Overview
BKOAI’s developed a simulation-aware FMEA system that combines Deep Search Agents with the Agent-as-a-Service (AaaS) framework to make risk analysis adaptive and data-driven
Challenge
Traditional FMEA processes are limited by:
- Static knowledge bases — updates require manual entry and are often delayed.
- Sequential analysis — investigations follow a fixed path, slowing decision-making.
- Lack of data integration — simulation results, maintenance logs, and sensor data remain disconnected.
- Reactive response — failure analysis occurs after the event rather than anticipating it.
Solution
BKOAI’s simulation-aware FMEA system uses a parallel, multi-agent architecture to analyze multiple data sources simultaneously. An Orchestrator Agent breaks a query into sub-tasks for:
- Graph Agent: Retrieves documented failure causes and effects from the FMEA database.
- Document Agent: Extracts relevant conditions from manuals and reports using semantic search.
- Log Agent: Reviews maintenance histories to find recurring failure patterns.
- Predictive Agent: Runs ML models on live sensor data to estimate failure probability.
A Synthesizer Agent then combines all findings into a unified analysis that blends structured knowledge, real-world data, and live predictions.
Key Benefits
- Dynamic Adaptation: The system continuously learns from new data and simulation results.
- Faster Decision-Making: Parallel agents operate simultaneously, reducing analysis time dramatically.
- Integrated Intelligence: Combines historical, operational, and predictive insights into one coherent workflow.
- Proactive Reliability: Moves FMEA from reactive reporting to forward-looking risk prevention.
