Forest Products Industry

Raute 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. Source: Timberbiz Raute is a global leader in technology and services for the wood products industry specializing in supplying machinery, digital solutions, and plant-wide services for veneer, plywood, and Laminated Veneer Lumber (LVL) production. 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 use of energy in downstream stages. Raute’s analysers 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, analysers 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 developed specifically for veneer based engineered wood production, analysers can identify defects more consistently under different wood species, surface characteristics and production conditions. The systems generate detailed defect maps for individual sheets, supporting more precise and 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,” said Markus Sirviö, responsible for analyser 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 analysers 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 analysers are becoming an established part of production. Their role is shifting from inspection to enabling consistent, data driven decision making across the production process.

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