Proposal of advanced taguchi's linear graphs for split-plot experiments

Tomomichi Suzuki, Hironobu Kawamura, Seiichi Yasui, Yoshikazu Ojima

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Taguchi's orthogonal arrays and linear graphs are convenient tools for the design of fractional factorial experiments, especially for practitioners. Taguchi also proposed how to use them in split-plot designs and prepared linear graphs for split-plot designs. For the orthogonal array of order 16, Taguchi proposed one which is called L16 orthogonal array. Taguchi presented 18 linear graphs when a L16 orthogonal array is used in split-plot designs. Those linear graphs are capable of showing main effects of whole plots, subplots, sub-subplots, and so on, but they are not capable of showing interaction effects of plots of different levels. Also, those linear graphs do not cover all the possible designs, and there exist a lot of other linear graphs that can be applied when using L16 orthogonal arrays. The primary objective of this paper is to propose an improved version of linear graphs. Another purpose of this paper is to investigate how to list all the possible linear graphs that can be applied when using L16 orthogonal arrays. A proposal is made and many new linear graphs are presented.

Original languageEnglish
Title of host publicationFrontiers in Statistical Quality Control 10
PublisherKluwer Academic Publishers
Pages339-348
Number of pages10
ISBN (Print)9783790828450
DOIs
Publication statusPublished - 2012
Event2010 10th International Workshop on Intelligent Statistical Quality Control - Seattle, WA, United States
Duration: 18 Aug 201020 Aug 2010

Publication series

NameFrontiers in Statistical Quality Control 10

Conference

Conference2010 10th International Workshop on Intelligent Statistical Quality Control
Country/TerritoryUnited States
CitySeattle, WA
Period18/08/1020/08/10

Keywords

  • Fractional factorial design
  • Orthogonal array
  • Two-factor interaction

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