A team of researchers at the Swiss Federal Laboratories for Materials Science and Technology (Empa) is working exclusively to optimize wood processing via machine learning.
 
Empa scientist Mark Schubert and his team are using the many opportunities offered by machine learning for wood technology applications. Together with Swiss Wood Solutions, Schubert develops a digital wood-selection- and processing strategy that uses artificial intelligence. The SWS Smartfactory 4.0 aims to predict the optimal processing from the choice of raw material to the final high quality product.
 
"Every processing company faces the problem of interpreting and making decisions based upon the results of the receiving inspection, which provides data on the density, moisture content, fiber direction and annual ring position of the raw wood, says Empa. In order to process the wood profitably, the sequential production steps such as separation, sorting and treatment must be well planned and many process parameters set correctly.
 
Employees with a sense of proportion and years of experience can often help to avoid mistakes. However, there is no holistic approach that records and analyzes the raw material and process parameters that would allow product quality to be predicted in real time."
 
That's where artificial intelligence comes in. Together with Swiss Wood Solutions, lead researcher Mark Schubert is developing a digital wood-selection- and processing strategy that uses artificial intelligence. The SWS Smartfactory 4.0 aims to predict optimal processing from the choice of raw material all the way to the final product.

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