Information visualization about changes of process mean and variance on (¯x, s) control chart

Yasuhiko Takemoto, Ikuo Arizono

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The (Formula presented.) control chart is one of simultaneous control charts to monitor process mean and variance on (Formula presented.) coordinate. The primary purpose of the (Formula presented.) control chart has been the judgement of the process condition at the time of individual samplings. Then, for the purpose of identifying some process parameters which are responsible for an out-of-control signal in the (Formula presented.) control chart, a method based on Akaike Information Criterion (AIC) has been proposed in recent years. However, similar to other simultaneous control charts, a disadvantage of the (Formula presented.) control chart is that the time-ordered nature of the data is visually lost. In this research, we address a way of overcoming the disadvantage of the (Formula presented.) control chart by giving visual information on the time progress. At first, we locate areas indicating a caution and a warning of an out-of-control condition on the (Formula presented.) control chart using AIC. Then, a method of drawing a time series of the sample mean and standard deviation on the (Formula presented.) control chart is considered using some techniques of the information visualization. Based on the consideration above, the procedure of perceiving the track of changes in the process condition up to the out-of-control signal is proposed.

Original languageEnglish
Pages (from-to)496-510
Number of pages15
JournalQuality Technology and Quantitative Management
Volume16
Issue number4
DOIs
Publication statusPublished - Jul 4 2019

Keywords

  • Akaike information criterion (AIC)
  • Kullback–Leibler information
  • caution and warning areas
  • control chart
  • simultaneous monitoring schemes

ASJC Scopus subject areas

  • Business and International Management
  • Industrial relations
  • Management Science and Operations Research
  • Information Systems and Management
  • Management of Technology and Innovation

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