Prediction of Required Materials for Aircraft Heavy Maintenance

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

Prediction of Required Materials for Aircraft Heavy Maintenance

Original language description

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.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20304 - Aerospace engineering

Project

<a href="/en/project/CK01000204" target="_blank" >CK01000204: Improving effectiveness of aircraft maintenance planning and execution</a><br>

Continuities

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

Publication year

2022

Confidentiality

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

Article name in the collection

2022 New Trends in Civil Aviation (NTCA)

ISBN

978-80-01-06985-1

ISSN

—

e-ISSN

2694-7854

Number of pages

7

Pages from-to

35-41

Publisher name

České vysoké učení technické v Praze

Place of publication

Praha

Event location

Praha

Event date

Oct 26, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000895902200004