Waites Helps Owens Corning Avoid $11M in Potential Losses

When Owens Corning’s ball mill began showing signs of failure at its Tessenderlo Plant, Waites’ AI-powered preventive maintenance system detected the issue before a catastrophic breakdown. The system saved over $11 million in potential production losses, repair costs, and downtime by preventing an unplanned shutdown.
This success underscores the power of AI-driven predictive maintenance in safeguarding critical manufacturing assets.
With 24 global facilities now equipped with Waites’ monitoring solution, Owens Corning has transformed its maintenance strategy into proactive, data-driven decision-making.

Owens Corning is a global leader in building and construction materials. It provides high-quality products for residential, commercial, and industrial applications worldwide. Founded in 1938 and
headquartered in Toledo, Ohio, the company’s unwavering commitment to innovation and operational excellence has fueled its growth to approximately 25,000 employees across more than 30 countries.
This expansive presence supported $11 billion in sales for 2024, underscoring its dedication to sustainability, innovation, and operational excellence.

CHALLENGES AND PAIN POINTS

In an effort to transition from reactive to proactive maintenance, Owens Corning sought a partner for wireless condition monitoring of critical assets. The company required a standardized, scalable solution that could be  rapidly deployed across its plants without the need for extensive cabling or IT infrastructure.
As part of its journey to predictive maintenance, Owens Corning evaluated 40 condition monitoring solutions before shortlisting a select few. A 90-day proof of concept at a South Carolina plant solidified Waites as the optimal choice due to its actionable alerts, rapid ROI, and scalable coverage.
During the trial, Waites identified critical lubrication and alignment issues — particularly at motors’ non-drive ends (NDE) — that had previously gone unnoticed but represented a significant share of anomalies.
Over 70% of flagged action items focused on cleaning, alignment, and extending equipment life. This demonstrated the value of proactive maintenance in reducing downtime, increasing throughput, and enhancing equipment reliability.

“Instead of reacting to a crisis, we integrate repairs into our existing maintenance schedule — often preventing a complete shutdown.”
“Before using Waites, we relied on periodic inspections and manual lubrication. Unplanned downtime caught us off guard far too often, especially with equipment where the original manufacturer’s lead
times can be months.”

Jelle Willems -Reliability Engineer at Owens Corning

Recognizing the need for a standardized, proactive approach, Owens Corning sought a solution capable of delivering real-time data and immediate insights, enabling targeted repairs before serious failures occurred.

SOLUTION & IMPLEMENTATION
Owens Corning selected Waites as its corporate solution and has expanded the program to 24 facilities worldwide. Wireless Waites sensors were installed to track vibration and temperature on critical equipment, such as fans, conveyors, and large ball mills.

KEY FEATURES
• Wireless Sensors:
Installed on critical assets to capture real-time operational data.
• AI-Driven Data Analysis:
The system analyzed sensor readings to detect early signs
of bearing wear, misalignment, and lubrication issues.
• Proactive Alerts:
Maintenance teams received immediate notifications when
anomalies were detected, allowing them to investigate promptly.
• Expert Support from Waites’ Analysts:
Waites’ analysts review system data, interpret complex findings,
and provide specific, actionable recommendations

By replacing multiple local systems and route-based checks with Waites’ wireless sensors, Owens Corning gained real-time data collection, enterprise-wide visibility, and instant alerts, enabling a decisive shift toward proactive maintenance.
Owens Corning significantly reduced unexpected downtime by moving away from breakdown-driven repairs and toward a data-centric model, increasing equipment reliability across multiple divisions.

On February 26, 2024, Owens Corning’s Tessenderlo Plant in Belgium received an alert on Ball Mill #5 — a critical “A Equipment” asset operating for over 40 years. Real-time Waites data showed a significant temperature spike at the non-drive-end (NDE) main bearing, prompting an immediate inspection.

TESSENDERLO BALL MILL INCIDENT: AN $11M SUCCESS

TECHNICIANS DISCOVERED
• A cracked NDE shaft and excessive run-in
• A damaged white metal bearing shell
• Inadequate lubrication in the oil-bath system

Otherwise, the facility would have risked an unplanned, prolonged shutdown with severe production losses.
The maintenance team replaced the end shaft and bearing shell, ordered a second shaft to keep in stock, and installed an automatic lubrication system to maintain consistent
oil levels — critical for preventing repeat issues.

Avoided Downtime: 5,376 hours
Production Losses Prevented: $9,281,395.20
Repair/Labor Savings: $1,960,000
Total Avoided Costs: $11,241,39

“From an ROI standpoint, installing the Waites system was one of the easiest decisions we’ve made. It’s a small investment compared to the $11 million we saved.”
Jelle Willems

CONCLUSION
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Owens Corning’s experience with Waites illustrates how early detection and proactive intervention can shift a reactive maintenance model into one that prevents major failures in advance. By identifying the cracked ball mill shaft before it failed, the company saved over $11 million in potential losses and sustained critical production lines.
Moreover, lessons learned at Tessenderlo prompted Owens Corning to install automatic lubrication systems on ball mills throughout its operations. Combined with Waites’ AI-driven analytics and real-time monitoring, these changes continue to standardize best practices, reduce unplanned downtime, and drive a significant enterprise-wide ROI.
With corporate buy-in, Owens Corning expanded Waites’ system well beyond its initial pilot, embracing a global rollout. The company now stands at the forefront of manufacturing innovation — leveraging full-spectrum data, expert analyst insights, and progressive maintenance practices to secure a more resilient and sustainable future.