PROGNOS
In-house AI and big-data predictive maintenance suite that monitors aircraft, engine, APU, and inventory health to anticipate failures up to 50 flights before they occur.
PROGNOS is AFI KLM E&M's own predictive maintenance platform, developed internally and commercialised to external operators. It ingests continuous sensor data streams — thousands of parameters per flight generated by onboard systems — and applies proprietary machine-learning algorithms to detect degradation signatures early enough for planned maintenance to replace reactive line fixes. The headline capability is failure prediction up to 50 flights in advance, shifting the maintenance event from an AOG scenario into a scheduled shop visit.
The suite is modular, comprising four integrated products: PROGNOS for Aircraft (airframe systems and components), PROGNOS for Engine (gas-path and mechanical health across multiple engine families including the LEAP-1A and Trent XWB), PROGNOS for APU (auxiliary power unit monitoring with per-stopover data upload), and PROGNOS for Inventory (demand forecasting tied to predicted failure patterns, reducing both stockout and excess holding risk). Each module can be adopted independently or as a combined programme.
Data is collected and transmitted daily — inflight and during turnarounds — and analysed by AFI KLM E&M's qualified engineering team, who act as an extension of the operator's maintenance control function rather than leaving interpretation to the airline alone. Over 1,300 engines are currently under PROGNOS monitoring across multiple operators. Deployed customers publicly include Virgin Atlantic (17 Boeing 787s) and Norse Atlantic Airways (12 Boeing 787-9s).
For Gulf and Middle East operators running long-haul 787 or A380 fleets in high-frequency, high-temperature environments, reducing unplanned AOG events has an outsized revenue impact. PROGNOS targets precisely that exposure.
Technical specifications.
| Failure prediction horizon | Up to 50 flights in advance |
| Engines under monitoring | >1,300 |
| Suite modules | Aircraft / Engine / APU / Inventory |
| Engine families supported | LEAP-1A, Trent XWB + others |
| Data collection frequency | Daily — inflight and turnaround |
| Aircraft types deployed on | Boeing 787 (confirmed), Airbus and Boeing fleets broadly |
Use cases.
- ›Long-haul widebody operators (787, A330, A380) seeking to convert unplanned AOG events into scheduled maintenance interventions
- ›Engine health management for carriers under ACMI or power-by-the-hour contracts where unplanned shop visits carry direct financial penalties
- ›APU monitoring for airlines with high-frequency short-haul cycles where APU utilisation and wear rates are elevated
- ›Predictive inventory management to align spare parts provisioning with forecast failure demand rather than historical consumption
- ›Digital MRO transformation programmes where the airline wants an outsourced analytics capability without building an in-house data-science team
- ›Gulf and Middle East carriers operating 787 fleets in extreme-temperature environments where thermal degradation accelerates component wear