Over the last few decades, the number of people flying has grown significantly. Now, a few years since the pandemic ended, air traffic is back to the level it was before the pandemic, and is expected to grow even faster than before the pandemic.
Most aircraft engine repa
...
Over the last few decades, the number of people flying has grown significantly. Now, a few years since the pandemic ended, air traffic is back to the level it was before the pandemic, and is expected to grow even faster than before the pandemic.
Most aircraft engine repairs are organised as Maintenance, Repair and Overhaul (MRO). Scheduling projects for an aircraft engine MRO presents several key challenges. Like the uncertainty of processes (especially when depending on external parties). At the time of writing, the supply chain of these MROs remains heavily disrupted, resulting in numerous parts being (near) unobtainable. And challenges involving personnel. Even if all other resources are ready and available, this means nothing if there are not enough personnel with the required skills available.
The goal of this research is to develop a model that uses exact methods to perform proactive rescheduling of the aeroplane engine MRO process. This model focuses on finding a solution that balances between: (1) Quality, (2) Deviation impact minimisation and (3) Robustness. Quality refers to metrics such as project turnaround time (TAT), workload performance, and minimisation of unused workforces. Robustness metrics focus on aspects such as minimising the number of excessively scheduled resources in a solution or indicating how well a solution responds to disruptions in the input data. Finally, deviation impact minimisation focuses on minimising the impact reschedules have on the actual workflow of the MRO.
