On designing a new control chart for Rayleigh distributed processes with an application to monitor glass fiber strength

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

In this study, a Shewhart type control chart, namely (Formula presented.) chart, has been proposed to monitor a process that follows Rayleigh distribution. The proposed (Formula presented.) chart is implemented to monitor the single scale parameter of the Rayleigh distributed process. We have studied the proposed chart under two type of control limits namely probability and (Formula presented.) -sigma limits. The performance of the proposed chart has been assessed by using power function. In addition, we have investigated run length properties including average run length (ARL), standard deviation of run length (SDRL) and median run length (MDRL). The analysis of run length profile reveals that the proposed VR chart outperforms the existing charts including the traditional Shewhart control chart and V control charts under Rayleigh distribution. The construction process for the newly proposed chart has been demonstrated using a simulated data. Finally, a real application of the proposed (Formula presented.) chart, along with the existing (Formula presented.) chart, is presented that evaluates the strength of glass fiber in a manufacturing process.

Original languageEnglish
Pages (from-to)3168-3184
Number of pages17
JournalCommunications in Statistics Part B: Simulation and Computation
Volume51
Issue number6
DOIs
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.

Keywords

  • Control chart
  • Gamma distribution
  • Maximum likelihood estimation
  • Rayleigh distribution
  • Run length

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation

Fingerprint

Dive into the research topics of 'On designing a new control chart for Rayleigh distributed processes with an application to monitor glass fiber strength'. Together they form a unique fingerprint.

Cite this