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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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