A loglinear model to predict lumber quality depending on quality parameters of logs

In sawmills logs, produced by forestry associations, are graded. The grade of a log depends on the log dimensions and the quality of the log. Depending on the target lumber grades, logs of a specific log grade are cut with a specific sawing pattern. Hence during the cutting of logs of one specific l...

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Bibliographic Details
Published in:European journal of wood and wood products 2005-04, Vol.63 (2), p.112-117
Main Authors: PETUTSCHNIGG, A. J, KATZ, H
Format: Article
Language:English
Subjects:
Applied sciences
Exact sciences and technology
Forest management
Forestry
Lumber
Mathematical models
Mechanical woodworking and drying
Optimization
Parameters
Polymer industry, paints, wood
Quality
Saw mills
Sawing
Sawmills
Statistical models
Wood
Wood. Paper. Non wovens
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Summary:In sawmills logs, produced by forestry associations, are graded. The grade of a log depends on the log dimensions and the quality of the log. Depending on the target lumber grades, logs of a specific log grade are cut with a specific sawing pattern. Hence during the cutting of logs of one specific log grade, not only the target lumber grades, but also a large number of other lumber grades are produced. The range of the resulting lumber grades is mainly due to the quality differences in logs in one log grade. In this paper, a statistical model to predict the lumber quality depending on the characteristics of a log quality is elaborated. A more target-oriented grading could be deduced for the logs observed from the model results. Based on this model, the requirements of sawmills regarding log quality features can be defined more precisely depending on the target lumber grade. In a further step, the relation between lumber quality and tree quality parameters could be investigated. According to the need of optimisation of processes in the whole value-added chain, this information can be used to adapt forest vegetation management in the future.
ISSN:0018-3768
1436-736X
DOI:10.1007/s00107-004-0537-3