Powerful Foldover Designs

ABSTRACT The foldover technique for screening designs is well‐known to guarantee zero aliasing of the main effect estimators with respect to two‐factor interactions and quadratic effects. It is a key feature of many popular response surface designs, including central composite designs, definitive screening designs, and most orthogonal, minimally aliased response surface designs. In this paper, we show that the foldover technique is even more powerful, because it produces degrees of freedom for a variance estimator that is independent of model selection. These degrees of freedom are characterized as either pure error or fake factor degrees of freedom. A fast design construction algorithm is presented that minimizes the expected confidence interval criterion to maximize the power of screening main effects. An augmented design and analysis method is also presented to avoid having too many degrees of freedom for estimating variance and to improve model selection performance for second‐order models. Simulation studies show that our new designs are at least as good as traditional designs when effect sparsity and hierarchy hold, but do significantly better when these effect principles do not hold. A real data example is given for a 20‐run experiment where optimization of ethylene concentration is performed by manipulating eight process parameters.

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Publication Details

Journal
Quality and Reliability Engineering International
Published
2025-10-21
DOI
https://doi.org/10.1002/qre.70105
Primary Topic
Advanced Multi-Objective Optimization Algorithms
Type
article
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article

Powerful Foldover Designs

Kyle Vogt‐Lowell, Jonathan W. Stallrich, Rakhi Singh, Fanxing Li
Quality and Reliability Engineering International
Advanced Multi-Objective Optimization Algorithms
article

Powerful Foldover Designs

Kyle Vogt‐Lowell, Jonathan W. Stallrich, Rakhi Singh, Fanxing Li
article en

Abstract

ABSTRACT The foldover technique for screening designs is well‐known to guarantee zero aliasing of the main effect estimators with respect to two‐factor interactions and quadratic effects. It is a key feature of many popular response surface designs, including central composite designs, definitive screening designs, and most orthogonal, minimally aliased response surface designs. In this paper, we show that the foldover technique is even more powerful, because it produces degrees of freedom for a variance estimator that is independent of model selection. These degrees of freedom are characterized as either pure error or fake factor degrees of freedom. A fast design construction algorithm is presented that minimizes the expected confidence interval criterion to maximize the power of screening main effects. An augmented design and analysis method is also presented to avoid having too many degrees of freedom for estimating variance and to improve model selection performance for second‐order models. Simulation studies show that our new designs are at least as good as traditional designs when effect sparsity and hierarchy hold, but do significantly better when these effect principles do not hold. A real data example is given for a 20‐run experiment where optimization of ethylene concentration is performed by manipulating eight process parameters.

Quality and Reliability Engineering InternationalVol. 42(2)
North Carolina State University (US), Indian Institute of Technology Madras (IN), UNC/NCSU Joint Department of Biomedical Engineering (US)
Openalex Percentile: Top 68%
Advanced Multi-Objective Optimization Algorithms
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