Monitoring process mean and variability with one non-central chi-square chart
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Data
2004-12-01
Autores
Costa, AFB
Rahim, M. A.
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Título de Volume
Editor
Carfax Publishing
Resumo
Traditionally, an (X) over bar -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) over bar 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.
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Palavras-chave
monitoring process mean and variance, (X)over-bar chart, EWMA chart, non-central chi-square chart
Como citar
Journal of Applied Statistics. Basingstoke: Carfax Publishing, v. 31, n. 10, p. 1171-1183, 2004.