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The parameter selection and average run length computation for EWMA control charts
Conference paper

The parameter selection and average run length computation for EWMA control charts

Sheng Shu Cheng, Fong-Jung Yu, Shih-Ting Yang and Jiang-Liang Hou
NCTA 2014 - Proceedings of the International Conference on Neural Computation Theory and Applications, pp.294-299
2014

Abstract

Determination of the control limits Exponentially weighted moving average Smoothing parameter selection Statistical Process Control
In the Statistical Process Control (SPC) field, an Exponentially Weighted Moving Average for Stationary processes (EWMAST) chart with proper control limits has been proposed to monitor the process mean of a stationary autocorrelated process. There are two issues of note when using the EWMAST charts. These are the smoothing parameter selections for the process mean shifts, and the determination of the control limits to meet the required average run length (ARL). In this paper, a guideline for selecting the smoothing parameter is discussed. These results can be used to select the optimal smoothing parameter in the EWMAST chart. Also, a numerical procedure using an integration approach is presented for the ARL computation with the specified control limits. The proposed approach is easy to implement and provides a good approximation to the average run length of EWMAST charts.

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