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TOMRA brings artificial neutral network in wood recycling

 Wednesday, August 3, 2022

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Artificial Intelligence is making headline news everywhere. Experts in the field of AI and major players in the recycling are convinced that machine intelligence can help solve some of the panelboard industry’s biggest challenges.

Jose Matas, Segment Manager Wood, TOMRA, remarked, “Thanks to AI, automated sorting systems are no stranger to the recycling industry. Optical sorters employed in recycling circuits have employed AI algorithms to sort materials for over 30 years and are now experiencing another wave of technological advancement with the use of Deep Learning.”

Recycling waste wood is a valuable business opportunity and a viable means to mitigating the environmental impact of using primary resources. Once waste wood is collected, it undergoes an extensive purification process to remove unwanted materials, such as stones, metals, or inert materials with X-Ray sorting technology. The clean woodchips can then be further sorted by material type according to operator’s requirements.

Today, operators have a choice of numerous sorting methods ranging in size, efficiency and initial costs. The most effective, scalable and flexible solution combines leading-edge technologies to generating the purest wood fractions. Unlike conventional sorting methods, the combination of the Near-Infrared and Deep Learning technologies enables peak performances in sorting accuracy and purity levels. With sophisticated sensors and the power of artificial neural networks, the sorting system is trained to distinguish different material types, such as processed wood and non-processed wood. Since only the purest non-processed wood fractions are suitable for the production of high-quality particleboards made of recycled content, separating wood by type is an indispensable step in modern particleboard manufacturing and wood recycling plants.

Published from TOMRA.COM, article by JOSE MATAS.

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