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Investigation of NDE technologies for drying quality segregation to aim for optimal kiln schedules to reduce drying degrade & accelerate kiln throughput in the hardwood sawmilling industry

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Published Date

December 2020

Hardwood logs and green boards often show large variations in the rate at which they dry, which causes problems for timber processors. If fast or slow drying boards could be identified they could be segregated to allow optimal batch drying, reducing product variability in moisture content and reducing overall drying time.

This project aimed to assess drying degrade in terms of check and collapse development, identify whether simple wood properties of density or extractives content affect the drying rate of jarrah and shinning gum, and trial the ability of two technologies (acoustics and NIR) to scan green lumber prior to drying in order to segregate individual boards into “fast” or “slow” drying batches.

The report found that drying rate decreased with the increase of most of extractive contents in both species, and drying rate decreased with the increase of green density in E. nitens but did not vary much with green density in jarrah. The primary predictor for the number of internal checks differed between species; in jarrah it was initial moisture content, while in E. nitens it was area collapse. The primary predictor for the area of internal checks also differed; in jarrah it was collapse-free area shrinkage, and E. nitens it was area collapse in.

Unfortunately no wood property or acoustic and ultrasonic variable, either alone or in combination, could reliably predict drying rate and drying degrade and collapse for both species, apart from the along-grain acoustic and ultrasonic velocity which appeared to provide some prediction to drying rate of jarrah.

Near infrared spectroscopy showed moderate correlations for several properties. While individually these properties are of limited interest, collectively they may be able to identify the worst performing boards in order to segregate them for milder drying.

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Roger Meder, Jun Li Yang, Philip Blakemore, Andrew Morrow, Dung Ngo, Nick Ebdon, Matthew Josh, Muruga Muruganathan

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