Impact of Over-Run on Profitability of Hardwood Sawmills
Keywords:Over-run, optimal profitability, sawmill efficiency, stepwise linear regression, log scales
AbstractThe objective of this paper is to ascertain if the common sawmill efficiency measure, over-run, bears a significant relationship to the ultimate measure of efficiency-profitability. A data set of log grades and lumber yields from twelve batches of red oak logs, representing about four weeks of production, was collected from a mill in central Pennsylvania. The over-run and actual profitability of each batch were calculated from mill results. For comparison, each batch was optimized through a linear programming technique to determine potential mill profitability under prevailing log and lumber prices; the corresponding over-run of each optimized batch was calculated. Stepwise linear regression techniques were utilized to prove a hypothesis that no relationship exists between over-run and profitability, either actual profit as realized by the sawmill studied or theoretically optimal profit as determined by a linear programming solution. Simple linear regression was then used to validate the result. The study demonstrates clearly that, in this case, over-run is not a predictor of profitability, and as influenced by a company's choice of log scale, is merely a relative measure of operational efficiency that may lead to mistaken assumptions about mill profitability.
Bare, B. B., D. Briggs, and G. Mendoza. 1989. Log allocation and soft optimization: A de novo programming approach. Forest Prod. J.39(9):39-44.nBeauregard, R., M. Beaudoin, D. Ait-Kadi, and J. P. Mongeau. 1994. A systemic approach to consider complexity in sawmill modeling. Wood Fiber Sci.26(3):421-437.nBryan, E. L. 1996. The best possible sawmill. Miller Freeman Books, San Francisco, CA. 231 pp.nCarino, H. F., and S. U. Foronda. 1987. Determining optimum log requirements in lumber manufacturing. Forest Prod. J.37(11/12):8-14.nJackson, N. D., and G. W. Smith. 1961. Linear programming in lumber production. Forest Prod. J.11(6):272-274.nManess, T. C., and D. M. Adams. 1991. The combined optimization of log bucking and sawing strategies. Wood Fiber Sci.23(2):296-314.nPearse, P. H., and S. Sydneysmith. 1966. Method of allocating logs among several utilization processes. Forest Prod. J.16(9):87-98.nSampson, G. R., and C. A. Fasick. 1970. Operations research application in lumber production. Forest Prod. J.20(5):12-16.nWadhwa, V. 2005. Determination of the optimal performance of hardwood sawmills and its relationship to the metric "over-run". Unpublished Master's thesis, The Pennsylvania State University, University Park, PA. 74 pp.n
The copyright of an article published in Wood and Fiber Science is transferred to the Society of Wood Science and Technology (for U. S. Government employees: to the extent transferable), effective if and when the article is accepted for publication. This transfer grants the Society of Wood Science and Technology permission to republish all or any part of the article in any form, e.g., reprints for sale, microfiche, proceedings, etc. However, the authors reserve the following as set forth in the Copyright Law:
1. All proprietary rights other than copyright, such as patent rights.
2. The right to grant or refuse permission to third parties to republish all or part of the article or translations thereof. In the case of whole articles, such third parties must obtain Society of Wood Science and Technology written permission as well. However, the Society may grant rights with respect to Journal issues as a whole.
3. The right to use all or part of this article in future works of their own, such as lectures, press releases, reviews, text books, or reprint books.