The use of statistical methods in industry is increasing. Arguably, the most cost-beneficial of these methods for quality and productivity improvement is statistical design of experiments. A trial-and-error search for the vital few factors that most affect quality is costly and time-consuming. The purpose of experimental design is to characterize, predict, and then improve the behavior of any system or process. Designed experiments are a cost-effective way to accomplish these goals.
This chapter presents an overview of using the custom designer. The Examples Using the Custom Designer section, includes specific examples for creating various types of custom designs, such as mixture designs and split plots.