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Predictive maintenance is advancing quickly, and the aviation sector is learning how to apply it in practical and operationally meaningful ways. EXSYN remains closely involved in supporting airlines and MROs as they strengthen their data foundation and introduce predictive capabilities into daily workflows.
Our recent webinar walked through a full working day for a CAMO team and showed, step-by-step, how automation apps shift effort from manual firefighting to repeatable, auditable processes. Sander de Bree, Robert Vermeij and Carlos Llopis led the session with live demos of the EXSYN Apps and ran real workflows records so engineers could see exactly how decisions are made and validated.
EXSYN has launched a new modular platform that unites its established products and services under one framework designed to deliver aviation data continuity. Each app can now be licensed separately. Operators can start with the apps that solve today’s most pressing challenges and expand step by step, without large-scale system overhauls.
The session addressed key challenges that CAMO teams face, including manual data entry, trust issues with existing data, and the risk of human error. Sander and Ralph conducted live demonstrations showcasing automation solutions designed to enhance efficiency
Predictive efforts stall at handovers. The cure is a single flow: OEM library for documented truth, AD integration for a shared regulatory picture, M&E health checks and airworthiness reviews for validated data. Reliability and engine health then run on leg- and serial-linked signals, refreshed by a scheduler. Result: stable KPIs, cleaner trends, fewer false positives.
Predictive maintenance succeeds only when people believe what the data is telling them. Engineers, reliability analysts, and CAMO staff do not reject models because they dislike innovation. They pause because their lived experience has taught them that small inconsistencies grow into audit findings, deferred defects, and avoidable AOGs.
Predictive maturity starts with disciplined reliability data, not telemetry or algorithms. Clean and connected M&E records create the only foundation models can stand on. Without that layer, prediction turns into noise instead of operational intelligence.