UBC Theses and Dissertations

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UBC Theses and Dissertations

Kiln drying optimization for quality hem-fir lumber Shahverdi, Mahdi


Western hemlock is a dominant coastal species in British Columbia, Canada. This species is commonly marketed with amabilis fir as Pacific Coast Hemlock or hem-fir. Hem-fir is difficult to dry, mostly because of the existence of wetwood and large initial moisture content variation. The dried lumber will likely end up with a large final moisture content difference resulting in increased drying defects and decreased lumber quality and factory productivity. In this study, application of green chain moisture-based sorting coupled with drying schedule modifications were considered as ways to improve final moisture content variation within and between kiln dried hem-fir lumber. There were two research phases. The first (without sorting), aimed to develop a modified drying schedule whereas in the second, the developed schedule was used along with a standard industrial schedule. Additionally, there was a green moisture content pre-sorting component in the second phase where freshly cut specimens were sorted based on their initial moisture content into three groups, i.e., mixed, low, and high moisture. To assess the specimen kiln dried quality, final moisture content variation, moisture content gradient, drying rate, warp, surface and internal checks, shrinkage, and casehardening were assessed. Data analysis revealed that there was no significant difference between the drying runs in terms of final moisture content variation, except in the high initial moisture content group. High initial moisture content sorting helped to reduce the final moisture content variation. The modified schedule, when there was a high initial moisture content sorting, also improved the uniformity of final moisture content in comparison to the industrial schedule. Moreover, neither the moisture sorting nor the drying schedule did affect the final moisture content variation for the low and mixed initial moisture content groups. Therefore, the green moisture-based pre-sorting was statistically effective just in the sorted group with high initial moisture content and where the modified schedule was used.

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