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Predictive Thermal & Vibration Risk Monitoring in Rotary Equipment
A major power generation and water utility managing 240 high capacity centrifugal pumps, steam turbines, and industrial compressor units.
Runs onDrishti- catastrophic rotary equipment mechanical failures reduced
- 92%catastrophic rotary equipment mechanical failures reduced
- equipment maintenance expenditure reduced
- 34%equipment maintenance expenditure reduced
How the work runs
The pressure that made this worth automating, the steps the system runs, and what came out the other side.
Pressure & Trigger Points
- Turbine and pump maintenance was performed on rigid calendar intervals, resulting in unnecessary servicing of healthy assets and unexpected bearing failures.
- Vibration and bearing temperature anomalies developed rapidly between quarterly manual technician inspections, causing catastrophic shaft seizures.
- Replacing a damaged high pressure pump shaft cost $180,000 in emergency machining and 5 days of lost utility pumping capacity.
The run · 5 operational steps
Click any step to inspect telemetry signals, model reasoning, and governance gates.
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1
Continuous High Frequency Telemetry Processing
Drishti samples tri axial vibration accelerometers and bearing thermal sensors at high frequency rates continuously.
Input Signal:
Real-time operational telemetry & queue
Reasoning Pattern:
MCP grounded vector inference
Governance Gate:
Policy constrained with audit write-back
Verified Business Outcomes
- Catastrophic rotary equipment mechanical failures reduced by 92%.
- Equipment maintenance expenditure reduced by 34% by transitioning from calendar to condition based servicing.
- Extended average rotary asset operating lifespan by 3.5 years across the utility fleet.
Capabilities this relies on
- signal ingestion
- system connectors
- anomaly detection
- root cause reasoning
- alert routing
- in boundary deployment
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