What Mills Risk Without High-End Defect Detection

28.07.2025
RAUTE GROUP

Stop losing millions. See how AI defect detection is transforming veneer production and profits.

Imagine losing up to €2 million each year because tiny veneer defects slip through your current mill system undetected. What if you could catch every harvester mark, birch bark inclusion, and sound knot before it ever reaches the lay-up line? 
 
High-end defect detection, such as AI-powered analyzers, makes that possible. It not only turns marginal yield gains into significant bottom-line impact and rapid ROI, but also ensures precise veneer control, minimizing the risk of defects slipping into the wrong places and causing costly rework. 
 
Rapid Yield Gains, Simulation, and ROI 
 
“Drying is the single most expensive phase in plywood production, costing between €1 million and €3 million annually in energy and labor. Sending flawed sheets through the dryer not only wastes that investment but can lead to rework, downgraded panels, or outright waste,” says Tuukka Sorvari, Sales Manager Analyzers and Machine Vision at Raute. 
 
The composing line is one of the most demanding workstations for mill operators when visually grading birch veneer because bark layers blend with knots and can evade defect detection. Implementing AI analyzers immediately increases accuracy. Bark inclusions that legacy systems caught inconsistently are now outlined every time, and elusive sound knots register reliably. 
 
Beyond just spotting visible flaws, analyzers integrate data on moisture grades, strength properties, waviness, and roughness to deliver real-time quality maps at the peeling and drying stages. “This early assessment enables greater process control, giving operators actionable feedback on pitch angle, BUR (Back-Up Roll) pressure settings, and raw-material quality before defects cascade downstream,” adds Sorvari. 
 
As a result, process visibility extends across peeling, drying, and composing, creating continuous feedback loops that isolate where quality loss occurs, and process-related defects accumulate. AI integration reduces downstream rework, boosts saleable veneer throughput per shift, and delivers ROI far faster than traditional investments. 
 
Catching Hidden Defects Early 
 
One frequently overlooked issue is veneer roughness, which often escapes detection until the final sanding stage. “At one mill site, a sanding line operator estimated that up to 15 percent of panels were being downgraded due to excessive roughness,” recalls Sorvari. 
 
Traditional systems often miss such surface issues in earlier stages, but Raute’s R7 analyzers, for example, can generate a roughness index throughout the line, enabling operators to pinpoint when and where quality begins to deteriorate.  
 
R7-Series analyzers also simulate veneer recovery rates before drying by combining defect maps with moisture and strength data to predict yield outcomes in real time. This allows mills to divert low-recovery sheets to green composing units and optimize dryer loads before defects become locked in. 


A Roadmap for Immediate Action 
 
To gain sustained mill-wide performance, manufacturers must adopt a structured approach. The following practices detail how to scale AI-driven defect detection across the production line, unlock continuous yield optimization, future-proof operations against rising quality, and adapt to changing raw material pressures: 

Why You Must Act Now 
 
According to Sorvari, global markets are increasingly demanding sustainable production, customization, and tighter compliance with carbon regulations: “Mills that delay AI analyzer adoption risk falling behind competitors who already extract maximum value from every log and minimize energy waste through smarter decisions.” 
 
In this environment, where each undetected defect translates into lost margin and heightened regulatory risk, the imperative is clear: integrate AI-powered defect detection now to stay competitive, compliant, and profitable. The time to act is now, and the potential benefits are too significant to ignore. 

 

Tuukka Sorvari
Engineer (B.Sc.), Kajaani University of Applied Sciences
Sales Manager, Analyzer Business Unit, Raute Corporation

Tuukka has over two decades of experience in machine vision, software, and field services within the plywood industry. He began his career at Raute in 2002 as a Software Engineer and has since held various technical and managerial roles, including Field Services Engineer and Product Manager for Digital Services. Since 2024, he has served as Sales Manager for the Analyzer Business Unit, focusing on delivering advanced quality control and production optimization solutions. Tuukka is dedicated to applying digital tools that enhance efficiency and performance across plywood manufacturing processes.

 

Read our Success Story about how Koskisen, a Finnish wood processing company, piloted Raute's AI solution to enhance efficiency and drive the future of wood processing. » READ THE SUCCESS STORY

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