Global Manufacturer Cuts Unplanned Downtime 31% with Predictive Maintenance
Industrial IoT + ML on Azure delivered predictive maintenance across 14 plants — saving $19M in lost production hours.
A global industrial manufacturer with 14 plants across three continents was losing $60M+ annually to unplanned line stoppages. Maintenance was reactive — fix-on-failure with weekly preventive sweeps — and OEM-supplied condition data sat in vendor portals nobody on the floor logged into.
Apptad built a unified condition-monitoring platform on Microsoft Azure: IoT Hub for sensor ingestion, Microsoft Fabric for the lakehouse, Azure ML for time-series anomaly detection, and Power BI dashboards on the floor. We trained models per asset class — pumps, gearboxes, compressors — and integrated alerts directly into the CMMS so maintenance leaders saw work orders, not raw warnings.
Unplanned downtime dropped 31% across the rolled-out plants in year one. The CFO quantified $19M in recovered production hours and 22% lower spare-parts inventory carrying cost. Maintenance leaders moved from reactive to scheduled work, with first-time-fix rate up 40 points.
The Numbers Behind the Story
Built On
The platforms and partners that powered this engagement. Where Apptad has a dedicated alliance, the chip links to our partnership page.
“We stopped fighting fires. The line leaders now plan maintenance the way our schedulers plan production runs — with data we trust.”
