Thesis (MScFor (Forest and Wood Science))--University of Stellenbosch, 2006. / Producing high quality end products, rather than focusing on volume production, is slowly but surely becoming the main driving force in the wood processing industry of South Africa. Drying defects such as surface checks and discolouration by yellow stain and kiln brown stain are major factors in softwood timber downgrades when selecting furniture grade timber. Previous efforts to control these defects have focused on schedule adaptation, but as the industry is still mainly concerned with volume production, and because of the varying lumber price, longer schedules to control these drying defects have not yet been that attractive for the larger sawmills. In ongoing research in this laboratory, a dip treatment of freshly sawn softwood boards in an aqueous solution containing a surfactant called sodium lauryl sulphate (SLS) was used to try to influence the mechanism involved in the development of these stains. Further, complementary research is reported in this study. Firstly, the possibility of using SLS solutions to control surface mould development and bluestain was investigated. Results showed that SLS did control the development of blue stain and mould growth in open-stacked boards for up to three weeks, using concentrations as low as 0.1%, and up to two weeks in closed-stacked timber when using concentrations of 0.2%. Secondly, it was investigated whether SLS treatment would have a detrimental effect on downstream product quality; in particular, kiln dried boards and glued components for furniture manufacturing. Since SLS influenced fluid water flow during kiln drying, the treatment could have exacerbated the occurrence of surface checking due to altered moisture distribution profiles. Results of this investigation showed that the SLS treatment did not result in increased surface checking. Thirdly, as furniture quality timber treated with SLS would be glued, (and also finished with surface coatings), it was further considered important to determine if SLS treatment influenced adhesion properties of wood surfaces. Based on shear test results, it was established that SLS did not influence the adhesion properties of wood when glued with two most commonly used glues in the furniture industry i.e. polyvinyl acetate (PVAc) and urea formaldehyde (UF).

Interlocking Cross Laminated Timber (ICLT) wall panels are a new wood construction product similar to Cross Laminated Timber panels. Besides being an innovative structural system, they also utilize beetle killed timber from many of the forests that have been devastated by the Mountain Pine Beetle. Three tests were performed on three ply ICLT panels measuring 8 feet (2.44m) wide, 8 feet (2.44m) tall and 8.5 inches (21.6cm) thick to determine the racking, flexural and axial strengths of the wall panels. After each test was performed the walls were disassembled and investigated for cause of failure. Using the data from the tests as a benchmark, simple analytical models to predict the design capacities of the walls for racking, flexural, and axial strengths were established. The analytical models for racking strength, flexural strength and axial strength predicted reasonably well the measured strength values. Additional testing is necessary to increase the available database, further validate the analytical models developed, better understand the structural performance of ICLT panels, and establish acceptable design methodology for ICLT wall panels.

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With the evolution of GPU performance, the interest of using AI for all kinds of purposes has risen. Companies today put a great amount of resources to find new ways of using AI to increase the value of their products or automating processes. An area in the wood industry where AI is widely used and studied is in defect detection. In this thesis, the combination of using AI and hyperspectral images is studied and evaluated in the case of segmenting defects in hardwood with a U- Net network structure. The performance is compared to another known method usually used when dealing with high-dimensional data: PLS-DA. This thesis also compares the use of RGB image data in combination with AI, to further analyze the usefulness that the hyperspectral data provide. The results showed signs of improvement when using hyperspectral images com- pared to RGB images when detecting blue stain and red heartwood defects. De- tection of the defects rot and knots did however show no sign of improvements. Due to the annotations being more accurate in the RGB data, the results from the hyperspectral data-fed networks would suggest that blue stain and red heartwood could be of interest regarding further investigation. Computational performance is shown to vary across the different reduction meth- ods, and the results from this thesis provides some insight that might aid in the reasoning regarding how to choose an appropriate reduction method.