Accuracy considerations when optimally sawing pruned logs: internal defects and sawing precision
Source abstract
Abstract
There is worldwide interest in non-destructive evaluation (NDE) tools to extract more value from logs. Technologies range from high precision, high resolution scanners, such as computed tomography (CT) to less precise or lower resolution technologies. While the lesser resolution technologies are associated with lower costs, they are accompanied by reduced precision. In this study, the effect of reduced precision on lumber value yield was examined to determine whether benefits are still possible with imperfect knowledge of internal defects. As the attainment of optimal value from a log is highly dependent on not only the accuracy of data describing the log and internal defects but also placement of saws, both aspects were studied. Mathematical models of pruned logs with internal defects representing differing degrees of measurement accuracy were generated and sawn into boards using computerised sawing methods. With precise knowledge of internal defects and optimal sawpattern placement, increases in value relative to a no-internal-knowledge benchmark averaged 23%. As sawpattern positioning deviated from optimal placement, a logarithmic decrease in lumber value was found. Imprecise knowledge of internal defects yielded increases in lumber value averaging 13%. Thus, there appears to be potential for NDE methods, even with less-than-precise defect detection capabilities.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Industrial Vision Systems and Defect Detection · Wood Treatment and Properties · Forest ecology and management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (26)
Show source-provided references
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