Simulation-Aware FMEA Analysis
BKOAI developed a simulation-aware FMEA system combining Deep Search Agents with the Agent-as-a-Service (AaaS) framework to make risk analysis adaptive and data-driven
Goals
- Transition from static, manual risk analysis to dynamic, data-driven reliability.
- Accelerate decision-making through parallelized failure analysis.
- Integrate historical, operational, and predictive data into one workflow.
- Shift FMEA from reactive reporting to proactive risk prevention.
Challenges
- Traditional FMEA relies on static knowledge bases that require manual updates.
- Sequential investigations follow fixed paths, slowing decision-making.
- Siloed data prevents integration of simulations, maintenance logs, and live sensors.
- Failure analysis often occurs only after events rather than anticipating risks.
Solutions
- Deployed an Orchestrator Agent to run parallel, multi-agent analysis workflows.
- Integrated Graph, Document, Log, and Predictive Agents for comprehensive analysis.
- Utilized a Synthesizer Agent to unify knowledge and deliver actionable predictions.
- Combined FMEA records, simulation results, maintenance histories, and live sensor data.
Results
- Enabled dynamic adaptation by continuously incorporating new data and simulation results.
- Reduced analysis timelines significantly through simultaneous agent execution.
- Shifted reliability workflows from reactive reporting to proactive risk prevention.
- Delivered integrated intelligence across historical, operational, and predictive insights.
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