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Improving lumber cut-up manufacturing efficiency using optimization methods.

机译：使用优化方法提高锯材的制造效率。

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摘要

Although automatic and computerized equipment has been incorporated into modern gang-rip first rough mills, many of the process steps still rely on human decision making. Examples include choosing the appropriate lumber grade for processing; designing the optimal gang-rip saw arbor; and defining part priority values for the chop saw. This research was based on the hypothesis that these decisions can be improved through optimization strategies without extra capital investment.; This research first developed a software program, the Gang Ripsaw Optimizer (GRO) written in C++ language. GRO generates an optimized fixed-blade arbor by reiteratively searching and comparing optimal part combinations provided by the Romi-Rip 2.0 simulator. Results showed that GRO provides better solutions than two other available arbor design programs.; Second, this research created a system that generates static priority values through a 20-factor face-center central composite design. Various formulas were formed based on part sizes. Results indicated that the static value mode could produce a yield comparable to that given by the dynamic modes for representative cutting bills. On average, the yield from the static value mode was 0.99 percent lower than that from the complex dynamic exponential mode, 0.97 percent lower than the simple dynamic exponential mode, and 0.87 percent lower than simple dynamic mode, respectively.; Third, the simple linearity assumption required to apply linear programming to solve the least-cost lumber grade-mix problem was examined. The study statistically proved that the simple linear relationship between yield and two- and three-grade lumber combinations does not hold for 90 percent of the industrial cutting bills. To solve the least-cost lumber grade-mix problem without violating the assumption, a five-factor mixture design was applied. Upper bounds were applied to 3A Common lumber, according to the cutting bill's level of difficulty, because of the limited availability of larger parts. By locating the lowest cost point from the lumber grade—cost response surface, the corresponding lumber grade mix was obtained. This statistical method allows the user to pre-specify the lumber grades that are available.
机译：尽管自动和计算机化的设备已被集成到现代化的立式首批粗轧机中，但许多工艺步骤仍依赖于人为决策。例如，选择合适的木材等级进行加工；设计最佳的组合式锯木机；并为劈锯定义零件优先级值。该研究基于以下假设：可以通过优化策略来改进这些决策，而无需额外的资本投资。这项研究首先开发了一种软件程序，即用C ++语言编写的Gang Ripsaw Optimizer（GRO）。 GRO通过反复搜索和比较Romi-Rip 2.0仿真器提供的最佳零件组合来生成优化的固定刀片刀杆。结果表明，与其他两个可用的乔木设计程序相比，GRO提供了更好的解决方案。其次，这项研究创建了一个系统，该系统通过20个因素的面部中心中央复合设计生成静态优先级值。根据零件尺寸形成各种公式。结果表明，静态值模式可以产生与动态模式下具有代表性的单张纸相当的产量。平均而言，静态值模式的收益率比复杂动态指数模式的收益率低0.99％，比简单动态指数模式的收益率低0.97％，比简单动态指数模式的收益率低0.87％。第三，研究了应用线性规划来解决成本最低的木材等级混合问题所需的简单线性假设。该研究从统计学上证明，产量与两级和三级木材组合之间的简单线性关系不能满足90％的工业采伐费用。为了在不违反假设的前提下解决成本最低的木材级配问题，采用了五因素混合设计。根据切割法案的难易程度，将上限应用于3A普通木材，因为较大零件的可用性有限。通过从木材等级－成本响应面中找出最低成本点，可以得到相应的木材等级混合物。这种统计方法允许用户预先指定可用的木材等级。

著录项

  • 作者

    Zuo, Xiaoqiu.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Agriculture Wood Technology.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 222 p.
  • 总页数 222
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 森林采运与利用;
  • 关键词

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