Monitoring of process parameters using Bayesian methodology

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Monitoring of the process parameters is a key to enhancing the performance of the output. For this purpose many statistical tools are used in practice and control chart is one of the most popular choices. Bayesian and Classical setups are two major categories for defining the design structures of control charts. This study is planned to investigate the performance of the process mean control chart (i.e. X̄-Chart) in the Bayesian and Classical environments and compare them in terms of power and/or Average Run Length (ARL), Additionally this article will highlight and address some of the issues with the Bayesian setup of process monitoring for quality and reliability.

Original languageEnglish
Pages (from-to)1-7
Number of pages7
JournalInternational Journal of Agricultural and Statistical Sciences
Volume7
Issue number1
StatePublished - Jun 2011

Keywords

  • Average Run Length (ARL)
  • Bayesian
  • Classical
  • Elicitation
  • Hyperparameters
  • Power
  • Prior uncertainty
  • Unbiasedness
  • X̄-chart

ASJC Scopus subject areas

  • Statistics and Probability
  • Agricultural and Biological Sciences (miscellaneous)
  • Applied Mathematics

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