Lidé na fakultě
Ing. Ondřej Vítovec

2023, 2023 New Trends in Aviation Development (NTAD), Praha, IEEE Czechoslovakia Section), p. 83-88), ISBN 979-8-3503-7042-3, ISSN 2836-2756

Maintenance, Repair, and Overhaul (MRO) organizations are one of the pillars of aviation safety. They ensure the airworthiness of aircraft in accordance with regulatory requirements. In Europe, until the recent changes in legislation, safety was part of quality and compliance management. Today, MROs are required to implement a Safety Management System (SMS). The paper focuses on MRO hazard and risk register, proposing a sample register with a procedure how to develop it. The proposed solution integrates with other parts of the integrated management system, such as quality control or occupational health and safety. The hazard and risk register was proposed using the recent approach of the System-Theoretic Accident Model and Processes (STAMP) accident causality model, suitable for complex sociotechnical systems, which are typical in the aviation today. The proposed solution allows the assessment of the system as a whole, which leads to the identification of new types of hazards and structuring of the existing ones. The presented study was performed with two European MROs to evaluate and validate its outputs.

Stať ve sborníku z prestižní konf. (Scopus)

2022, 2022 New Trends in Civil Aviation (NTCA), Praha, České vysoké učení technické v Praze), p. 35-41), ISBN 978-80-01-06985-1, ISSN 2694-7854

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.

Stať ve sborníku z prestižní konf.