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Abstract
This paper is concerned with scanning and assessment of hardwood lumber early in the manufacturing process. Scanning operations that take place immediately after the headrig have significantly greater potential to reduce loss and improve economic value, as compared to scanning that is performed during subsequent manufacturing steps. In spite of this, the scanning of green, unplaned lumber has received relatively little attention in the research community. Part of the reason for this is that image capture and analysis are more difficult when fibrous structures and debris are present near the surface of the wood. This paper describes a prototype system that addresses this problem. The system, which automatically provides an optimal edging and trimming solution along with resulting lumber grades, has been has been developed and tested for use with unplaned hardwood lumber that is still in the green state. The system obtains thickness (profile) and reflectance information at 1/16-inch (1.6-mm) resolution, using commercially available laser sources and a video camera. It analyzes the resulting images to detect wane and important lumber-degrading defects. Wane boundaries are detected with 3/16-inch (5-mm) error on average, and a modular artificial neural network is used to locate clear wood, knots, and decay. Using this surface information for each board, the system then automatically finds optimal solutions for placement of cuts to yield maximum commercial value based on current market prices.
Citation
Lee, Sang-Mook; Abbott, A. Lynn; Araman, Philip A.; Schmoldt, Daniel L. 2003. A prototype scanning system for optimal edging and trimming of rough hardwood lumber. Proceedings, ScanTech 2003, The Tenth International Conference on Scanning Technology and Process Optimization in the Wood Industry. 49-58.
