Aircraft maintenance production planning depends on an accurate estimate of the time and workload to complete a given aircraft maintenance package. It is related to the formation of the final price to the client, determining the turnaround time for the airplane and capacity planning for the maintenance base. Defect removal work is one of the factors that most significantly affect the execution time. The volume of these unplanned works is random and is a major source of uncertainty in determining the total workload. Therefore, before starting the work on the aircraft, together with the evaluation of the work set by the operator, hours for elimination of defects are calculated. This is usually done based on previous experience with similar maintenance events. In this work the contribution of different factors to the percentage of unscheduled works was explored using two generic approaches. The more conventional was package-level based on the total planned man-hours, aircraft age, aircraft type and operator. An alternative was to consider task-level variables as the type of maintenance tasks performed (according to the MSG-3 logic) and the systems/equipment/skills involved. The results confirm that applying data analytics in maintenance production planning can provide better accuracy. Task-level analysis brings additional insights for more informed decisions related to maintenance scheduling.
Predicting the unscheduled workload for an aircraft maintenance work package
13TH INTERNATIONAL SCIENTIFIC CONFERENCE ON AERONAUTICS, AUTOMOTIVE AND RAILWAY ENGINEERING AND TECHNOLOGIES (BulTrans-2021) ; 2021 ; Sozopol, Bulgaria
AIP Conference Proceedings ; 2557 , 1
2022-10-13
8 pages
Conference paper
Electronic Resource
English
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