How Trend Analysis Informs Predictive Aircraft Maintenance

Feb. 6, 2026

Upholding safe business aircraft operations through effective predictive maintenance is much more than simply collecting data. Through this sophisticated technology, operators and maintenance teams are using trend analysis to determine when to intervene, plan maintenance events and reduce unexpected downtime.

From gradual changes in engine performance to early signs of system wear, the real challenge is knowing when to take action. Now, AI-assisted computer algorithms are being developed to predict when aircraft parts will need to be replaced before they fail.

NBAA Maintenance Committee member Leonard Beauchemin, managing director of AeroTechna Solutions, explained that predictive maintenance can serve two purposes. First, the establishment of aircraft “airworthiness” in real time on a continuing basis using off-boarded performance data. This is the objective of FAA Advisory Circular 43-218.

“This process of aircraft integrated health management falls under the scope of ‘condition-based maintenance’ (CBM),” Beauchemin said. “CBM is not a task-based approach, but instead a process-based activity.”

Second, according to Beauchemin, predictive maintenance enhances the operator’s ability to use off-boarded data to determine a component’s performance and meet their operational reliability standards for that specific operator.

“Just because a component is not performing to the operator’s reliability standards, that doesn’t make the aircraft unairworthy per the type certificate holder’s aircraft maintenance manual limitations,” Beauchemin said.

When Data Becomes Actionable

NBAA member Suresh Narayanan, CEO at Dallas-based Jets MRO, believes that the transition from monitoring to action typically occurs when predictive models indicate a 70-80% probability of component failure within a defined timeframe, when trending data approaches manufacturer-specified limits, or when multiple correlated parameters show concurrent degradation, suggesting systemic issues.

“The key differentiator is risk assessment – we evaluate not just the severity of the trend, but also the criticality of the affected system, operational impact of potential failure and available lead time for intervention,” Narayanan said.

Beauchemin suggested that any party using trend data will have to determine the values for establishing “alert level” notifications or comparison assessment values. “Alert” notifications should include instructions on the actions to be taken.

“These actions are developed based on one of the two objectives, ‘airworthiness’ or ‘reliability,’” said Beauchemin. “Alert levels could also be coded by severity, similar to a crew alerting system.”

For NBAA member Joe Peebles, AOG specialist at Georgia-based JP Aerotechnics, a data trend becomes actionable when it moves from being “interesting” to being something that could realistically turn into an AOG situation.

“We’re looking for trends that are consistent over time, getting worse and tied to systems that directly affect dispatch reliability,” Peebles said. “Things like engines, electrical power, environmental systems or hydraulics.”

Translating Data Into Operations

Turning trend data into operational action is much more than simply monitoring dashboards. It involves coordination between maintenance planning, dispatch, scheduling and frontline technicians to ensure early warnings translate into timely decisions.

Peebles said his team’s role is to help the operator turn it into a controlled maintenance event instead of a reactive road trip.

“We work with maintenance control and scheduling to line the job up with a planned stop or overnight, so the airplane comes to us on purpose, not because it broke somewhere inconvenient,” he said.

Similarly, Narayanan thinks the integration with operations occurs through automatic notifications that allow maintenance planning to adjust scheduled events, scheduling teams to determine optimal service windows, and dispatch to implement operational limitations or enhanced monitoring requirements until resolution.

“Critical to our process is comprehensive communication tracked through integrated software platforms that ensure predictive findings translate into coordinated action across all departments,” Narayanan said.

Reliable Early-Warning Indicators

Not all aircraft data provide the same operational value. Some systems offer clear, repeatable signs of developing issues, while others are harder to interpret in real time.

For Narayanan, engine systems consistently provide the most reliable predictive data through full authority digital engine control (FADEC)- generated parameters, including exhaust gas temperature (EGT), fuel flow, oil temperature and pressure, and vibration levels, with the maturity of engine health-monitoring algorithms enabling highly accurate trend analysis.

“When data suggests a component might fail in the coming flight hours, the decision to pull the aircraft early usually comes down to mission risk,” said Peebles. “If the airplane is heading into remote locations, tight schedules or high-visibility trips, we’ll often recommend addressing it sooner.”

Cost Implications

Early intervention usually means spending money sooner than planned, but unplanned failures tend to be far more expensive. Beyond the direct repair cost, operators often face aircraft downtime, schedule disruptions, crew repositioning and lost revenue.

While an early part replacement may feel premature, Peebles said it’s usually cheaper than emergency travel, expedited shipping, overtime, lost trips and the reputational hit of a grounded aircraft.

“We’re not just saving parts — we’re protecting their schedule and their brand,” said Peebles.

Impact on Reliability and Uptime

“Predictive maintenance has fundamentally transformed operational performance,” said Narayanan, “with data showing 35-40% reductions in unscheduled maintenance events and dispatch reliability improvements from 97.5% to 99.2% for aircraft with comprehensive monitoring.”

Over time, predictive maintenance helps support better dispatch reliability and fleet availability because his team is doing more work in planned environments and less in parking lots at midnight.

However, it “only works when the data actually drives planned action — otherwise it’s just interesting graphs while the airplane is still one flight away from an AOG,” said Peebles.

Looking to the future, Beauchemin recommends maintaining prudence. “Our industry, as it should, will be very cautious to not elevate the acceptable level of risk beyond the current levels we achieve today with our classic methods of aircraft technical airworthiness management.”