A paper company boosted AI sensor efficiency with a simple change in management

Matthew McLaughlin, a reliability engineer at Domtar, faced a challenge when a motor at the company's Kingsport, Tennessee, mill failed. His manager asked him to review data from 450 sensors, but McLaughlin estimated it would take 32 weeks to analyze. As AI adoption grows in manufacturing, companies must adapt to maximize their investments. Domtar had already implemented AI-assisted sensors from Waites Sensor Technologies to monitor equipment vibrations and prevent breakdowns. However, the company needed a new way to manage the data. McLaughlin decided to engage more with Waites, leading to weekly data sharing and improved AI performance. Rob Ratterman, CEO of Waites, emphasized that AI alone isn't enough; human expertise is crucial. Domtar now uses 748 sensors, with Waites detecting issues like motor cracks or misalignment up to six months in advance. This has allowed the company to reduce unplanned downtime by 1,546.65 hours. McLaughlin also noted that trust in the system has grown to the point where multimillion-dollar decisions are now based on Waites data. The system has also led to reduced maintenance costs and fewer part purchases, thanks to continuous monitoring and AI-driven insights.