Potentially increased sawmill yield from hardwoods using X-ray computed tomography for knot detection

Stefan M. Stängle , Franka Brüchert , Antti Heikkila , Timo Usenius , Arto Usenius , Udo H. Sauter

AbstractContextOne of the most important wood defects affecting the value yield from European beech (Fagus sylvatica [L.]) logs is knots that are visible on the sawn wood surface. The non-invasive technology of X-ray computed tomography (CT) can be used for the assessment of log internal features, especially the geometry and position of knots before primary breakdown to support the decision of value-optimised log rotation in sawmills.AimsThe objective of this study was to test whether value-optimised log rotation can be performed successfully by using the CT-derived knowledge of internal knottiness for the hardwood species beech.MethodsSize parameters of 670 knots were measured and their position was marked in CT images from 33 logs. The 3D-reconstructed logs were virtually sawn in 12 different rotational angles using the software InnoSIM. This allowed visual grading of the simulated sawn wood and the calculation of product volume and value.ResultsThe results show that if optimal rotation was applied to each single log, both total volume as well as total product value yield could be improved by up to 24 % compared with the average yield of all simulated rotational angles.ConclusionIn this small-scale study, it is demonstrated that CT technology could be used to support the decision about optimal rotational angle of beech logs to maximise volume and value yield.

Mots clés: CT; Wood quality; Knot detection; Fagus sylvatica; Sawing optimisation; Log rotational angle

Domaines: Sciences du Vivant [q-bio]

Stefan M. Stängle, Franka Brüchert, Antti Heikkila, Timo Usenius, Arto Usenius, et al.. Potentially increased sawmill yield from hardwoods using X-ray computed tomography for knot detection. Annals of Forest Science, 2015, 72 (1), pp.57-65. ⟨10.1007/s13595-014-0385-1⟩. ⟨hal-01284151⟩