Prediction of Required Materials for Aircraft Heavy Maintenance

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F22%3A00362081" target="_blank" >RIV/68407700:21260/22:00362081 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.23919/NTCA55899.2022.9934582" target="_blank" >https://doi.org/10.23919/NTCA55899.2022.9934582</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.23919/NTCA55899.2022.9934582" target="_blank" >10.23919/NTCA55899.2022.9934582</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Prediction of Required Materials for Aircraft Heavy Maintenance

Popis výsledku v původním jazyce

The aim is to provide a method of predicting the material required for heavy aircraft maintenance using mathematical prediction models. This includes the possibility of comparing the accuracy of different models. Previous studies have not applied multiple different mathematical prediction models to real operational data, i.e., data from an Approved Maintenance Organisation (AMO). To easily operate and display the results, computer software, including a Graphical User Interface (GUI), has been developed in a MATLAB environment. Real operational data was provided by AMO organisation for the years 2016 to 2020 inclusive. A total of ten mathematical prediction models were selected for the prediction calculations. These were selected based on research and previous studies on the topic of material prediction. The user of the software has the possibility to perform the prediction for all parts in the database or only for one specific part. The results are stored in the database or displayed directly in the GUI. The model accuracies for all parts are on average about 92 %. If we use cleaned data and exclude from the predictions parts that often have zero quarterly demand, we get to an average prediction accuracy of 83 %. The most accurate forecasts are made by the Exponential Smoothing with use of Moving Average Forecasting Model, Croston's Forecasting Model and Syntetos-Boylan Approximation Forecasting Method models.

Název v anglickém jazyce

Prediction of Required Materials for Aircraft Heavy Maintenance

Popis výsledku anglicky

The aim is to provide a method of predicting the material required for heavy aircraft maintenance using mathematical prediction models. This includes the possibility of comparing the accuracy of different models. Previous studies have not applied multiple different mathematical prediction models to real operational data, i.e., data from an Approved Maintenance Organisation (AMO). To easily operate and display the results, computer software, including a Graphical User Interface (GUI), has been developed in a MATLAB environment. Real operational data was provided by AMO organisation for the years 2016 to 2020 inclusive. A total of ten mathematical prediction models were selected for the prediction calculations. These were selected based on research and previous studies on the topic of material prediction. The user of the software has the possibility to perform the prediction for all parts in the database or only for one specific part. The results are stored in the database or displayed directly in the GUI. The model accuracies for all parts are on average about 92 %. If we use cleaned data and exclude from the predictions parts that often have zero quarterly demand, we get to an average prediction accuracy of 83 %. The most accurate forecasts are made by the Exponential Smoothing with use of Moving Average Forecasting Model, Croston's Forecasting Model and Syntetos-Boylan Approximation Forecasting Method models.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20304 - Aerospace engineering

Projekt

<a href="/cs/project/CK01000204" target="_blank" >CK01000204: Zvýšení efektivity plánování a provádění údržby dopravních letadel</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2022 New Trends in Civil Aviation (NTCA)

ISBN

978-80-01-06985-1

ISSN

—

e-ISSN

2694-7854

Počet stran výsledku

7

Strana od-do

35-41

Název nakladatele

České vysoké učení technické v Praze

Místo vydání

Praha

Místo konání akce

Praha

Datum konání akce

26. 10. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000895902200004