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The fingerprint approach: Using data generated by a 2-axis log scanner to accomplish traceability in the sawmill's log yard
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.
Swedish Inst. for Wood Technol. Res., SE-11486, Stockholm, Sweden.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.
2003 (English)In: Forest products journal, ISSN 0015-7473, Vol. 53, no 2, p. 78-86Article in journal (Refereed) Published
Abstract [en]

Today the sawmill industry is in possession of sophisticated measuring devices for sawlogs. This equipment is employed in practice for measuring log dimensions, and the data gathered are used for sorting out sawlogs according to different criteria or for judging potential quality for future end-uses. However, a lot of these data are not fully utilized. Meanwhile, large knowledge gaps regarding the flow and the origin of the wood material persist in the sawmill's daily routine. For sawmills performing presorting of sawlogs, the most significant information gap is located between the log sorting station and the saw intake where the log batch identity disappears and the logs are mixed according to different sorting criteria. This study attempts to use the data generated by 2-axis log scanners to develop a traceability system, the fingerprint approach (a marking/reading free system), between the log sorting station and the saw intake. The originality of the fingerprint approach is based on the biological variability of the wood material; the assumption is that each sawlog is a unique individual with unique features. Measuring these features at the log sorting station and at the saw intake and then connecting them to a common database will in fact permit each individual sawlog to be followed within the sawmill and thus enable the development of an advanced raw material flow control. The results of this work entirely indicate the promising potential of the fingerprint approach, which is based on the hypothesis that logs are separate entities with individual features. Being able to separate logs at the individual level is essentially a question of taking advantage of the right log features, measuring them with high accuracy, and employing appropriate search/recognition algorithms. The log parameters and the measurement accuracy generated by the 2-axis log scanner used in this study were not enough to accomplish individual separation for more than 34 percent of the logs. An improvement of measurement accuracy by 30 percent would allow 50 percent of the logs to be individually separated.

Place, publisher, year, edition, pages
2003. Vol. 53, no 2, p. 78-86
National Category
Other Mechanical Engineering
Research subject
Wood Technology
Identifiers
URN: urn:nbn:se:ltu:diva-4207Scopus ID: 2-s2.0-0037296716Local ID: 21eb25a0-bb53-11db-b560-000ea68e967bOAI: oai:DiVA.org:ltu-4207DiVA, id: diva2:977071
Note

Validerad; 2003; 20061017 (cira)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2023-11-09Bibliographically approved

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Chiorescu, SorinGrönlund, Anders

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