<![CDATA[In this study, we aim to build a multivariate control chart for autocorrelated data. We use MEWMA and MEWMV control charts which are free of normality assumption. Time series model is then applied to tackle autocorrelation problem in the data where the control charts require independence assumption. The real dataset used is the quality characteristics of white crystal sugar, also called gula kristal putih (GKP). There are 3 quality characteristics of GKP, namely moisture (%), color of solution (IU), and grain type (mm). It is considered that these quality characteristics are correlated each other. Our results show that the variability process is out of control where there are 5 observations outside the control limits. Meanwhile the mean process is also out of control. The factors causing the out of control include the workers, the raw materials, the measurement, the machines, and the methods. The process capability indices result in the values less than 1 which means the process is not sufficiently capable.]]>
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