MEWMA Chart
There are no points above the upper control limit; therefore the variability can be considered stable. However, there are a few points that are higher than the rest that could be investigated.
The multivariate form of the EWMA control chart. Use a MEWMA chart to simultaneously monitor two or more related process characteristics in an exponentially weighted control chart. For example, use a MEWMA chart to monitor temperature and pressure in a plastic injection-molding process. Each MEWMA point incorporates information from all the previous subgroups or observations in combination with a user-defined weighting factor. MEWMA charts can help you detect small process shifts quicker than other multivariate charts, such as the TSquared control chart.
Another advantage of MEWMA charts is that they are not greatly influenced when a small or large value enters the calculation. Also, MEWMA charts can be custom tailored to detect any size shift in the process. Because of this, they are often used to monitor in-control processes for detecting small shifts away from the target.
For example the following MEWMA is of the plastic injection-molding example described above:
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MEWMA Chart |
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There are no points above the upper control limit; therefore the variability can be considered stable. However, there are a few points that are higher than the rest that could be investigated.
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The plot points can be based on either subgroups or individual observations. When data are in subgroups, the mean of all the observations in each subgroup is calculated. Exponentially weighted moving averages are then formed from these means. When you have individual observations, exponentially weighted moving averages are formed from the individual observations.