doi: 10.17706/ijapm.2016.6.4.200-206
Numerical Integration Method of Average Run Length for SARMA(P,Q)L Process Base on CUSUM Procedure
Suvimol Phanyaem
- Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology
Abstract
Statistical process control (SPC) is widely used to monitor and improve quality in industrial processes. Cumulative sum (CUSUM) chart is an effective tool in statistical process control for detecting change in a process mean. The main purpose of this paper is to present the numerical integration of Average Run Length (ARL) of CUSUM chart when observations are seasonal autoregressive and moving average of order (P,Q)L denoted by SARMA(P,Q)L process with exponential white noise. In addition, we compare the ARL between Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) charts. The results show that the EWMA chart is superior to the CUSUM control chart in the case of process has small shifts in mean.
Keywords
- Seasonal autoregressive and moving average order (P
- Q)L
- process
- cumulative sum (CUSUM)
- average run length (ARL)
How to Cite
Suvimol Phanyaem, "Numerical Integration Method of Average Run Length for SARMA(P,Q)L Process Base on CUSUM Procedure," International Journal of Applied Physics and Mathematics, vol. 6, no. 4, pp. 200-206, 2016. https://doi.org/ 10.17706/ijapm.2016.6.4.200-206
Copyright & License
Copyright © 2016 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).