Authors: Shay R. Capehart, Ahmet Keha, Murat Kulahci, Douglas C. Montgomery
Addresses: Department of Mathematics, Air Force Institute of Technology, Wright-Patterson AFB, OH 45433, USA. ' Department of Industrial, Systems and Operations Engineering, Arizona State University, Phoenix, AZ 85287, USA. ' Department of Informatics and Mathematical Modelling, Technical University of Denmark, Lyngby, 2830, Denmark. ' Department of Industrial, Systems and Operations Engineering, Arizona State University, Phoenix, AZ 85287, USA
Abstract: Split-plot designs are commonly used in industrial experiments when there are hard-to-change and easy-to-change factors. Due to the number of factors and resource limitations, it is more practical to run a fractional factorial split-plot (FFSP) design. These designs are variations of the fractional factorial (FF) design, with the restricted randomisation structure to account for the whole plots and subplots. We discuss the formulation of FFSP designs using integer programming (IP) to achieve various design criteria. We specifically look at the maximum number of clear two-factor interactions and variations on this criterion.
Keywords: design criteria; clear effects; fractional factorial design; tailor-made designs; hard-to-change factors; split-plot design; integer programming.
International Journal of Experimental Design and Process Optimisation, 2011 Vol.2 No.1, pp.34 - 57
Published online: 14 Jan 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article