Constructing General Orthogonal Fractional Factorial Split-Plot Designs

Constructing General Orthogonal Fractional Factorial Split-Plot Designs

Sartono, B.
Goos, P.
Schoen, E.

2015

While the orthogonal design of split-plot fractional factorial experiments has received much attention already, there are still major voids in the literature. First, designs with one or more factors acting at more than two levels have not yet been considered. Second, published work on nonregular fractional factorial split-plot designs was either based only on Plackett-Burman designs, or on small nonregular designs with limited numbers of factors. In this article, we present a novel approach to designing general orthogonal fractional factorial split-plot designs. One key feature of our approach is that it can be used to construct two-level designs as well as designs involving one or more factors with more than two levels. Moreover, the approach can be used to create two-level designs that match or outperform alternative designs in the literature, and to create two-level designs that cannot be constructed using existing methodology. Our new approach involves the use of integer linear programming and mixed integer linear programming, and, for large design problems, it combines integer linear programming with variable neighborhood search. We demonstrate the usefulness of our approach by constructing two-level split-plot designs of 16-96 runs, an 81-run three-level split-plot design, and a 48-run mixed-level split-plot design. Supplementary materials for this article are available online. © 2015 American Statistical Association and the American Society for Quality.

Life
RAPID - Risk Analysis for Products in Development
ELSS - Earth, Life and Social Sciences
Predictive Health Technologies
Science
Healthy Living
Integer linear programming
Mixed-level design
Integer programming
Optimization
Product design
Integer Linear Programming
Mixed levels
Multi-level designs
Orthogonal array
Two-level designs
Variable neighborhood search
Design

http://resolver.tudelft.nl/uuid:21e0645e-a8f3-4058-afc5-d0e675bc4ace

https://doi.org/10.1080/00401706.2014.958198

529822

0040-1706

Technometrics, 57 (4), 488-502

article