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Workforce shift scheduling at aircraft line maintenance with cumulative demand modelling

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dc.contributor Graduate Program in Industrial Engineering.
dc.contributor.advisor Ünal, Ali Tamer.
dc.contributor.author Altay, Gökhan.
dc.date.accessioned 2023-03-16T10:29:25Z
dc.date.available 2023-03-16T10:29:25Z
dc.date.issued 2018.
dc.identifier.other IE 2018 A67
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/13391
dc.description.abstract This study aims to do overall shift assignments of aircraft line maintenance crew to satisfy line maintenance tasks in time. These tasks can only be satisfied by maintenance crew with necessary qualifications. Therefore, shift assignments are done for tasks that require a specific qualification. Main objective of this study is to prevent the delay due to not having workforce ready to satisfy maintenance tasks. At our model, we generated desired manpower demand schedule to monitor maintenance crew shift assignments to satisfy maintenance tasks earlier or to keep more worker ready for unplanned demand cases. Moreover, we also consider planned demand schedule coming from maintenance tasks of airplanes that is required to be satisfied in time. We formulated both demand schedules as cumulative in order to assign maintenance workers near desired demand schedule while being able to satisfy planned demand in time. We used Cplex to solve this model. We noticed that Cplex doesn’t perform good for all problem instances. Therefore, to support performance of the Cplex solver, we also offered a simulated annealing algorithm to improve results. This problem is tested for different amounts of airplanes, workforce, planning horizons and demand patterns and results are evaluated.
dc.format.extent 30 cm.
dc.publisher Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018.
dc.subject.lcsh Aircraft industry.
dc.subject.lcsh Aircraft industry -- Maintenance and repair.
dc.title Workforce shift scheduling at aircraft line maintenance with cumulative demand modelling
dc.format.pages x, 50 leaves ;


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