maintenance decision process, and a prospect value function of three parameters vague interval value is defined based on prospect theory and the formula for measuring the distance between vague interval value, and a non-linear model of equipment maintenance policies can be established. The implementing process of maintenance policy decision for avionics system based on cognitive uncertainty information processing is given in this paper, and a ranking of the maintenance alternatives is determined. Finally, A specific example of decision of maintenance strategies in avionics system with the application of the proposed method isSatisfactory performance of an aircraft depends up on the continued reliability, security, features enhancements of avionics system. Reliability is proportional to amount of maintenance received and knowledge of men who performed such maintenance [13,17]. Now, an avionics system may comprise a large number of components, and efficient maintenance strategy is required to improve the reliability of relevant functions and to reduce high maintenance cost. For a long time, both home and abroad have to take preventive tests and...

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“…In order to ensure adequate life-cycle performance, it is crucial to implement optimal management strategies that maintain performance of infrastructure systems within acceptable levels through their life-cycle (Okasha & Frangopol 2009. Life-cycle management is widely recognized as an effective tool for maximizing the cost-effectiveness of implementing intervention actions that improve condition and safety, and extend the service life of deteriorating infrastructure systems (Ang 2011, Barone & Frangopol 2014a, Frangopol & Liu 2007.…”

Section: Introductionmentioning

confidence: 99%

Risk- and Sustainability-Informed Decision Making for Structures in a Life-Cycle Context

Frangopol¹,

Sabatino²

2017

Proceedings of the Joint COST TU1402 - COST TU1406 - IABSE WC1 Workshop: The Value of Structural Health Monitoring for the Reli

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Life-cycle maintenance of deteriorating structures by multi-objective optimization involving reliability, risk, availability, hazard and cost

Cited by 107 publications

References 24 publications

Sustainability-informed maintenance optimization of highway bridges considering multi-attribute utility and risk attitude

Sustainability-informed maintenance optimization of highway bridges considering multi-attribute utility and risk attitude

Maintenance strategy decision for avionics system based on cognitive uncertainty information processing

Risk- and Sustainability-Informed Decision Making for Structures in a Life-Cycle Context

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