Over the last several years data generated by aircraft has increased exponentially thru introduction of new onboard equipment that allows for the so-called connected aircraft. In the wake of this data growth OEM’s and airlines have shown increased interest in data analytics and predictive maintenance.
According to the MRO survey 2017 by Oliver Wyman (When Growth Outpaces Capacity) 77% of respondents want to implement predictive maintenance in the coming three years. The MRO survey 2017 by Aircraft IT confirms this trend as most respondents answered that next to paperless maintenance predictive maintenance will play a major role in the development the upcoming years.
So, is your airline ready for implementing predictive maintenance?
Based on years of working with airlines and aircraft data, within EXSYN we characterize three different types of airline:
- Reporting airline
- Monitoring airline
- Data driven airline
Each of these three types of airlines stand on different success levels for adoption of predictive maintenance.
Let’s have a closer look at the three types of airline:
The reporting airline
The reporting airline is characterized by producing monthly reliability reports, drawing from manual work of retrieving the various information such as aircraft utilization, Pilot reports, Maintenance findings and component removals and then consolidate this data into Excel.
This typically is a very manual labour-intensive process and puts the reporting airline in a situation that they are able to produce the reports on monthly bases but not action on these reports.
The monitoring airline
The monitoring airline, stands 1 level higher on the adoption success scale of becoming predictive. This type of airline typically already moved away from excel reports and uses an analytical tool and mostly also dashboards. This allows the airline to act more quickly on rising issues and monitor the fleet than rather reporting the status of their fleet.
However, it still draws on the same set of data, the SPEC2000 chapter 11 reliability data. Which ultimately prevents the airline of adopting any predictive maintenance models as data sets are to limit to become reliable enough for operational usage.
The data driven airline
The data driven airline, has the highest level of adoption success for predictive maintenance models. It used all character traits of the monitoring airline but has recognized the need of having access to larger sets of data beyond its own airline data, such as industry reliability data, Flight Data Recorder information, weather data as well as ADS-B transponder data. Ultimately the data driven airline implements a data driven platform in its organization that provides information to its operational units such as maintenance operations control to make informed decisions in day-of-operation itself.
Any airline wanting to make use of the benefits that predictive maintenance brings to its operation will first need to start with the evaluation of which type of airline they are today. The outcome of this question will determine the roadmap that will need to be laid down to get to the point of highest success adoption of being able to implement predictive maintenance principles in the airline business.