Mixture-process variable experiments with noise variables

Heidi B. Goldfarb, Connie M. Borror, Douglas Montgomery

Research output: Contribution to journalArticle

30 Scopus citations

Abstract

In a mixture experiment, the design factors are mixture components whose proportions are varied, and the response variables are assumed to depend only on these component proportions. In addition to the mixture components, the experimenter may be interested in other variables that can be varied independently of one another and of the mixture components. We consider the case where one or more of these variables is a noise variable, or a variable that cannot be controlled in practice. We develop models for these robust mixture formulation problems. We then derive mean and variance functions and illustrate their use in formulation optimization. Cases of uncorrelated and correlated noise variables are addressed.

Original languageEnglish (US)
Pages (from-to)393-405
Number of pages13
JournalJournal of Quality Technology
Volume35
Issue number4
StatePublished - Oct 1 2003

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Keywords

  • Mixture experiments
  • Mixture-process experiments
  • Noise variables
  • Response surface methodology
  • Robust parameter design

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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