Analysis of functional responses from robust design studies

Vijayan N. Nair, Winson Taam, Qian K. Ye

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

Robust design studies with functional responses are becoming increasingly common. The goal in these studies is to analyze location and dispersion effects and optimize performance over a range of input-output values. Taguchi and others have proposed the so-called signal-to-noise ratio analysis for robust design with dynamic characteristics. We consider more general and flexible methods for analyzing location and dispersion effects from such studies and use three real applications to illustrate the methods. Two applications demonstrate the usefulness of functional regression techniques for location and dispersion analysis while the third illustrates a parametric analysis with two-stage modeling. Both a mean-variance analysis for random selection of noise settings as well as a control-by-noise interaction analysis for explicitly controlled noise factors are considered.

Original languageEnglish (US)
Pages (from-to)355-371
Number of pages17
JournalJournal of Quality Technology
Volume34
Issue number4
StatePublished - Oct 2002
Externally publishedYes

Fingerprint

Functional Response
Robust Design
Dispersion Effect
Noise Factor
Parametric Analysis
Signal to noise ratio
Dynamic Characteristics
Regression
Optimise
Robust design
Output
Interaction
Modeling
Range of data
Demonstrate

Keywords

  • Design of experiments
  • Functional data analysis
  • Quality improvement
  • Variation reduction

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Statistics and Probability
  • Management Science and Operations Research

Cite this

Analysis of functional responses from robust design studies. / Nair, Vijayan N.; Taam, Winson; Ye, Qian K.

In: Journal of Quality Technology, Vol. 34, No. 4, 10.2002, p. 355-371.

Research output: Contribution to journalArticle

Nair, Vijayan N. ; Taam, Winson ; Ye, Qian K. / Analysis of functional responses from robust design studies. In: Journal of Quality Technology. 2002 ; Vol. 34, No. 4. pp. 355-371.
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