Enhanced CUSUM control charts for monitoring Coefficient of Variation: A case study in Textile industry

The recent blooming developments of Artificial Intelligence (AI), Internet Things (IoT), and Data Science (DS) have put Smart Manufacturing (SM) into a new context. This leads to more attractions on control charts as one the useful tools that contribute success in SM by anomaly detection (AD) approach. Coefficient variation (CV) is popular statistic used quality SM. In this paper, we propose investigating performance Cumulative sum (CUSUM) monitoring CV with fast initial response (FIR) strategy. chart parameters are also optimized according random shift size given interval proposed Nelder-Mead optimization algorithm. numerical results show FIR CUSUM-γ2 greater than ones. An example yarn at spinning mill design proposed. These findings for practitioners well managers researchers. could be applied other processes various domains such finance, business, industrial processes, etc.