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Optimal Design of a EWMA Chart to Monitor the Normal Process Mean

  • Lee, Jae-Heon (Department of Applied Statistics, Chung-Ang University)
  • Received : 2012.03.02
  • Accepted : 2012.06.05
  • Published : 2012.06.30

Abstract

EWMA(exponentially weighted moving average) charts and CUSUM(cumulative sum) charts are very effective to detect small shifts in the process mean. These charts have some control-chart parameters that allow the charts and be tuned and be more sensitive to certain shifts. The EWMA chart requires users to specify the value of a smoothing parameter, which can also be designed for the size of the mean shift. However, the size of the mean shift that occurs in applications is usually unknown and EWMA charts can perform poorly when the actual size of the mean shift is significantly different from the assumed size. In this paper, we propose the design procedure to find the optimal smoothing parameter of the EWMA chart when the size of the mean shift is unknown.

Keywords

References

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