- Research Article
1
- 10.9790/1684-2205012946
Enhanced FMEA Methods For Proactive Bridge Failure Risk Analysis
- Sep 01, 2025
- IOSR Journal of Mechanical and Civil Engineering
- Abiola Ajayi
The structural integrity of bridges is critical to ensuring public safety, economic stability, and uninterrupted transportation networks. Traditional risk assessment approaches, such as visual inspections, load testing, and Failure Mode and Effects Analysis (FMEA), have historically provided the foundation for maintenance decisionmaking. However, these methods often face limitations in dynamic operating environments due to subjectivity, static scoring frameworks, and insufficient integration of real-time monitoring data. This study proposes an Enhanced FMEA framework that integrates Structural Health Monitoring (SHM) data—collected through advanced sensing technologies, Internet of Things (IoT) devices, unmanned aerial vehicles (UAVs), and fiber optic systems—into risk assessment processes. Quantitative metrics, statistical methods, and machine learning models are applied to improve predictive accuracy, while fuzzy logic and Bayesian networks address uncertainties in scoring. Comparative analysis between conventional and enhanced FMEA demonstrates superior performance of the integrated approach in terms of predictive reliability, reduction of false positives and negatives, and optimization of maintenance schedules. Case applications in bridges and related infrastructure reveal the scalability and adaptability of the proposed model. Findings underscore the potential of data-driven FMEA to transform infrastructure risk management, enabling proactive maintenance and extending the operational lifespan of critical assets
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