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Cost minimization through optimized raw material quality compositionAuthor(s): Urs Buehlmann; R. Edward Thomas; Xiaoqui Zuo
Source: Robotics and Computer-Integrated Manufacturing. 27: 746-754.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionLumber, a heterogeneous, anisotropic material produced from sawing logs, contains a varying number of randomly dispersed, unusable areas (defects) distributed over each boards’ surface area. Each board's quality is determined by the frequency and distribution of these defects and the board's dimension. Typically, the industry classifies lumber into five quality classes, ranking board quality in respect to use for the production of wooden components and its resulting material yield. Price differentials between individual lumber quality classes vary over time driven by market forces. Manufacturers using hardwood lumber can minimize their production costs by proper selection of the minimum cost lumber quality combination, an optimization problem referred to as the least-cost lumber grade-mix problem in industry parlance. However, finding the minimum cost lumber quality combination requires that lumber cut-up simulations are conducted and statistical calculations are performed.
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CitationBuehlmann, Urs; Thomas, R. Edward; Zuo, Xiaoqui. 2011. Cost minimization through optimized raw material quality composition. Robotics and Computer-Integrated Manufacturing. 27: 746-754.
Keywordscost minimization decision support system, (DSS), cost models, cutting stock problem, decision making, decision process, manufacturing, production planning and control, component production
- Lumber Cost Minimization through Optimum Grade-Mix Selection
- Identifying and locating surface defects in wood: Part of an automated lumber processing system
- Second-order polynomial model to solve the least-cost lumber grade mix problem
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