Some simple mathematical aids for cause-and-effect analyses

Edward A. Silver, Thomas R. Rohleder

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

A common approach used in quality or process improvement is cause-and-effect analysis. It involves identifying a (large) number of possible causes of an undesirable effect or problem, and then choosing the sequence of investigation of the possible causes. The philosophy of continuous improvement dictates that any associated modelling should use relatively simple, robust models that provide insights and guidance without extensive data collection or computational requirements. Thus, we present some fairly simple mathematical formulations of the aforementioned sequencing decision.

Original languageEnglish (US)
Pages (from-to)85-92
Number of pages8
JournalJournal of Quality Technology
Volume30
Issue number1
StatePublished - Jan 1998
Externally publishedYes

Fingerprint

Continuous Improvement
Process Improvement
Quality Improvement
Sequencing
Guidance
Formulation
Requirements
Modeling
Continuous improvement
Data collection
Quality improvement
Cause and effect analysis
Process improvement
Model
Philosophy

Keywords

  • Approximation
  • Constrained Optimization
  • Process Improvement
  • Quality Improvement

ASJC Scopus subject areas

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

Cite this

Silver, E. A., & Rohleder, T. R. (1998). Some simple mathematical aids for cause-and-effect analyses. Journal of Quality Technology, 30(1), 85-92.

Some simple mathematical aids for cause-and-effect analyses. / Silver, Edward A.; Rohleder, Thomas R.

In: Journal of Quality Technology, Vol. 30, No. 1, 01.1998, p. 85-92.

Research output: Contribution to journalArticle

Silver, EA & Rohleder, TR 1998, 'Some simple mathematical aids for cause-and-effect analyses', Journal of Quality Technology, vol. 30, no. 1, pp. 85-92.
Silver, Edward A. ; Rohleder, Thomas R. / Some simple mathematical aids for cause-and-effect analyses. In: Journal of Quality Technology. 1998 ; Vol. 30, No. 1. pp. 85-92.
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