The use of the first industrial X-ray CT scanner increases the lumber recovery value: case study on visually strength-graded Douglas-fir timber

Key message: Industrial computed tomography scanning of logs provides detailed information on timber quality prior to sawing. A sawing simulation—considering log rotation angle and knot size accuracy—revealed an average value increase of up to 20% for the best angle compared to the conventional horns-up position. Context: Computed tomography (CT) scanning has the potential to improve the value of products sawn from logs and meets the increasing demands of the wood industry for detailed information on log quality prior to processing. Aims: In a validation step, automated measurements of knot cluster variable DAB (DIN 4074-1:2012-06) using CT were compared with manual measurements. In a second optimization step, the hypothesis that the value of the sawn products is increased by sawing at the best rotation angle as opposed to the horns-up position was tested. Methods: A sample of 36 Douglas-fir logs were scanned in an industrial CT scanner, and sawn into boards. Knots on the boards were manually measured, and compared with the corresponding knots on virtual boards created from the CT data. The error of the DAB was measured by comparing CT data to manual measurements. An optimized sawing simulation was performed, using the measured DAB error to account for CT measurement errors, as well as a rotational error to account for errors in the log turning equipment. Using the results of the sawing simulation, Monte Carlo simulations were performed to show the potential and benefit of an industrial CT scanner. Results: The three largest DABs measured by the CT showed good correlation to the measurements on the manual boards. The simulation revealed an average increase of value from 4 to 20% compared to the conventional horns-up position depending on the relative price differences between the strength grades. Conclusion: By using a CT scanner to optimize sawing, sawmill owners can process logs in a better way to produce final products with increased added value