Browsing by Author "Thomas, R. Edward"

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    The Effect of Kerf Thickness on Hardwood Log Recovery
    Thomas, R. Edward; Buehlmann, Urs (Forest Products Society, 2022-02-07)
    When sawing a log into lumber or other products, the saw blade removes material to separate the wood fibers between the resulting two parts, a loss of material that is commonly referred to as saw kerf. Thicker kerfs result in greater waste and less material available to produce lumber. Over the past decades, with the advancement of materials and technology, saw blade thickness has decreased. However, the reduction in material loss owing to a reduction in saw kerf may not always translate into a statistically significant increase in lumber product recovery. In this study, we explored the effect of saw kerf thickness on lumber recovery for a range of hardwood log diameters using the US Forest Service's Log Recovery Analysis Tool (LORCAT) sawmill simulation tool. Results indicate that the recovery gains realized depend upon the log diameters sawn, the lumber target thickness, and the change (reduction) in the thickness of the saw kerf.
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    Estimating Component Yield for CLT Production
    Buehlmann, Urs; Thomas, R. Edward (2017)
    The emergence of cross-laminated timber (CLT) for building construction in North America may provide an additional and possibly more valuable product market for hardwood logs. Using the RaySaw sawing and ROMI rough mill simulators and a digital databank of laser-scanned low-grade yellow-poplar (Liriodendron tulipifera) logs, we examine the yield-recovery potential for components used in the production of CLT. Results include a sawing yield of 65% and a rough-mill yield of 78%, for a total material yield of approximately 50%. This study confirmed the usability of yellow poplar as a material for the production of CLT and allows to estimate the impact on our forest resource of increased use of yellow poplar CLT.
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    Integrating the Least-Cost Grade-Mix Solver into ROMI
    Buck, Rebecca Arlene (Virginia Tech, 2009-12-08)
    Up to 70 percent of rough mill manufacturing expenses stem from raw material (lumber) cost. Rough mill costs can be reduced by optimizing the lumber grade or grades that are purchased. This solution is known as the least-cost lumber grade-mix solution. The least-cost lumber grade-mix solutions has been a topic of great interest to both the secondary hardwood industry and to academia since even small changes in raw material cost can contribute to substantial reduction in rough mill expenses. A statistical model was developed for finding the least-cost lumber grade-mix which uses the rough mill simulator, ROMI-RIP 2.0, and the statistical package, SAS 8.2. The SAS 8.2-based least-cost lumber grade-mix model was validated by comparing SAS 8.2-based least-cost grade-mix solutions to OPTIGRAMI 2.0, a least-cost lumber grade-mix solver that relies on linear modeling. The SAS 8.2-based least-cost lumber grade-mix solver found lower cost solutions in 9 of 10 cutting bills that were tested. The SAS 8.2-based least-cost lumber grade-mix solver was packaged with ROMI 3.0, an updated version of ROMI-RIP, and provided to industry free of charge by the USDA Forest Service. The USDA Forest Service also purchased a SAS server license to allow least-cost lumber grade-mix solver users free access to SAS 8.2. However, industry users were reluctant to use the USDA Forest Service SAS server since it requires the user to enter individual cost and yield data to a government computer. This solution also required the user to have internet access and limited access to one user at any time. Thus, the goal of this research was to incorporate the least-cost lumber grade-mix solver into ROMI using the free, open source statistical package R 2.7.2. An R 2.7.2-based least-cost lumber grade-mix solver was developed and validated by comparing the R 2.7.2-based least-cost lumber grade-mix solutions to the updated SAS 9.2-based least-cost lumber grade-mix solutions. No differences were found in the least-cost lumber grade-mix solutions from either solver. Thus, a new least-cost lumber grade-mix solver using the R 2.7.2 open source statistical package was created. R 2.7.2 is installed on each personal computer on which the USDA Forest Service's ROMI rough mill simulation software is installed and, thus, no external computing resources are needed when solving the least-cost lumber grade-mix problem.
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    Potential for Yield Improvement in Combined Rip-First and Crosscut-First Rough Mill Processing
    Thomas, R. Edward; Buehlmann, Urs (2016-02)
    Traditionally, lumber cutting systems in rough mills have either first ripped lumber into wide strips and then crosscut the resulting strips into component lengths (rip-first), or first crosscut the lumber into component lengths, then ripped the segments to the required widths (crosscut-first). Each method has its advantages and disadvantages. Crosscut-first typically works best for the production of wider components, while rip-first favors the production of narrower and longer components. Thus, whichever type of processing method is selected for a given rough mill usually depends on the characteristics of the cutting bills the mill expects to process. There is a third option, a dual-line mill that contains both ripfirst and crosscut-first processing streams. To date, such mills have been rare for a variety of reasons, complexity and cost being among them. However, dual-line systems allow the mill to respond to varying cutting bill size demands as well as to board characteristics that favor one method (rip-first or crosscut-first) over the other. Using the Rough Mill Simulator (ROMI 4), this paper examines the yield improvement potential of dual-line processing over single-system processing (i.e., rip-first or crosscut-first processing alone) for a variety of cutting bills and lumber grade mixes.