Design of Experiments: An Overview

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Abstract

Design Of Experiments (DOE) is needed for experiments with real-life systems, and with either deterministic or random simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random simulation. DOE may have two goals: sensitivity analysis including factor screening and optimization. This contribution starts with classic DOE including 2k-p and Central Composite designs. Next, it discusses factor screening through Sequential Bifurcation. Then it discusses Kriging including Latin Hyper cube Sampling and sequential designs. It ends with optimization through Generalized Response Surface Methodology and Kriging combined with Mathematical Programming, including Taguchian robust optimization.
Original languageEnglish
Place of PublicationTilburg
PublisherOperations research
Number of pages21
Volume2008-70
Publication statusPublished - 2008

Publication series

NameCentER Discussion Paper
Volume2008-70

Keywords

  • simulation
  • sensitivity analysis
  • optimization
  • factor screening
  • Kriging
  • RSM
  • Taguchi

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