A moving average S control chart for monitoring process variability

ABSTRACT

An efficient alternative to the S control chart for detecting shifts of small magnitude in the process variability using a moving average based on the sample standard deviation s statistic is proposed. Control limit factors are derived for the chart for different values of sample size and span w. The performance of the moving average S chart is compared to the S chart in terms of average run length. The result shows that the performance of moving average S chart for varying values of w outweigh those of the S chart for small and moderate shifts in process variability.

KEYWORDS:

• control charts
• moving average S control chart
• process variability
• average run length (ARL)
• S chart

About the authors

Olatunde A. Adeoti obtained his B.Sc (Hons) degree (first-class honors) in Mathematics from the University of Ilorin, M.Sc (Statistics) from the University of Lagos and his Ph.D. in Statistics from the University of Ilorin, Ilorin, Nigeria. He is a member of the American Statistical Association and the Nigerian Statistical Association. His research interests include statistical process control, statistical quality control and management in healthcare, and artificial neural network in statistical process control. He is currently a Senior Lecturer at the Department of Mathematics and Statistics, Bowen University, Nigeria.

J. O. Olaomi obtained his B.Sc. (Hons) degree in Statistics and Postgraduate Diploma in Computer Science from the Obafemi Awolowo University, Ile-Ife, Nigeria. He obtained his M.Sc. and Ph.D. (Statistics) from the University of Ibadan, Nigeria. He belongs to many professional societies, including the South Africa Statistical Association (SASA). His research interests include Endogeneity (Econometrics), Time Series Econometrics, Statistical Computing/Consulting, and Operations Research and Sampling. He is currently an Associate Professor of Statistics at the University of South Africa.

Acknowledgments

The authors would like to thank Professor W. H. Woodall for careful proofreading, helpful comments, and suggestions on earlier versions of this article. We are equally grateful to the referee(s) for their useful comments that improved the quality of this article.