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The efficient refurbishment of rotable parts on an aircraft proves to be a main concern for airline carriers today. Airlines must be able to seamlessly rotate parts into and out of the system for maintenance in accordance with FAA requirements while leaving daily operations uninterrupted. In this paper, we develo

The efficient refurbishment of rotable parts on an aircraft proves to be a main concern for airline carriers today. Airlines must be able to seamlessly rotate parts into and out of the system for maintenance in accordance with FAA requirements while leaving daily operations uninterrupted. In this paper, we develop an airline maintenance scheduling model that constructs an optimal schedule for part maintenance over a given time horizon using deterministic forecasting techniques. The model generates a schedule that minimizes the total cost of a maintenance schedule solution while maximizing the utility of all parts in the system. The model is then tested against actual network data of three part types crucial to airline operations and used to investigate the current data collection processes of US Airways maintenance lead time metrics. Manual sensitivity analysis is performed to generate the marginal value of each parameter and potential model extensions are highlighted as a result of these conclusions.
ContributorsDunham, Nicole Elizabeth (Author) / Gel, Esma (Thesis director) / Jacobs, Timothy (Committee member) / Clough, Michael (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-12
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Description
Most staff planning for airline industries are done using point estimates; these do not account for the probabilistic nature of employees not showing up to work, and the airline company risks being under or overstaffed at different times, which increases costs and deteriorates customer service. This model proposes utilizing a

Most staff planning for airline industries are done using point estimates; these do not account for the probabilistic nature of employees not showing up to work, and the airline company risks being under or overstaffed at different times, which increases costs and deteriorates customer service. This model proposes utilizing a stochastic method for American Airlines to schedule their ground crew staff. We developed a stochastic model for scheduling that incorporates the risks of absent employees and as well as reliability so that stakeholders can determine the level of reliability they want to maintain in their system based on the costs. We also incorporated a preferences component to the model in order to increase staff satisfaction in the schedules they get assigned based on their predetermined preferences. Since this is a general staffing model, this can be utilized for an airline crew or virtually any other workforce so long as certain parameters about the population can be determined.
ContributorsOtis, Matthew (Co-author) / Reyes, Katherine (Co-author) / Gel, Esma (Thesis director) / Jacobs, Tim (Committee member) / Clough, Michael (Committee member) / Barrett, The Honors College (Contributor)
Created2016-05