Modeling a response with self-generated and externally generated sources of variation

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8 Scopus citations


Attempts to model the variation of a random response in terms of the factors that affect it and its own self-generated variability constitute the bulk of the scientific and engineering research effort. This is particularly valid for quality engineering, where modeling of a response is often required to solve quality problems or to improve quality. While models that are derived from established domain-specific theories are commonly used in various disciplines, a pragmatic approach may be conceived that assembles under a single general model features that are shared by models developed in disparate and unrelated disciplines. In this paper, we develop a new approach compatible with this concept. On the basis of recently developed inverse normalizing transformations, the new model provides the quantile-relationship between a response (the dependent variable) and the factors that affect it (the independent variables), assuming only that this relationship is either uniformly convex or concave. Furthermore, two independent sources of variation, one internal and one external, are assumed to account for the observed response variation. We demonstrate the validity of the new approach by showing that the new model is a generalization of models that are currently in use in three disparate engineering disciplines: hardware reliability, software reliability, and chemical engineering. Employing some previously published data sets, the modeling competence of the new approach is demonstrated.

Original languageEnglish
Pages (from-to)563-578
Number of pages16
JournalQuality Engineering
Issue number4
StatePublished - 1 Jun 2002
Externally publishedYes


  • Fatigue-life
  • Generalized linear modeling
  • Inverse normalizing transformations
  • Nonnormal populations
  • Software-reliability growth
  • Vapor pressure modeling

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering


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