Evaluating the precision of bivariate attribute measurements

Jung Lyu, Ming Nan Chen

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Many quality improvement programs employ measurement system analysis (MSA) to ensure the reliability of measurement results, which are the basis for conclusions regarding the behaviour of critical quality characteristics. Gauge repeatability and reproducibility (R&R) study is an important approach for evaluating the precision of MSA. Although many gauge capability studies exist and are common in industry, few have discussed cases with attribute data. Modern manufacturing processes must monitor two or more related quality characteristics simultaneously to enhance the quality management effectiveness. This study presents a novel model for evaluating gauge R&R for bivariate attribute data. An alloy manufacturing case is utilized to illustrate the process and potential of the proposed model. Findings are employed to assess and improve measurement systems with bivariate attribute data.

Original languageEnglish
Pages (from-to)99-110
Number of pages12
JournalJournal of Statistical Computation and Simulation
Volume80
Issue number1
DOIs
Publication statusPublished - 2010 Jan 1

Fingerprint

Measurement System
Gauge
Attribute
Gages
Systems Analysis
Manufacturing
Quality Improvement
Quality Management
Systems analysis
Repeatability
Reproducibility
Quality management
Monitor
Industry
Model
Measurement system
Quality characteristics

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

Cite this

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Evaluating the precision of bivariate attribute measurements. / Lyu, Jung; Chen, Ming Nan.

In: Journal of Statistical Computation and Simulation, Vol. 80, No. 1, 01.01.2010, p. 99-110.

Research output: Contribution to journalArticle

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