Availability of machines is very important in achieving operational excellence. In Aerospace, this need is especially high, to make sure that airplanes can keep up with flight plans and passengers, as well as cargo, can get to their destination in time. However, machines have to be maintained from time to time. Then, it helps to have a good estimate of when the maintenance activity will be ready. This enables the maintenance department to take appropriate measures, such as keeping the optimal number of spare parts in stock and optimally planning for down time of the machine. This operations practice describes how Fokker Services implemented a technique for predicting the throughput time of their maintenance activities on airplane engines. It shows that they managed to improve their throughput time prediction, which potentially means a higher customer satisfaction can be achieved. Moreover, the techniques that they use to predict the throughput time of a repair, can also be used to predict the expected time until the next repair or maintenance action is necessary. We expect that – with the advent of Internet of Things – such ‘data-driven condition based maintenance’, will not just be important for Fokker Services, but for all companies that maintain expensive machinery.
|Place of Publication||Eindhoven|
|Publisher||Technische Universiteit Eindhoven|
|Number of pages||12|
|Publication status||Published - 13 Nov 2018|
|Name||eSCF Operations Practices: Insight from Science|