Multivariate Quality Control Charts Startup Panel - Quick Tab

Select the Quick tab of the Multivariate Quality Control Charts Startup Panel to access the options described here.

Hotelling T2 Chart for Individuals. Select Hotelling T2 Chart for Individuals and click the OK button to display the Defining Variables for Hotelling T-Square (Individuals) Chart dialog box. You can also double-click on Hotelling T2 Chart for Individuals to display the dialog box. This analysis will produce a Hotelling T2 chart for sample means, for multiple continuous variables, as well as a generalized variance chart for multivariate control of within-sample variability (variance/covariance).

Hotelling T2 Chart for Means. Select Hotelling T2 Chart for Means and click the OK button to display the Defining Variables for Hotelling T-Square (Means)/GV Chart dialog box. This analysis will produce a Hotelling T2 chart for sample means, for multiple continuous variables, as well as a generalized variance chart for multivariate control of within-sample variability (variance/covariance).
Element Name Description
MEWMA Chart for Individuals Select MEWMA Chart for Individuals and click the OK button to display the Defining Variables for MEWMA (Individuals) Chart dialog box. This analysis will produce a multivariate exponentially weighted moving average chart for individual observations. This chart is particularly well suited for identifying drift (small process shifts) of individual observations or measurements from a multivariate process.
MEWMA Chart for Means Select MEWMA Chart for Means and click the OK button to display the Defining Variables for MEWMA (Means) Chart dialog box. This analysis will produce a multivariate exponentially weighted moving average chart for means. This chart is particularly well suited for identifying drift (small process shifts) of sample means for a multivariate process
Multivariate CUSUM Chart Select Multivariate CUSUM Chart and click the OK button to display the Defining Variables for Multivariate CUSUM chart dialog box. This analysis will produce a multivariate cumulative sum chart, or MCUSUM. Like the MEWMA chart for individual observations, this chart is particularly well suited for identifying drift (small process shifts) of individual observations or measurements from a multivariate process.
Multiple Stream X and MR Chart Select Multiple Stream X and MR Chart and click the OK button to display the Defining Variables for Multiple Stream X and MR chart dialog box. This analysis will produce a multiple stream chart for individual observations, and multiple stream moving range chart. Select this chart to control/monitor multiple identical processes (e.g., multiple machines producing the same parts), to identify quickly when one of the processes changes (produces values that are different from those produced by the other process streams, e.g., machine wear).
Multiple Stream X-Bar and R Chart Select Multiple Stream X-Bar and R Chart and click the OK button to display the Defining Variables for Multiple Stream X-Bar and R chart dialog box. This analysis will produce a multiple stream chart for sample means and multiple stream range chart. Select this chart to control/monitor sample means for multiple identical processes (e.g., multiple machines producing the same parts), to identify quickly when one of the processes changes (produces values that are different from those produced by the other process streams, e.g., machine wear).
Multiple Stream X-Bar and S Chart Select Multiple Stream X-Bar and S Chart and click the OK button to display the Defining Variables for Multiple Stream X-Bar and S Chart dialog box. This analysis will produce a multiple stream chart for sample means and multiple stream standard deviation chart. This chart is identical to the multiple stream X-bar and R chart, except that sample standard deviations (instead of ranges) are used to monitor variability.

See also, Common Types of Multivariate Control Charts and Multivariate Quality Control Overview.