Robust parameter design using a supersaturated design for a response surface model

Shun Matsuura, Hideo Suzuki, Takahisa Iida, Hirotaka Kure, Hatsuo Mori

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Recently, the application of response surface methodology (RSM) to robust parameter design has attracted a great deal of attention. In some cases, experiments are very expensive and may require a great deal of time to perform. Central composite designs (CCDs) and Box and Behnken designs (BBDs), which are commonly used for RSM, may lead to an unacceptably large number of experimental runs. In this paper, a supersaturated design for RSM is constructed and its application to robust parameter design is proposed. A response surface model is fitted using data from the designed experiment and a stepwise variable selection. An illustrative example is presented to show that the proposed method considerably reduces the number of experimental runs, as compared with CCDs and BBDs. Numerical experiments are also conducted in which type I and II error rates are evaluated. The results imply that the proposed method may be effective for finding the effects (i.e. main effects, two-factor interactions, and pure quadratic effects) of active factors under the 'effect sparsity' assumption.

Original languageEnglish
Pages (from-to)541-554
Number of pages14
JournalQuality and Reliability Engineering International
Issue number4
Publication statusPublished - 2011 Jun


  • central composite design
  • response surface methodology
  • robust parameter design
  • second-order model
  • supersaturated design

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Management Science and Operations Research


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