Single-Step Factor Screening and Response Surface Optimization Using Optimal Designs with Minimal Aliasing

Cheng and Wu (2001) introduced a method for response surface exploration using only one design by using a 3-level design to first screen a large number of factors and then project onto the significant factors to perform response surface exploration. Previous work generally involved selecting designs based on projection properties first and aliasing structure second. However, having good projection properties is of little concern if the correct factors cannot be identified. We apply Jones and Nachtsheim’s (2009) method for finding optimal designs with minimal aliasing to find 18, 27, and 30-run designs to use for single-step screening and optimization. Our designs have better factor screening capabilities than the designs of Cheng and Wu (2001) and Xu et al. (2004), while maintaining similar D-efficiencies and allowing all projections to fit a full second order model