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Statistical Quality Control: Recent Advances

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International Encyclopedia of Statistical Science

Statistical quality control aims to achieve the product or process quality by utilizing statistical techniques, in which statistical process control (SPC) has been demonstrated to be one primary tool for monitoring the process or product quality. Since 1920s, the control chart, as one of the most important SPC techniques, has been widely studied.

Univariate Control Charts Versus Multivariate Control Charts

In terms of the number of variables, control charts can be classified into two types, that is, univariate control charts and multivariate control charts.

The performance of the conventional univariate control charts, including Shewhart control charts, cumulative sum (CUSUM) control charts and exponentially weighted moving average (EWMA) control charts have been extensively reviewed. The research demonstrates that the Shewhart chart is more sensitive to large shifts than the EWMA and CUSUM chart and vice versa. These traditional control charts usually assume that the observations are...

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Tsung, F., Shang, Y., Ning, X. (2011). Statistical Quality Control: Recent Advances. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_83

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