Sharif University of Technology Scientia Iranica 1026-3098 32 16 2026 09 01 Impact of measurement error on maximum hybrid exponentially weighted moving average control chart 24062 10.24200/sci.2021.57789.5417 EN Muhammad Noor-ul-Amin Department of Statistics, COMSATS University Islamabad, Lahore, Pakistan. Amjad Javaid Pakistan Bureau of Statistics, Islamabad, Pakistan. Muhammad Hanif National College of Business Administration and Economics, Lahore, Pakistan. Saddam Akber Abbasi Department of Mathematics, Qatar University, Doha, Qatar. Journal Article 2021 02 22 Statistical process control provides various types of control charts for monitoring mean and variance shifts in the industrial production process individually as well as jointly to improve and maintain the quality of products. Authors proposed control charts based on sample values selected to calculate the desired statistics, assuming that these values are measured correctly. But in a real-life situation, measurements of the values may suffer from errors, ultimately affecting the efficiency of control charts. A few of the researchers in the field of control charts also discussed the problem of measurement error during process monitoring and proposed solutions to avoid losses for producers. We also present a Hybrid Exponentially Weighted Moving Average (HEWMA) control chart for joint monitoring of mean and variance, with the effect of measurement error on the efficiency of this control chart, and name it the Maximum Hybrid Exponentially Weighted Moving Average with Measurement Error (Max-HEWMAME) control chart. The impact of measurement error has been shown in the calculations and presented in the form of Average Run Lengths (ARLs) and Standard Deviations of Run Lengths (SDRLs) using the Monte Carlo simulation method. A real-life example is also included to support the simulation results. https://scientiairanica.sharif.edu/article_24062_53ed2b3a7be0b98f96b0c30153c406f3.pdf