Domtar Uses AI to Boost Efficiency and Quality in Sawmills

Published in 23 de November de 2025 by g7

Domtar is integrating artificial intelligence at the core of its wood operations. The company’s sawmills are increasingly leveraging AI modeling and machine learning to transform the way lumber is assessed, graded, and optimized, achieving significant gains in both product quality and operational efficiency.

For an industry already known for resource efficiency, this evolution is remarkable. In Domtar’s sustainable operations, every part of the tree is used – from lumber to pulp to biomass. With AI, the company is taking this optimization to the next level.

Over the past two years, Domtar has integrated AI modeling at several sites, including mills in Glenwood (Arkansas), Cross City (Florida), Thunder Bay and Atikokan (Ontario), and Normandin, La Doré and Senneterre (Quebec). These models enable real-time visual inspections and automated lumber grading, identifying defects with a level of speed and accuracy far beyond human capacity.

“AI allows us to be more precise and consistent,” says Carl Lévêque, Quality Superintendent for Domtar’s planer mills. “There’s a lot less waste.”

Precision Meets Performance

Once the boards arrive at the planer mill, advanced sensors and cameras scan them from multiple angles. The AI system analyzes wood composition, detecting inconsistencies such as discoloration, internal separation, or insect damage. This automated process replaces manual inspections, ensuring greater accuracy and consistency across every batch.

AI models are custom-designed for each product’s specifications. For instance, the Normandin mill alone produces 15 unique lumber products, each meeting strict client and building code requirements. With AI, Domtar maximizes the value of every piece of wood while maintaining compliance with quality standards.

Humans + Machines = Smarter Outcomes

Domtar’s approach doesn’t remove people from the process – it enhances them. Engineers and technicians train the AI, tagging image data and refining models through ongoing tests. Optimization supervisors run field tests regularly to ensure that results match real-world expectations.

When AI occasionally flags acceptable wood as defective, employees collaborate with suppliers to adjust the model, reducing false rejections and minimizing waste.

This synergy between technology and human insight ensures continuous improvement and reinforces Domtar’s commitment to sustainable forestry.