Optimal designs for industrial and computer experimentation

本研究的目的是获得用于工业和计算机实验的最佳设计。工业筛选实验经常用于确定哪些因素在所研究的产品或过程的质量中起统计学意义上的重要作用。通常情况下，改变某些实验因素的水平比改变其他因素更困难或更昂贵。在这种情况下，“分裂情节设计”经常出现。本研究考虑了仅由少量运行（例如，12、16、20、24等）组成的分块设计的最佳选择。这种设计为实践者提供了比目前文献中列出的大多数分块设计更灵活的运行规模，因此应该为工业实验节省成本。

This research is concerned with obtaining optimal designs for use in industrial and computer experimentation. Industrial screening experiments are frequently used to ascertain which factors play a statistically significant role in the quality of a product or process under study. It is often the case that the levels of some of the experimental factors are more difficult, or expensive, to vary than the rest. In such settings "split-plot designs" often arise. This research considers the optimal choice of split-plot designs consisting of only a few runs (for example, 12, 16, 20, 24, etc). Such designs offer practitioners more flexible run sizes than most split-plot designs presently cataloged in the literature and as such should result in cost-savings for industrial experimenters.