Sharif University of Technology Scientia Iranica 1026-3098 31 15 2024 08 01 Monitoring coefficient of variation using variable sampling interval double exponentially weighted moving average charts 1293 1312 22539 10.24200/sci.2021.58623.5819 EN X. L. Hu Institute of High-Quality Development Evaluation, Nanjing University of Posts and Telecommunications, Nanjing, China 0000-0002-5556-2612 S. Y. Zhang School of Management, Nanjing University of Posts and Telecommunications, Nanjing, China Y. Zhang School of Management, Tianjin University of Commerce, Tianjin, China J. J. Zhang Department of Mathematics, Liaoning University, Shenyang, China P. P. Zhou School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing, China Journal Article 2021 06 29 As a measure of relative variability, the coefficient of variation (CV) is a valuable charting statistic in statistical process control. Great efforts have been devoted to monitoring CV efficiently. To further improve the performance of CV charts, this paper proposes three Double Exponentially Weighted Moving Average (DEWMA) charts by incorporating Variable Sampling Interval (VSI) strategies to monitor the CV squared. The run length properties of the proposed charts are evaluated via Monte Carlo simulations. Comparative studies show that the proposed VSI DEWMA CV charts detect the process shifts faster than the existing CV charts. A real data example is presented to illustrate the VSI DEWMA CV charts. https://scientiairanica.sharif.edu/article_22539_dd70b24049efc557de07e8e5264cb98c.pdf