Machine learning approach for structural timber strength grading starting from the computed tomography of the log

All timber used for structural purpose in the European Union has to be strength graded. To grade a board to possibilities exist: visual grading and machine grading. While both methods serve the purpose, mechanical grading stands out for its superior reliability. Machine strength grading entails subjecting each timber piece to specialized machines that determine the indicative properties required to assign an appropriate grade. This work, carried out at Microtec, proposes to use a machine learning approach to strength grade boards starting from computer tomography data of the entire starting log provided by Microtec CT Log. By integrating machine learning into the grading process, the objective is to optimize production efficiency, minimize material wastage, and streamline operations. The ultimate vision is to enable strength grading directly from the tomography of the log, eliminating the need to cut the board beforehand.