Control charts are widely used in industries to monitor a process for quality improvement. When dealing with variables data, we usually employ two control charts to monitor the process location and spread. We give an overview of the control charts proposed in the last decade or so in an effort to use only one chart to simultaneously monitor both process location and spread. Two approaches have been advocated for using one control chart for process monitoring. One approach plots two quality characteristics in the same chart while the other uses one plotting variable to represent the process location and spread.

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A single control chart called Multivariate Maximum Control Chart (Max-Mchart) is proposed in this article that is capable of monitoring the process, with the quality of an item being determined by several correlated quality characteristics. This scheme simultaneously monitors the process location and process spread using only one chart. The chart quickly detects both small and large shifts in the process parameters and indicates the parameter that has shifted. Compared with other recently proposed single multivariate control charts, this chart quickly detects small shifts in the process mean and is also simple to use, as it applies the well known Shewhart control charts procedures to compute the average run lengths.

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