The effect of measurement error on the performance of the s chart

Ming Ha Lee, Zhi Yau Lee, Wei Lin Teoh, Vie Ming Tan, Melinda Kong, XinYing Chew

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

In this paper, we look at how measurement error affects the statistical performance of the s chart. The linear covariate error model is used to evaluate the efficiency of the s chart with measurement error. The influence of input factors on the performance of the s chart is explored using the linear covariate error model. Shorter out-of-control average run lengths of the s chart are seen to be connected to smaller measurement error ratios, higher coefficient B values, and more repeated measurements of each item in each sample. To illustrate how to use the s chart when there is measurement error, an example is given.
Original languageEnglish
Title of host publicationInternational Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication (ICMSCE 2023)
EditorsAnton Purnama, Burhanuddin Arafah
PublisherSPIE
ISBN (Electronic)9781510671775
ISBN (Print)9781510671768
DOIs
Publication statusPublished - 19 Dec 2023
Event2023 International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication - Istanbul, Turkey
Duration: 6 Sept 20237 Sept 2023

Publication series

NameProceedings of SPIE
Volume12936
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2023 International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication
Abbreviated titleICMSCE 2023
Country/TerritoryTurkey
CityIstanbul
Period6/09/237/09/23

Keywords

  • Measurement error
  • linear covariate error model
  • s chart

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Applied Mathematics
  • Electrical and Electronic Engineering
  • Computer Science Applications

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