reliability of aircraft avionics systems using risk assessment models

Avionics systems, a critical component of civil aircraft, are essential for ensuring flight safety, operational efficiency, and compliance with regulatory standards. given their increasing complexity and extensive software integration, the need for robust, evidence‑based reliability assessment frameworks has intensified. this study introduces the first practically implemented and cross-validated framework integrating frat, fmea, and fta sequentially on real-world boeing 737 data (2018–2023), bridging operational risk assessment with root-cause analysis in a novel data-driven manner. in this study, we present a practically implemented, integrated framework combining the flight risk assessment tool (frat), failure modes and effects analysis (fmea), and fault tree analysis (fta) in a sequential and interconnected process. first, fmea was applied to real‑world failure records of boeing 737 avionics (2018–2023) to prioritize critical failure modes using risk priority numbers. the outcomes were then analyzed using fta diagrams to identify root causes, followed by frat evaluations under level d flight simulations to assess operational risk. a case study demonstrated that the navigation system failure rate decreased from 12% to 4%, mean time between failures (mtbf) increased from 2,000 to 3,200 hours, and annual maintenance costs dropped by 22%. these improvements were achieved through software updates compliant with do‑178c standards, installation of redundant sensors, and intensive crew training. the framework was validated using both historical data and simulation results, ensuring accuracy and applicability. this research provides aviation designers and safety engineers with a proven methodology to enhance avionics reliability, reduce downtime, and align with international aviation safety standards. future work could extend this framework to ai‑based avionics and 5g‑enabled flight control systems, with emphasis on cybersecurity and global interoperability.