<p>This study presents the construction of wavelet-based control charts, which do not require the normality assumption. The control charts are nonparametric multivariate in nature and can deal with autocorrelated data. To remove nonstationary from the data, wavelet decomposition is used, and the extracted stationary residuals are modeled by using the autoregressive model. We apply different multivariate cumulative sum (CUSUM) control charts on the extracted residual matrix and evaluate their performance from the wavelet decomposed data. The performance of the control charts is assessed using the in-control and out-of-control average run length (ARL). Furthermore, a comparison of spatial sign nonparametric CUSUM control chart and nonparametric CUSUM control chart is also a part of this study.</p>