Definitive screening designs (DSDs) uniquely address the key needs of many experimenters. How else can we explain the rapid and enthusiastic adoption of DSDs since their discovery was published in 2011? For many experimenters, 13- or 17-run DSDs for five to seven factors are go-to designs when screening for the few driving factors. Along with ‘Fit Definitive Screening’ in JMP, you potentially have a simple, efficient and effective experimental workflow to find the important main effects, interactions and curvilinear behaviors of these factors. If only three of the factors are active, you can fit the full second-order RSM model and achieve screening and optimization in one step. But what if more than three factors are active? When ambiguity occurs is there a simple next step? Or does the complexity of this situation become a barrier to adoption of DSDs? In this presentation, you will first hear about real-life examples that demonstrate the value of DSDs. You will then see simple ways to augment these DSDs, ensuring that the structure and properties can be preserved to maintain the benefits of DSDs. Consequently, more people in more situations can benefit from the workflow of sequential DOE and DSDs.
The attached pdf discusses the challenge and the search for a solution.
Practical implementation of these solutions is discussed in Strategies to Combat Problems Employing DSDs by Dr. Paul Nelson. The article is Part 3 in a series of articles exploring Practical (Real-life) Implementation of Sequential Design of Experiments and the Introduction of Definitive Screening Designs.
