The Parameter Selection and Average Run Length Computation for EWMA Control Charts

Sheng Shu Cheng, Fong-Jung Yu, Shih-Ting Yang, Jiang-Liang Hou

2014

Abstract

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.

References

  1. Alwan, L.C., Roberts, H.V., 1998. Time series modeling for statistical process control. Journal of Business and Economic statistics, 6, 87-95.
  2. English, J.R., Krishnamurthi, M., Sastri, T., 1991, Quality Monitoring of Continuous Flow Processes. Computers and Industrial Engineering, 20, 251-260.
  3. IMSL, 1989, STAT/LIBRARY manual. IMSL, Inc: Houston.
  4. Jiang, W., Wu, H., Tsung, F., Nair V.N., Tsui K.L., 2002, PID Charts for Process Monitoring. Technometrics, 44, 205-214.
  5. Lucas, J.M., Saccucci, M.S., 1990, Exponentially weighted moving average control schemes: properties and enhancements. Technometrics, 32, 1-12.
  6. Montgomery, D.C, Mastrangelo, C.M., 1991, Some statistical process control methods for autocorrelated data. Journal of Quality Technology, 23, 179-193.
  7. Tsung, F, Apley, D.W., 2002, The dynamic T-squared chart for monitoring feedback-controlled processes. IIE Transactions, 34, 1043-1054.
  8. Wincek, M.A., 1990, Industrial strength time series: Effect of new technologies on application and practice, unpublished paper presented at the 5th annual conference on making statistics more effective in schools of business, University of Kansas, June.
  9. Zhang, N.F., 1998, A statistical control chart for stationary process data. Technometrics, 40, 24-28.
  10. Zhang, N.F., 2000, Statistical control charts for monitoring the mean of a stationary process. Journal of Statistic Computation and Simulation, 66, 249-258.
Download


Paper Citation


in Harvard Style

Cheng S., Yu F., Yang S. and Hou J. (2014). The Parameter Selection and Average Run Length Computation for EWMA Control Charts . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014) ISBN 978-989-758-054-3, pages 294-299. DOI: 10.5220/0005146902940299


in Bibtex Style

@conference{ncta14,
author={Sheng Shu Cheng and Fong-Jung Yu and Shih-Ting Yang and Jiang-Liang Hou},
title={The Parameter Selection and Average Run Length Computation for EWMA Control Charts},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)},
year={2014},
pages={294-299},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005146902940299},
isbn={978-989-758-054-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)
TI - The Parameter Selection and Average Run Length Computation for EWMA Control Charts
SN - 978-989-758-054-3
AU - Cheng S.
AU - Yu F.
AU - Yang S.
AU - Hou J.
PY - 2014
SP - 294
EP - 299
DO - 10.5220/0005146902940299