Predicting throughput time

W.P.F. Beekmans, R.M. Dijkman (Editor)

Research output: Book/ReportReportAcademic

Abstract

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.
LanguageEnglish
Place of PublicationEindhoven
PublisherTechnische Universiteit Eindhoven
Number of pages12
ISBN (Print)978-90-386-4600-8
StatePublished - 13 Nov 2018

Publication series

NameeSCF Operations Practices: Insight from Science
No.16

Fingerprint

Throughput
Repair
Aircraft
Customer satisfaction
Machinery
Availability
Engines
Planning
Industry

Cite this

Beekmans, W. P. F., & Dijkman, R. M. (Ed.) (2018). Predicting throughput time. (eSCF Operations Practices: Insight from Science; No. 16). Eindhoven: Technische Universiteit Eindhoven.
Beekmans, W.P.F. ; Dijkman, R.M. (Editor). / Predicting throughput time. Eindhoven : Technische Universiteit Eindhoven, 2018. 12 p. (eSCF Operations Practices: Insight from Science; 16).
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Beekmans, WPF & Dijkman, RM (ed.) 2018, Predicting throughput time. eSCF Operations Practices: Insight from Science, no. 16, Technische Universiteit Eindhoven, Eindhoven.

Predicting throughput time. / Beekmans, W.P.F.; Dijkman, R.M. (Editor).

Eindhoven : Technische Universiteit Eindhoven, 2018. 12 p. (eSCF Operations Practices: Insight from Science; No. 16).

Research output: Book/ReportReportAcademic

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Beekmans WPF, Dijkman RM, (ed.). Predicting throughput time. Eindhoven: Technische Universiteit Eindhoven, 2018. 12 p. (eSCF Operations Practices: Insight from Science; 16).