Pulp & Paper Reliability: Autonomous Lubrication Intelligence for Chip Conveyor Bearings with AI LubeMatrix™

A leading pulp and paper mill relied on a chip conveyor that feeds
material directly into the digester - an asset with slow-speed
bearings constantly exposed to debris, moisture, and high load.
These conditions made traditional lubrication ineffective and
unpredictable.
By deploying AI LubeMatrix™, powered by a dedicated ultrasound
sensor providing live friction data and connected into the Industrial
Matrix AI Suite™ ecosystem, the facility transitioned from manual
and time-fed greasing to fully autonomous, condition-based
lubrication.
The result: extended bearing life, zero lubrication-related failures,
and $20,000+ in verified annual cost avoidance.

The Challenge

The chip conveyor operates 24/7, and bearing performance directly influences upstream and downstream production. The mill faced:

  • Bearings located behind guards, difficult to lubricate consistently

  • Time-fed lubricators unable to adapt to changing loads

  • Moisture and debris accelerating wear

  • Recurring bearing failures

  • High-risk unplanned stoppages impacting the entire fiber line

  • No real-time visibility into lubrication quality

Without continuous insight, lubrication failures were inevitable.

The Solution - AI LubeMatrix™ Powered
by Ultrasound Sensor Intelligence

An ultrasound sensor was installed directly on the conveyor bearings, providing real-time
friction and lubrication film analysis. This live ultrasonic data drives AI LubeMatrix™, enabling
the system to:

  • Monitor friction continuously

  • Detect the earliest rise in friction through ultrasound signatures

  • Trigger lubrication cycles only when needed

  • Deliver precise grease quantities matched to operating conditions

  • Verify lubrication effectiveness through post-lube ultrasound readings

  • Log every event for full traceability

The system operates seamlessly inside the Industrial Matrix AI Suite™ ecosystem, allowing teams to view lubrication performance across assets in one unified environment.

Findings & Action Plan

Phase

Insight

Action

Result

Detection

Ultrasound readings showed friction rising during load cycles.

Autonomous lubrication activated exactly when required.

Friction stabilized immediately.

Verification

Post-lube ultrasound readings confirmed lubrication success.

Any unresolved anomalies flagged for inspection.

Teams shifted attention to true mechanical concerns.

Stabilization

Continuous ultrasound data showed consistent lubrication film quality.

No manual greasing required.

Bearing life extended; reactive PM eliminated.

Total ROI

Metric

Before Monitoring

After Monitoring

Verified Impact

Downtime Exposure

High risk of failure

Zero lubrication-related failures

Significant downtime avoided

Lubrication Method

Manual / time-fed

Autonomous, ultrasound-driven

Accurate lubrication every time

Bearing Life

Average

Extended by 30–50%

Lower replacement cost

Annual Cost Avoidance

-

$20,000+

Verified

Strategic Insights

Ultrasound-driven lubrication is essential for bearings exposed to harsh contaminants.

Condition monitoring exposed patterns traditional PMs could never detect.

Data-driven lubrication preserved bearings, reduced waste, and improved energy stability.

The mill gained a reliable, predictable lubrication process backed by real-time data.

Long-Term Impact

Following this success, the facility expanded its Industrial Matrix
approach across:

Conveyors

Refiners

Press rolls

Chipper and sawmill bearings

Long-term benefits included:

Fewer lubrication-related failures

Reduced grease usage and environmental waste

Higher equipment availability

Consistent lubrication quality across all shifts

Stronger OEE across production lines

Conclusion

AI LubeMatrix™, powered by continuous ultrasound sensor intelligence and operating within the Industrial Matrix AI Suite™ ecosystem, transformed lubrication from a manual task into a precise, autonomous reliability function.
Every lubrication cycle is now data-driven, verified, and optimized, delivering measurable ROI and strengthening production stability.

Make lubrication autonomous.
Make reliability predictable.