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Aircraft spares consumption prediction model for the small air operators

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dc.contributor.advisor Adikariwattage V
dc.contributor.author Hettiarachchi KT
dc.date.accessioned 2019
dc.date.available 2019
dc.date.issued 2019
dc.identifier.citation Hettiarachchi, K.T. (2019). Aircraft spares consumption prediction model for the small air operators [Master’s theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.mrt.ac.lk/handle/123/15877
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/15877
dc.description.abstract When an aircraft spare or component found defective on ground or during the flight that might compromise the aircraft's safety, it is important to remove it and replaced with serviceable component always. However, in order to avoid delays in the operations, it is critical that the availability of the replacement at the aircraft parts store for a quick turnaround. Aircraft spares consumption prediction is so important. While excess inventories expensive due to additional inventory holding cost, inventory obsolesce, tying up capital. As well as stockouts creates huge capital losses to the air operators through costly flight delays or cancellations, loss of brand reputation, over utilization of other aircraft in the fleet, etc. So that availability of the right quantity at the right time of the aircraft spares is so vital, for that aircraft consumption prediction plays the key role. Regression analysis and the consumption prediction is classical and practical forecasting method. Four years of Cessna 208 series aircraft Main Wheel consumption details used for the analysis. Initially data analysed with linier regression analysis and found relationship with the Aircraft Flying Time and Main Wheel consumption is significant, but it is non linier relationship. Then same data was analysed with Poisson regression analysis and the final model was developed. It can be used for the consumption prediction model as well as a decision-making tool for the inventory level estimations. en_US
dc.language.iso en en_US
dc.subject TRANSPORT AND LOGISTICS MANAGEMENT-Dissertations en_US
dc.subject SUPPLY CHAIN MANAGEMENT-Dissertations en_US
dc.subject AIRCRAFT-Spare Parts en_US
dc.subject AIRCRATFT MAINTENANCE en_US
dc.subject FORECASTING-Mathematical Techniques en_US
dc.title Aircraft spares consumption prediction model for the small air operators en_US
dc.type Thesis-Full-text en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree MBA in Supply Chain Management en_US
dc.identifier.department Department of Transport and Logistics Management en_US
dc.date.accept 2019
dc.identifier.accno TH4041 en_US


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