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    Risk-Based Maintenance Planning for Deteriorating Pressure Vessels With Multiple Defects

    Source: Journal of Pressure Vessel Technology:;2017:;volume( 139 ):;issue: 004::page 41602
    Author:
    Haladuick, Shane
    ,
    Dann, Markus R.
    DOI: 10.1115/1.4036428
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Pressure vessels are subject to deterioration processes, such as corrosion and fatigue, which can lead to failure. Inspections and repairs are performed to mitigate this risk. Large industrial facilities (e.g., oil and gas refineries) often have regularly scheduled shutdown periods during which many components, including the pressure vessels, are disassembled, inspected, and repaired if necessary. This paper presents a decision analysis framework for the risk-based maintenance (RBM) planning of corroding pressure vessels. After a vessel has been inspected, this framework determines the optimal maintenance time of each defect, where the optimal time is the one that minimizes the total expected cost over the lifecycle of the vessel. The framework allows for multiple defects and two failure modes (leak and burst), and accounts for the dependent failure events. A stochastic gamma process is used to model the future deterioration growth to determine the probability of vessel failure. The novel growth model presents a simple method to predict both the depth and length of each corrosion defect to enable burst analysis. The decision analysis framework can aid decision makers in deciding when a repair or replacement should be performed. This method can be used to immediately inform the decision maker of the optimal decision postinspection. A numerical example of a corroding pressure vessel illustrates the method.
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      Risk-Based Maintenance Planning for Deteriorating Pressure Vessels With Multiple Defects

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    contributor authorHaladuick, Shane
    contributor authorDann, Markus R.
    date accessioned2017-11-25T07:19:10Z
    date available2017-11-25T07:19:10Z
    date copyright2017/21/4
    date issued2017
    identifier issn0094-9930
    identifier otherpvt_139_04_041602.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4235632
    description abstractPressure vessels are subject to deterioration processes, such as corrosion and fatigue, which can lead to failure. Inspections and repairs are performed to mitigate this risk. Large industrial facilities (e.g., oil and gas refineries) often have regularly scheduled shutdown periods during which many components, including the pressure vessels, are disassembled, inspected, and repaired if necessary. This paper presents a decision analysis framework for the risk-based maintenance (RBM) planning of corroding pressure vessels. After a vessel has been inspected, this framework determines the optimal maintenance time of each defect, where the optimal time is the one that minimizes the total expected cost over the lifecycle of the vessel. The framework allows for multiple defects and two failure modes (leak and burst), and accounts for the dependent failure events. A stochastic gamma process is used to model the future deterioration growth to determine the probability of vessel failure. The novel growth model presents a simple method to predict both the depth and length of each corrosion defect to enable burst analysis. The decision analysis framework can aid decision makers in deciding when a repair or replacement should be performed. This method can be used to immediately inform the decision maker of the optimal decision postinspection. A numerical example of a corroding pressure vessel illustrates the method.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleRisk-Based Maintenance Planning for Deteriorating Pressure Vessels With Multiple Defects
    typeJournal Paper
    journal volume139
    journal issue4
    journal titleJournal of Pressure Vessel Technology
    identifier doi10.1115/1.4036428
    journal fristpage41602
    journal lastpage041602-8
    treeJournal of Pressure Vessel Technology:;2017:;volume( 139 ):;issue: 004
    contenttypeFulltext
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