Azure · Manufacturing
IIoT + predictive maintenance across 12 plants cut unplanned downtime 27%.
We deployed IIoT ingestion and predictive maintenance ML across 12 plants on Azure — unplanned downtime cut 27% in the first year.
[Unplanned downtime]
-27%
[Plants online]
12
[Yield insight]
2×
[ The Problem ]
Where the business was stuck.
Unplanned downtime on legacy plant equipment eroded margin plant-by-plant.
[ Key Challenges ]
- ▸Plants running heterogeneous OT stacks
- ▸No unified telemetry across sites
- ▸Reactive maintenance model
Our approach
How we engineered
the outcome.
STEP 01
Edge-to-cloud pipeline via Azure IoT Edge + IoT Hub
STEP 02
Digital twin of each production line
STEP 03
ML models for failure prediction with maintenance-scheduler integration
[ Solution highlights ]
Delivered — measured — in production.
- ✓Unified telemetry across 12 plants
- ✓Downtime cut 27%
- ✓Maintenance scheduled predictively
[ Tech stack ]
Built on Azure.
Azure IoT Hub
IoT Edge
Synapse
ML
"
Our line supervisors get failure warnings before the machine even shudders.
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