A Distribution‐freeCUSUMChart for Monitoring Variability of AutocorrelatedProcesses |
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| Authors: | Seong‐Hee Kim |
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| Affiliation: | H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA |
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| Abstract: | We present a distribution‐free tabular cumulative sum chart for monitoring the variability of an autocorrelated process. A quantity known as the asymptotic variance parameter is employed as a measure of the variability, and a distribution‐free tabular cumulative sum chart is applied to variance estimates calculated from batches of nonoverlapping samples. The proposed chart is applicable to a stationary process with a general marginal distribution and a general autocorrelation structure. It also determines control limits analytically without trial‐and‐error simulations. The performance of the proposed chart is tested on stationary processes with both normal and nonnormal marginals with various autocorrelation structures. Copyright © 2014 John Wiley & Sons, Ltd. |
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| Keywords: | statistical process control variability autocorrelated processes stationary processes distribution‐free statistical methods |
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