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Monitoring Process Mean and Variability with One Non-central Chi-square Chart

A. 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)
Date: 2004
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Citations: View citations in EconPapers (7)

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DOI: 10.1080/0266476042000285503

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