Cost minimization through optimized raw material quality composition

Urs Buehlmann; Ed Thomas; Xiaoqui Zuo

doi:10.1016/j.rcim.2010.12.013

Treesearch

Cost minimization through optimized raw material quality composition

Formally Refereed

Authors:

Urs Buehlmann, Ed Thomas, Xiaoqui Zuo

Year:

2011

Type:

Scientific Journal

Station:

Northern Research Station

DOI:

https://doi.org/10.1016/j.rcim.2010.12.013

Source:

Robotics and Computer-Integrated Manufacturing. 27: 746-754.

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Abstract

Lumber, 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.

Keywords

cost minimization decision support system, (DSS), cost models, cutting stock problem, decision making, decision process, manufacturing, production planning and control, component production

Citation

Buehlmann, Urs; Thomas, R. Edward; Zuo, Xiaoqui. 2011. Cost minimization through optimized raw material quality composition. Robotics and Computer-Integrated Manufacturing. 27: 746-754.