Designing fractional factorial split-plot experiments using integer programming

Shay R. Capehart, Ahmet Keha, Murat Kulahci, Douglas C. Montgomery

    Research output: Contribution to journalJournal articleResearchpeer-review


    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.
    Original languageEnglish
    JournalInternational Journal of Experimental Design and Process Optimisation
    Issue number1
    Pages (from-to)34-57
    Publication statusPublished - 2011


    • design criterion
    • Clear Effects
    • Fractional Factorial
    • FF
    • Tailor-made designs
    • Hard-to-change factors


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