DRAIDIS Use Case
Use equipment telemetry to flag degradation and plan maintenance earlier
The Challenge
Equipment readiness depends on finding degradation early enough to inspect, repair, and source parts. In the field, maintainers often work with incomplete telemetry, limited history, and more assets than experienced specialists can inspect continuously.
How DRAIDIS Solves It
DRAIDIS BRAVO and CHARLIE bring selected CAN bus data, vibration, thermal, and acoustic observations into an equipment-health workflow. Models flag possible degradation and show maintainers the supporting evidence. During the pilot, your team measures warning time and alert quality separately for each asset, sensor setup, operating condition, and failure mode. Your team controls whether maintenance and operating records may be used to evaluate or improve a model.
Sensor Integration
Connect selected vehicle CAN bus signals and external vibration, thermal, and acoustic sensors on the components your team wants to monitor.
Build the Baseline
Use reviewed operating history to establish a baseline for vibration, temperature, sound, and other selected signals on each monitored component.
Continuous Monitoring
Compare selected sensor streams with reviewed baselines. Models flag possible deviations and provide supporting evidence for maintainer review.
Possible Failure Mode
Suggest possible causes such as bearing wear, fluid contamination, electrical degradation, or structural fatigue, with confidence and evidence for maintainer review.
Warning Window
Estimate a maintenance warning window with uncertainty rather than a fixed failure date, and update it as new observations arrive.
Maintenance Recommendation
Suggest an inspection or procedure, possible parts, estimated labor, and urgency for maintainer review.
Parts Demand Recommendation
Prepare a parts-demand recommendation for review, or route it through a workflow that follows your procurement controls and approval limits.
Fleet Comparison
Compare health indicators across participating assets to surface possible batch, environment, or usage patterns for maintenance planners.
Deployment Configuration
This reference design spans 2 DRAIDIS tiers. The pilot defines and tests the coverage needed for your environment.
DRAIDIS BRAVO
Connects selected vehicle and equipment telemetry to a local health-monitoring workflow for maintainer review.
DRAIDIS CHARLIE
Aggregates selected health indicators across participating assets and prepares maintenance and parts-demand recommendations for planners.
Key Capabilities
Purpose-built AI capabilities for this mission set.
Multi-Sensor Health View
Bring selected CAN bus, vibration, thermal, and acoustic observations together for maintainer review.
Early-Warning Testing
Measure usable warning time by asset, sensor, failure mode, and operating condition.
Failure Mode Decision Support
Present possible failure modes with confidence and evidence so maintainers can choose the next inspection or repair.
Parts Demand Workflow
Route parts-demand recommendations through the sustainment review and approval process your organization uses.
Fleet-Level Comparison
Surface possible batch, environment, and usage patterns across participating assets for planner review.
Maintainer Decision Support
Give maintainers source-linked inspection suggestions and evidence without replacing their diagnosis or repair authority.
Performance Metrics
Measure
Asset-specific warning horizon
Baseline
Readiness impact
Baseline
Unplanned-downtime impact
Baseline
Parts-availability impact
Plan a Pilot for This Workflow
Review how DRAIDIS could support predictive maintenance in theater, then define the interfaces, data, hardware, controls, and operating conditions your team wants to test.