Thirty full-length sample trees from the B.C. Interior were selected for a study to determine whether external log characteristics can predict internal log quality. The sample trees were also used to create 3-dimensional log images for sawmill simulation purposes. "LogSaw", a simulation tool with internal log defect detection capabilities, was used to explore the extent to which internal and external log quality information can improve log breakdown optimization. A model of a hypothetical sawmill producing lumber for the standard North American dimension market was created to study how lumber value recovery depends on different sawing optimization scenarios.
Three sawing optimization scenarios using different levels of knowledge of internal log defects were compared to currently used sawing optimization technique:
Ideal sawing optimization - all defects within log interior are known.
Sawing optimization using only the knowledge of surface knots.
Sawing optimization using log rotation instructions based on zones of least external knot density.
Simulation results have shown that it is worthwhile to “look into the log”. When compared with the current optimization technique, the sawing optimization, including the full knowledge of log interior, has increased the value recovery by 6.2%. When only the surface knots were projected into the log interior and included in the optimization, the value recovery had increased by 4.3%. Even this 4.3% increase is still a big improvement because this sawing optimization could be implemented using currently available scanning technologies and optimization software enhanced to include log surface knots. The scenario of using log rotation instructions based on predicted zones of least internal knot density did not show value recovery improvement.
Including surface knots in the log breakdown optimization has considerably increased sawmill revenue; the hypothetical sawmill considered in this study, processing 400,000 m3 of log per year, has increased its revenue by $2.2 million.
The 2003 Wildland Fire Detection Workshop was the first in a series of workshops on fire detection organized by FPInnovations. The workshops take place at the Hinton Training Centre with the goal to bring Canadian and international wildland fire detection expertise together in one place; encouraging communications among participants; and providing ideas & innovations to create solutions for the issues affecting wildfire detection programs today, on every scale, and well into the future.
Harvest operations on soft soils can be particularly challenging in order to respect site and soil disturbance guidelines as well as operational requirements. To address the challenges of operating on soft soils, FPInnovations has worked on solutions designed to reduce disturbance on weak soils while minimizing implementation and investment costs by using machines already being used in the operation.
Innovations for the future; learning from the past
November 2 - 4, 2010 Hinton Training Centre, Hinton, Alberta, Canada
Presented at the 3rd International Wildland Fire Detection Workshop
The 2010 Wildland Fire Detection Workshop was the third in a series of workshops on fire detection organized by FPInnovations. The workshops take place at the Hinton Training Centre with the goal to bring Canadian and international wildland fire detection expertise together in one place; encouraging communications among participants; and providing ideas & innovations to create solutions for the issues affecting wildfire detection programs today, on every scale, and well into the future.
Innovations for the future; learning from the past
November 2 - 4, 2010 Hinton Training Centre, Hinton, Alberta, Canada
The 2010 Wildland Fire Detection Workshop was the third in a series of workshops on fire detection organized by FPInnovations. The workshops take place at the Hinton Training Centre with the goal to bring Canadian and international wildland fire detection expertise together in one place; encouraging communications among participants; and providing ideas & innovations to create solutions for the issues affecting wildfire detection programs today, on every scale, and well into the future.
