Abstract
The multivariate exponentially weighted moving average (MEWMA) control chart, in which the smoothing parameter is a principal diagonal matrix, is established based on the assumption that the samples follow the standard normal distribution to monitor the multivariate quality characteristics. However, monitoring quality characteristics always exists in the whole process. To make the MEWMA control chart more effective, a modified multivariate exponentially weighted moving average control chart, namely practical MEWMA (PEWMA) control chart, is proposed, in which the smoothing coefficient matrix is extended to a full-rank matrix which the smoothing parameter are all not zero. Analysis of both the in-control and out-of-control statistical performance of PEWMA control chart illustrate that the average run length of PEMWA control chart is more superior to the MEWMA. Finally combined with a factory example, a minimisation cost model is constructed based on the Lorenzen-Vance economic model to optimise the parameter combination.
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