Monitoring coefficient of variation using variable sampling interval double exponentially weighted moving average charts

Document Type : Article

Authors

1 Institute of High-Quality Development Evaluation, Nanjing University of Posts and Telecommunications, Nanjing, China

2 School of Management, Nanjing University of Posts and Telecommunications, Nanjing, China

3 School of Management, Tianjin University of Commerce, Tianjin, China

4 Department of Mathematics, Liaoning University, Shenyang, China

5 School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing, China

Abstract

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.

Keywords

References

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Scientia Iranica
Volume 31, Issue 15
Transactions on Industrial Engineering (E)
July and August 2024
Pages 1293-1312

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History

  • Receive Date: 29 June 2021
  • Revise Date: 02 September 2021
  • Accept Date: 25 October 2021

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