Raute, a global market leader in veneer, plywood and LVL production technologies,  has deployed AI‑enhanced defect detection in production environments to improve how veneer, plywood, and LVL production lines identify and utilize raw material. The solution enables earlier and more consistent production decisions, helping mills improve recovery, reduce waste, and optimize energy use.

In veneer‑based engineered wood production, defect detection has a direct impact on how efficiently raw material can be utilized. It influences grading, clipping, routing, and repairing decisions throughout the process. When detection is inaccurate or inconsistent, it leads to unnecessary waste, reduced recovery, and inefficient energy use in downstream stages.

Raute's analyzers are industrial systems used to measure, grade, and classify veneer and panels at different stages of production. They provide real‑time quality data to support production decisions across the process. By combining visual defect detection with measurements such as moisture and strength properties, analyzers create a consistent foundation for data‑driven and increasingly automated production.

AI‑enhanced defect detection strengthens this role. By combining industrial machine vision with deep learning models specifically developed for veneer‑based engineered wood production, analyzers can identify defects more consistently across different wood species, surface characteristics, and production conditions. The systems generate detailed defect maps for individual sheets, enabling more precise, repeatable decisions.

Demand for this capability is growing as manufacturers work with a wider mix of raw materials. AI‑based defect detection in Raute analyzers is built on more than 50 years of analyzer development and extensive experience from veneer processing across over 50 wood species. This provides a strong foundation for applying the same approach to both commonly used and more specialized materials.

“More variable raw materials mean that mistakes made early in the process become increasingly costly later on,” says Markus Sirvi? responsible for analyzer business development at Raute. “When detection becomes more consistent, mills can improve recovery and avoid inefficiencies that would otherwise carry through the entire production process.”

Raute analyzers can be applied at multiple points in production, including green veneer inspection after peeling, dry veneer grading after drying, and panel repairing and grading. Early‑stage defect detection is particularly important, as it helps prevent low‑quality material from entering energy‑intensive processes such as drying and hot pressing.

As engineered wood producers work to improve efficiency with increasingly variable raw materials, AI‑enhanced analyzers are becoming an established part of production. Their role is shifting from inspection to enabling consistent, data‑driven decision‑making across the production process.

Source: raute.com