Customer Story

27 failures detected. 31 hours of downtime prevented. Zero sensors on the asset.

The world's leading steel company deployed SAM4 across hot strip mill conveyors operating at extreme temperatures — where no sensor can survive. The result: 39 faults detected across two phases, some up to 7 months before failure.

Failures Detected

Hours Downtime Prevented

Rollers Monitored

Months Advance Warning

Overview

The world's leading steel company, operating in extreme conditions

ArcelorMittal is the world's leading steel and mining company, present in 60 countries with an industrial footprint in 18. Their hot strip mill in Ghent moves sizzling hot steel plates along conveyors — an environment where traditional sensors simply cannot survive.

By deploying SAM4 Health in the motor control cabinet, ArcelorMittal gained unprecedented visibility into assets that were previously unmonitorable, enabling proactive maintenance decisions.

The Challenge

Extreme heat makes conventional monitoring impossible

ArcelorMittal's rotating assets operate in harsh, high-temperature environments. Conveyors at the hot strip mill carry steel at extreme temperatures — conditions where vibration sensors and acoustic monitoring equipment fail. Without condition monitoring, failures in roller bearings and drive components caused unplanned production stops.

Manual inspection was dangerous and unreliable. The company needed a monitoring approach that worked from a safe distance, without placing hardware in the hostile production environment.

The Solution

Monitoring from the motor control cabinet — away from the heat

SAM4 installs inside the motor control cabinet, far from the hostile production floor. During a 12-month pilot on the hot strip mill conveyors, SAM4 detected 12 developing faults — all confirmed by maintenance engineers, some up to 4 months in advance.

Based on these results, ArcelorMittal expanded to 56 critical runout table rollers. SAM4 then detected an additional 27 failures, some up to 7 months before they would have caused downtime. This lead time enabled optimal maintenance scheduling, transforming downtime from a crisis event into a managed maintenance window.

[Image Placeholder: Hot Strip Mill Monitoring]

The Results

Early warnings, precise maintenance planning

31 hrs

Downtime Prevented

Estimated production loss prevented from 27 early detections on runout table rollers.

Total Faults Detected

Identified across pilot (12) and expansion (27) phases, all confirmed by inspections.

7mo

Maximum Lead Time

Some detections came up to 7 months before failure, enabling optimal intervention timing.

SAM4 gave us precisely the insights we needed. Thanks to SAM4, we can monitor assets that would otherwise remain unreachable.

Andy Roegis Industrial Digitalization Manager for Northern Europe, ArcelorMittal

Monitor your hardest-to-reach assets

Deploy SAM4 in extreme environments where traditional sensors fail, and get months of advance warning on developing faults.

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