Control charts are generally used to detect mean process changes in continuous processes. However, counting procedures that characterize product quality are popular in production processes, such as the number of defects or the proportion of defective products. This research aims to investigate using the Modified Exponentially Weighted Moving Average combined with a nonparametric Sign Rank control chart, namely MEWMA-SR chart is a novel tool. Comparative analyses involving different run length measures are conducted to evaluate the proposed scheme against MEWMA, MEWMA-SR, and classical EWMA charts. The performance of the MEWMA-SR chart is assessed using Monte Carlo simulations based on its run-length profiles. It was found that the proposed combination control chart was effective in detecting changes better than other control charts along with presenting applications with real data. A study further validates the proposed chart’s practical utility through a case study analyzing COVID-19 mortality data.