In monitoring process parameters, we assume normality of the quality
characteristic of interest, which is an ideal assumption. In many practical situations,
we may not know the distributional behavior of the data, and hence,
the need arises use nonparametric techniques. In this study, a nonparametric
double EWMA control chart, namely the NPDEWMA chart, is proposed to
ensure efficient monitoring of the location parameter. The performance of
the proposed chart is evaluated in terms of different run length properties,
such as average, standard deviation and percentiles. The proposed scheme
is compared with its recent existing counterparts, namely the nonparametric
EWMA and the nonparametric CUSUM schemes. The performance measures
used are the average run length (ARL), standard deviation of the run
length (SDRL) and extra quadratic loss (EQL). We observed that the proposed
chart outperforms the said existing schemes to detect shifts in the
process mean level. We also provide an illustrative example for practical
considerations.