- 12 Jan 2022
- Dave Higdon
- Aircraft MRO
Though aircraft maintenance accounts for a substantial proportion of an aircraft owner’s operating costs, and can ground an aircraft unexpectedly, these can be limited if managed correctly. Sherryn de Vos explores the world of predictive maintenance…
Poor maintenance planning has real consequences for aircraft owners, keeping the aircraft grounded for unnecessary repairs, reducing the lifespan of parts, and heightening maintenance costs.
Is predictive maintenance the answer? Are private airplane owners and operators able to get a firmer grasp of their maintenance needs and countering these issues? David Purfurst, Global Pre-Sales Director from Rusada Aviation Software believes so…
What’s Predictive Maintenance?
Essentially, the concept of predictive maintenance in private aviation involves the use of information – such as sensor data and maintenance logs – to predict an aircraft’s maintenance needs ahead of time, helping aircraft owners and operators improve their maintenance planning.
The last decade has spurred on a number of revolutionary developments in the industry, including improved computational power, data storage capability, as well as the overall amount of data and data parameters the industry can look to.
Most of this can be attributed to the widely adopted use of sensors on aircraft and high-quality data routers. From there have come numerous advancements such as machine learning and Artificial Intelligence.
Computers learn to recognize advanced patterns through large data sets and streamline maintenance planning. According to Purfurst, however, predictive maintenance isn’t a particularly new concept – in fact it’s been around for some time now.
The origins of predictive maintenance began with condition-based maintenance but is now moving into more of an AI/machine-learning model.
Engine and Helicopter OEMs have been dipping into predictive maintenance for years now and have either developed their own sensor systems or partnered with sensor providers, to capture performance data for analysis.
The adoption of predictive maintenance by the rest of the industry, however, has been quite slow due to several factors, ranging from legacy aircraft not having the systems required to capture the data, to the OEMs control of the data and gaining access to it, and aviation authorities granting approval of predictive maintenance models.
The Benefits of Predictive Maintenance
Among the greatest benefits of predictive maintenance is the cost reduction of aircraft maintenance for operators who use it.
That’s because the insights provided by predictive maintenance allow operators to better calculate the useful life of a component (for example), leading to more informed maintenance and inventory planning. Sensors are also able to detect possible component defects in advance of an issue occurring, heavily reducing the number of Aircraft on Ground (AOG) events.
While there are several key considerations regarding an owner’s/operator’s use of predictive maintenance, the first thing to consider is technology. Operators’ fleets need to have the systems in place to capture the data needed for analysis, as well as an agreement with the OEM that allows for the easy (and secure) sharing of data.
Next is the cooperation between operators, OEMs, and the aviation authorities, which ensures all parties understand and agree on the safety benefits and risks.
For operators to truly realize the benefits of predictive maintenance, the industry needs to work on standardizing the data integration between onboard systems and maintenance management systems, such as the ENVISION software Rusada produces.
This will avoid the need for bespoke integrations between system providers, and allow for software solutions to incorporate more sensor findings into maintenance planning functionality.
Predictive Maintenance Has Longevity
Predictive maintenance is undoubtedly the future within Business Aviation, though adoption will continue to be slow for the time being. The next step will most likely be a transition to a hybrid model with both preventative and predictive maintenance being used alongside each other.
Purfurst admits that he’s not sure there will ever be a 100% predictive model across the industry, but it will certainly become more of a standard practice going forward, aided by the increased utilization of new generation aircraft that have the required sensors already in place.
Because predictive maintenance for aircraft can aid in determining the right moment to replace a part, it has a knock-on effect on the supply chain – and with companies able to predict part failures up to 15 days in advance, the results have been profound.
With predictive maintenance establishing itself solidly as the future for aircraft maintenance, it is now just up to the suppliers and operators to keep up with it.