Aerospace Structural Life Prediction AI
This AI solution uses advanced machine learning and graph-based models to predict structural behavior, degradation, and remaining useful life of aerospace and defense components and systems. By fusing operational data, material properties, and structural simulations, it enables precise life estimation, early fault detection, and targeted maintenance. Organizations reduce unplanned downtime, extend asset life, and lower maintenance and sustainment costs while improving safety and mission readiness.
The Problem
“Predict aero-structural degradation and RUL from ops data + materials + simulation”
Organizations face these key challenges:
Unplanned removals and AOG/mission aborts from undetected fatigue or rotor/airframe degradation
Over-maintenance due to conservative lifing assumptions and fixed interval schedules
Inconsistent life estimates across fleets because operational usage and environments vary widely
Slow engineering turnaround: manual analysis across sensor logs, inspections, and simulation results