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Comparing methods for design follow-up: revisiting a metal-cutting case study

Authors

  • David J. Edwards,

    Corresponding author
    1. Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA
    • Correspondence to: David J. Edwards, Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA.

      E-mail: dedwards7@vcu.edu

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  • Maria L. Weese,

    1. Department of Information Systems and Analytics, Miami University, Oxford, OH 45056, USA
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  • Gregory A. Palmer

    1. Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA
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Abstract

Adding another fraction to an initial fractional factorial design is often required to resolve ambiguities with respect to aliasing of factorial effects from the initial experiment and/or to improve estimation precision. Multiple techniques for design follow-up exist; the choice of which is often made on the basis of the initial design and its analysis, resources available, experimental objectives, and so on. In this paper, we compare four design follow-up strategies: foldover, semifoldover, D-optimal, and Bayesian (MD-optimal) in the context of a metal-cutting case study previously utilized to compare fractional factorials of different run sizes. Follow-up designs are compared for each of a inline image, inline image, and Plackett–Burman initial experiments. Our empirical results suggest that a single follow-up strategy does not outperform all others in every situation. This case study serves to illustrate design augmentation possibilities for practitioners and provides some basis for the selection of a follow-up experiment. Copyright © 2013 John Wiley & Sons, Ltd.

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