manufacturing
Operations
representative

At a Glance Multi Plant Operational Telemetry & Anomaly Detection

A global specialty chemicals manufacturer operating 14 continuous processing plants with over 80,000 IoT sensors tracking temperature, flow rate, pressure, and chemical acidity.

Runs onDrishti

unplanned reactor process shutdowns reduced: 72%unplanned reactor process shutdowns reduced
control room operator alarm fatigue reduced: 60%control room operator alarm fatigue 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

Plant operators monitored 25 separate SCADA and historian screens per control room, creating cognitive overload during critical process shifts.
Subtle process drift, such as minor heat exchanger fouling, went unnoticed across shifts until reactors exceeded critical thermal trip thresholds.
Unplanned reactor emergency shutdowns cost over $450,000 per incident in discarded raw materials and line decontamination downtime.

The run · 5 operational steps

Click any step to inspect telemetry signals, model reasoning, and governance gates.

scroll →

Unified Multi Plant Sensor Stream Ingestion

Drishti aggregates real time telemetry from OPC UA, MQTT, and legacy SCADA systems across all 14 manufacturing facilities.

Input Signal:

Real-time operational telemetry & queue

Reasoning Pattern:

MCP grounded vector inference

Governance Gate:

Policy constrained with audit write-back

Verified Business Outcomes

Unplanned reactor process shutdowns reduced by 72%, saving $3.2M annually.
Control room operator alarm fatigue reduced by 60% through single pane visual telemetry.
Early detection of process drift improved from 15 minutes to 18 hours prior to threshold breaches.

Capabilities this relies on

signal ingestion
system connectors
anomaly detection
root cause reasoning
alert routing
in boundary deployment

Related catalog agents