Robust analysis of variance: process design and quality improvement

Avi Giloni, Sridhar Seshadri, Jeffrey S. Simonoff

Research output: Contribution to journalArticlepeer-review


We discuss the use of robust Analysis Of Variance (ANOVA) techniques as applied to quality engineering. ANOVA is the cornerstone for uncovering the effects of design factors on performance. Our goal is to utilise methodologies that yield similar results to standard methods when the underlying assumptions are satisfied, but are also relatively unaffected by outliers (observations that are inconsistent with the general pattern in the data). We do this by utilising statistical software to implement robust ANOVA methods, which are no more difficult to perform than ordinary ANOVA. We study several examples to illustrate how using standard techniques can lead to misleading inferences about the process being examined, which are avoided when using a robust analysis. We further demonstrate that assessments of the importance of factors for quality design can be seriously compromised when utilising standard methods as opposed to robust methods.

Original languageEnglish (US)
Pages (from-to)306-319
Number of pages14
JournalInternational Journal of Productivity and Quality Management
Issue number3
StatePublished - 2006
Externally publishedYes


  • LAD regression
  • M-estimator
  • Taguchi
  • median
  • outlier
  • quality engineering
  • robust design
  • robust statistics
  • signal-to-noise ratio

ASJC Scopus subject areas

  • Business, Management and Accounting(all)


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