For many of us a flight delay or worse still a cancellation means an inconvenience to our plans; for an airline an aircraft on the ground (AOG) situation costs them an average of $10,000 per hour. Operational efficiency for an airline’s fleet is therefore of the utmost importance.
According to the IATA 42% of late flights are due to airline-controlled processes, such as maintenance. With the global aviation market rapidly on the rise, the MRO market is looking at ways in which predictive maintenance, through big data, could be integrated to minimise AOG and improve efficiencies.
Big data in the aviation industry is the term given to the collection and analysis of large amounts of complex data, collected from an aircraft using data sensors. Many of the big players, including Boeing and Airbus, have already realised the huge potential that the analysis of this data could have on the day-to-day flight operations of their fleet, including improving maintenance efficiencies in order to maximise performance.
The huge amount of data returned from the sensors on an aircraft can then be applied in a preventive and predictive approach to maintenance. Predictive maintenance works by predicting when equipment failure is likely to occur, thus preventing the occurrence of failure by ensuring that the required maintenance is carried out. This can dramatically reduce unplanned downtime and mitigate unscheduled maintenance.
The data also allows the maximum on-wing time for parts and engines optimising usage and lowering the total lifecycle cost.
Predictive maintenance enables MROs to quickly find faults and organise the resources required to meet the maintenance schedule in advance, maximising efficiency. This in turn keeps costs low for airlines and provides them with the minimum disruption to flights, keeping more planes in the air.
The way in which ELMS aims to complement these efficiencies found through the use of big data is by enabling organisations to quickly adapt and deploy the right resources for the job.
The ELMS aviation management tool enables organisations to quickly view all their employees training, qualifications and experience based on specific job categories and by aircraft type. A search can be filtered down to very specific detail to ensure the most competent staff are deployed for the job.
ELMS gives individuals the opportunity to be recognised for their experience, competency and compliance by current and future employers, and to continue to gain further training and experience to continue to enhance their profile.