Orthogonal minimally aliased response surface (OMARS) designs permit the study of quantitative factors at three levels using an economical number of runs. In these designs, the linear effects of the factors are neither aliased with each other nor with the quadratic effects and the two-factor interactions. Complete catalogs of OMARS designs with up to five factors have been obtained using an enumeration algorithm. However, the algorithm is computationally demanding for designs with many factors and runs. To overcome this issue, we propose a construction method for large OMARS designs that concatenates two definitive screening designs and improves the statistical features of its parent designs. The concatenation employs an algorithm that minimizes the aliasing among the second-order effects using foldover techniques and column permutations for one of the parent designs. We study the properties of the new OMARS designs and compare them with alternative designs in the literature.
翻译:正交最小别名响应曲面(OMARS)设计允许以经济化的试验次数研究三水平定量因子。在此类设计中,因子的线性效应既不会相互混淆,也不会与二次效应及双因子交互作用产生别名。通过枚举算法,目前已获得包含最多五个因子的OMARS设计完整目录。然而,该算法在处理多因子、多试验次数的设计时计算量极大。为克服此问题,本文提出一种构建大型OMARS设计的方法,该方法通过拼接两个确定性筛选设计并提升其母设计的统计特性。拼接过程采用一种算法,通过折叠反转技术和列置换操作对其中一个母设计进行处理,以最小化二阶效应间的别名现象。本文研究了新型OMARS设计的性质,并与文献中的替代设计进行了比较。