Abstract
Aircraft maintenance and repair organizations (MROs) have to be competitive and attractive for both existing and new customers. The aircraft ground time at MROs should be as short as possible and cost effective without reducing the quality of the work. Process optimization in MROs requires the continuous improvement of processes and the elimination of non-value-added activities during maintenance checks. There is, on the one hand, an obligation to follow the prescribed procedures and, on the other hand, pressure for time and cost reduction. The aircraft servicing process has been analysed according to a lean methodology. The optimization of logistics processes is recognized as the most promising method for reducing the maintenance service time and costs of spare parts. The probability of aircraft faults is calculated on the basis of historic data from previously completed service projects. Aircraft parameters, such as aircraft type, operator, aircraft age, flight hours, flight cycles, engine type and operation
location, are taken into consideration in the fault forecasting. The fault probability is used as an indicator for defining a priority list for the accomplishment of jobs included in the aircraft maintenance service. The proposed methodology was validated and confirmed on four different projects.
location, are taken into consideration in the fault forecasting. The fault probability is used as an indicator for defining a priority list for the accomplishment of jobs included in the aircraft maintenance service. The proposed methodology was validated and confirmed on four different projects.
Original language | English |
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Pages (from-to) | 624-633 |
Number of pages | 10 |
Journal | Eksploatacja i Niezawodnosc - Maintenance and Reliability |
Volume | 19 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2017 Sept 21 |
Externally published | Yes |
Subject classification (UKÄ)
- Reliability and Maintenance
Free keywords
- aircraft maintenance
- fault forecasting
- lean methods
- machine learning
- spare parts logistics