OPTIMIZING AIRCRAFT LINE MAINTENANCE THROUGH TASK RE-CLUSTERING AND INTERVAL DE-ESCALATION

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dc.contributor.author Muchiri, A.K
dc.contributor.author Smit, K.
dc.date.accessioned 2017-02-13T12:55:17Z
dc.date.available 2017-02-13T12:55:17Z
dc.date.issued 2017-02-13
dc.identifier.uri http://hdl.handle.net/123456789/2680
dc.description.abstract This paper presents an adaptation of maintenance interval de-escalation to line maintenance planning. The necessity to optimize maintenance follows from a need to reduce line maintenance visits that interrupt routine aircraft operation due to their frequent occurrence. Further, frequent opening and closing of panels results in significant wear and tear, and thus reducing the inherent reliability of the aircraft. A simulation model has been developed to predict the maintenance requirement of aircraft in an airline operating under known conditions. Construction and validation of the model are based on knowledge and statistical data of actual operations and maintenance practices. The main use of the model is to group maintenance tasks into manageable packages that can be executed at extended maintenance intervals and within specified periods, and thus increasing aircraft availability. The model can also be used to vary and adapt line maintenance packages in case an aircraft visits the hangar for non-routine maintenance. The concept of initial deescalation of maintenance intervals is introduced and its positive effects are demonstrated. en_US
dc.language.iso en en_US
dc.subject Aircraft maintenance en_US
dc.subject clustering en_US
dc.subject simulation en_US
dc.subject optimization, en_US
dc.subject Boeing 737NG en_US
dc.title OPTIMIZING AIRCRAFT LINE MAINTENANCE THROUGH TASK RE-CLUSTERING AND INTERVAL DE-ESCALATION en_US
dc.type Article en_US


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