Investigating the Impact of Ranked Set Sampling in Nonparametric CUSUM Control Charts

Muhammad Abid*, Hafiz Zafar Nazir, Muhammad Riaz, Zhengyan Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Nonparametric control charts can be useful as an alternative in practice to the data expert when there is a lack of knowledge about the underlying distribution. In this study, a nonparametric cumulative sum (CUSUM) sign control chart for monitoring and detecting possible deviation from the process mean using ranked set sampling is proposed. Ranked set sampling is an effective method when the observations are inexpensive, and measurements are perhaps destructive. The average run length is used as performance measure for the proposed nonparametric CUSUM sign chart. Simulation study shows that the proposed version of the CUSUM sign chart using ranked set sampling generally outperforms than that version of the nonparametric CUSUM sign chart and the parametric CUSUM control chart using simple random sampling scheme. An illustrative example is also provided for practical consideration.

Original languageEnglish
Pages (from-to)203-214
Number of pages12
JournalQuality and Reliability Engineering International
Volume33
Issue number1
DOIs
StatePublished - 1 Feb 2017

Bibliographical note

Publisher Copyright:
Copyright © 2016 John Wiley & Sons, Ltd.

Keywords

  • CUSUM chart
  • average run length
  • binomial distribution
  • nonparametric
  • ranked set sampling

ASJC Scopus subject areas

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

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