Nonparametric progressive mean control chart for monitoring process target

Saddam Akber Abbasi*, Arden Miller, Muhammad Riaz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

Nonparametric control charts are widely used when the parametric distribution of the quality characteristic of interest is questionable. In this study, we proposed a nonparametric progressive mean control chart, namely the nonparametric progressive mean chart, for efficient detection of disturbances in process location or target. The proposed chart is compared with the recently proposed nonparametric exponentially weighted moving average and nonparametric cumulative sum charts using different run length characteristics such as the average run length, standard deviation of the run length, and the percentile points of the run length distribution. The comparisons revealed that the proposed chart outperformed recent nonparametric exponentially weighted moving average and nonparametric cumulative sum charts, in terms of detecting the shifts in process target. A real life example concerning the fill heights of soft drink beverage bottles is also provided to illustrate the application of the proposed nonparametric control chart.

Original languageEnglish
Pages (from-to)1069-1080
Number of pages12
JournalQuality and Reliability Engineering International
Volume29
Issue number7
DOIs
StatePublished - Nov 2013

Keywords

  • Monte Carlo simulations
  • nonparametric control chart
  • process location
  • progressive mean
  • run length distribution

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Management Science and Operations Research

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