Scientia Iranica

Scientia Iranica

Impact of measurement error on maximum hybrid exponentially weighted moving average control chart

Document Type : Review Article

Authors
Muhammad Noor-ul-Amin 1
Amjad Javaid 2
Muhammad Hanif 3
Saddam Akber Abbasi 4
1 Department of Statistics, COMSATS University Islamabad, Lahore, Pakistan.
2 Pakistan Bureau of Statistics, Islamabad, Pakistan.
3 National College of Business Administration and Economics, Lahore, Pakistan.
4 Department of Mathematics, Qatar University, Doha, Qatar.
10.24200/sci.2021.57789.5417
Abstract
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.
Keywords
Statistical process control
Control charts
Measurement error
Past information
Quality characteristic
Subjects
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Scientia Iranica
Volume 32, Issue 16
Transactions on Industrial Engineering
September and October 2025 Article ID:5417

  • Receive Date 22 February 2021
  • Revise Date 08 August 2021
  • Accept Date 15 November 2021