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Monitoring Process Mean and Variability with One Non-central Chi-square Chart
Authors:A F B Costa  M A Rahim
Institution:1. Department of Production , UNESP-S?o Paulo State University , Brazil;2. Faculty of Administration , University of New Brunswick , Canada
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
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