The delays caused by faulty aircraft systems (e.g. auxiliary power units and air conditioning units) are a major inconvenience to air travelers and an ever-present headache for airline operators. They cause unscheduled aircraft groundings and frustrate customers. In recent years, some operators have taken a more progressive approach to these unscheduled maintenance events, establishing preventative maintenance programs to drive higher on-time rates.
The emerging concept of “predictive maintenance” promises to both diagnose aircraft problems and to make predictions about future events. However, assuming you gather data, using this data can be a major challenge as one needs to
- Sift through very large data sets for every flight
- Deal with incomplete data, as many systems have data that is not captured by the traditional ACMS (Aircraft Condition Monitoring System)
Recently, an operator realized a successful predictive maintenance program required data that was not captured by traditional onboard systems (e.g. pressure, temperature and vibration). The new data could then be used to significantly enhance the analysis process, producing accurate maintenance forecasts and predicting potential service disruptions.
The data capture device would need to be
- Highly configurable
- Capable of adapting to evolving requirements
- Easily integrated with existing aircraft systems with very low impact
- Capable of operating in unpressurized areas without modification
An adaptable data capture architecture was created that is capable of truly gathering predictive trend data on passenger aircraft. This architecture is ideally suited to address evolving predictive maintenance requirements and is able to incorporate new measurement requirements across multiple platform types – without major equipment developments. Read about the solution Curtiss-Wright developed for the commercial flight operator and the results achieved in our case study - download the case study to learn more.