 Monitoring Process Mean and Variability with One Non-central Chi-square ChartA. F. B. Costa and M. A. Rahim Journal of Applied Statistics, 2004, vol. 31, issue 10, 1171-1183 Abstract: Traditionally, an X-chart is used to control the process mean and an R-chart to control the process variance. However, these charts are not sensitive to small changes in process parameters. A good alternative to these charts is the exponentially weighted moving average (EWMA) control chart for controlling the process mean and variability, which is very effective in detecting small process disturbances. In this paper, we propose a single chart that is based on the non-central chi-square statistic, which is more effective than the joint X and R charts in detecting assignable cause(s) that change the process mean and/or increase variability. It is also shown that the EWMA control chart based on a non-central chi-square statistic is more effective in detecting both increases and decreases in mean and/or variability. Keywords: Monitoring process mean and variance; X chart; EWMA chart; non-central chi-square chart (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:31:y:2004:i:10:p:1171-1183 Ordering information: This journal article can be ordered from DOI: 10.1080/0266476042000285503 Access Statistics for this article Journal of Applied Statistics is currently edited by Robert Aykroyd More articles in Journal of Applied Statistics from Taylor & Francis Journals |
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