Integrating the Least-Cost Grade-Mix Solver into ROMI
Buck, Rebecca Arlene
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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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