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    Item type:Publication, Access status: without files ,
    A decision support model for the composite repair process in a collaborative platform
    (2018-09)
    Thyagarajan, Sowmya
    ;
    Gollnick, Volker
    This paper describes the development of a decision model to support the repair process for composite structures. During operation, aircraft are susceptible to various forms of damage caused by accidental impact, fatigue loads and other environmental conditions. Maintenance strategies implemented for specific damage need to become more accurate and cost efficient to ensure safe operation and airworthiness of the aircraft. The selected repair strategy and the connected type of repair determine the availability of the asset. When contemplated from an operational perspective, the decision could have an impact on key criteria such as reliability, cost and downtime. Prognostics-based condition monitoring has the potential to predict the failure behaviour by estimating the mean residual life or the remaining useful life. The decision support model developed in this paper integrates proportional hazard modelling to determine the repairable behaviour with a level of repair analysis to determine cost-optimal repair decisions.
    Publicationtype: Journal Article
      180
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    Item type:Publication, Access status: without files ,
    A novel decision support model for composite repair decision process
    (Curran Associates, Inc., 2017)
    Thyagarajan, Sowmya
    ;
    Gollnick, Volker
    This paper provides the development of a decision model to support the repair decision process for composite structures. Aircraft structures are susceptible to various damages affected by accidental impact, fatigue loads and other environmental conditions. Maintenance strategies implemented for specific damage have to be more accurate and cost efficient to ensure safe operations and airworthiness of the aircraft. The selected repair strategy and the connected type of repair determines the availability of the asset when contemplated from an operational perspective as the decision could have an impact on main criterias like reliability, cost and downtime. Prognostics based condition monitoring has the potential to predict the failure behaviour by estimating mean residual life or the remaining useful life. The decision support model developed here integrates proportional hazard modeling to determine the repairable behaviour with Level of repair analysis to determine the cost optimal repair decisions.
    Publicationtype: Conference Paper
      102