Improved log rotation using information from a computed tomography scanner

Berglund, Anders; Broman, Olof; Grönlund, Anders; Fredriksson, Magnus

doi:10.1016/j.compag.2012.09.012

Cited by 32 publications

(35 citation statements)

References 7 publications

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“…Various studies have shown that optimization of initial log breakdown based on knowledge of internal wood features-knots in the tested casescould considerably improve value recovery in sawn timber production (e.g. Rinnhofer et al [12], Berglund et al [13]). …”

Section: Introductionmentioning

confidence: 99%

Classification of wood surfaces according to visual appearance by multivariate analysis of wood feature data

et al. 2014

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Its natural aesthetics make wood an attractive material for construction and design. However, there is no detailed understanding of the relationships between human perception of the appearance and measurable features of wood surfaces that could be used for controlling sawn timber production. This study investigated whether wood surfaces can be classified according to their visual appearance on the basis of wood feature measurements. Cluster analysis was used to discover a classification based on a set of feature pattern variables in a sample of 300 softwood floorboards. A finely graded visual appearance sorting provided a reference. Discriminant analysis was applied to identify the relevant variables from the tested set and to assess predictability of the classification. The results indicated that visual appearance sorting could be approximated quite well by the variable-based classification after pregrouping according to board position in the log. Ambivalent results were obtained for group prediction within the validation sample. While for boards from some groups prediction was mostly or entirely correct, boards from other groups were largely misclassified. An effect of the available sample was one of the surmised causes, making repetition of the analysis based on a larger sample a desirable focus of further research.

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Section: Introductionmentioning

confidence: 99%

Classification of wood surfaces according to visual appearance by multivariate analysis of wood feature data

et al. 2014

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“…This means that a small change in rotational position can have a severe effect on the value of the sawn timber, for instance when a large knot changes from being on the flat side of a board to the edge side. This sensitivity is shown by Berglund et al (2012). The rotational position of a log in some cases needs to be chosen with high precision, something which was not the case here.…”

Section: Discussionmentioning

confidence: 88%

“…The optimal rotational position is subject to some uncertainty though, both in the detection of knots and in the precision with which it is possible to rotate a log in the sawing process. The effect of this lack of precision in the rotational position has been shown by Berglund et al (2012). In their study, the value loss when failing to rotate logs properly was more than 50%.…”

Section: Introductionmentioning

confidence: 87%

“…This study was made on Scots pine (Pinus sylvestris L.) and for Swedish sawmills and quality sorting rules. A study by Berglund et al (2012) on a similar material indicates a potential value increase of about 13% when optimizing the rotational position, compared to horns down. Another study, by Todoroki and Rönnqvist (1999), indicated a potential value increase of 16% when practicing live sawing and optimizing sawing parameters.…”

Section: Introductionmentioning

confidence: 99%

“…This reduces the amount of information that needs to be processed, which potentially saves computation time. However, such a method might be susceptible to positioning errors, as it is based on a smaller amount of information than in Berglund et al (2012). No industrially viable solution will be developed in this study, which can be seen as a feasibility study.…”

Section: Introductionmentioning

confidence: 99%

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Rotating Pinus sylvestris Sawlogs by Projecting Knots from X-ray Computed Tomography Images onto a Plane

Fredriksson¹,

Johansson²,

Berglund³

2013

BioResources

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In this paper, a method for utilizing knot information from computed tomography (CT) scanning of Scots pine (Pinus sylvestris L.) logs was evaluated. A high speed industrial CT scanner is being developed, which will enable scanning of logs in sawmills at production speed. This development calls for the ability to optimize breakdown parameters in a quick manner because there are many decisions to be made and the timeframe for these production decisions is short. One of the important breakdown parameters is in which rotational position to saw a log. The presented method used CT data to create a two-dimensional projection of knot information from a log, in order to minimize the amount of data to analyze. The center of mass of the knot projection relative to the center of the sawing pattern was chosen as the rotational position of the log. The aim was to put large knots on the flat surfaces of the boards, as knots on edge surfaces have a more negative effect on board quality in the sorting rules used in this study. The method was tested by sawing simulation and was compared with the industrial praxis of sawing logs horns down. The results show an increase in board quality and value, albeit for a selected group of Scots pine logs. The method is very sensitive to positioning errors, but it has some potential if sawlog positioning accuracy is improved.

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Sawmilling

Sandberg

Teischinger

2023

Springer Handbooks

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Improved log rotation using information from a computed tomography scanner

Cited by 32 publications

References 7 publications

Classification of wood surfaces according to visual appearance by multivariate analysis of wood feature data

Classification of wood surfaces according to visual appearance by multivariate analysis of wood feature data

Rotating Pinus sylvestris Sawlogs by Projecting Knots from X-ray Computed Tomography Images onto a Plane

Sawmilling

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