Korakoch Silpakob¹, Yupaporn Areepong^1,*, Saowanit Sukparungsee¹, Rapin Sunthornwat²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 281-298, 2023, DOI:10.32604/iasc.2023.032487

Abstract Control charts are one of the tools in statistical process control widely used for monitoring, measuring, controlling, improving the quality, and detecting problems in processes in various fields. The average run length (ARL) can be used to determine the efficacy of a control chart. In this study, we develop a new modified exponentially weighted moving average (EWMA) control chart and derive explicit formulas for both one and the two-sided ARLs for a p-order autoregressive (AR(p)) process with exponential white noise on the new modified EWMA control chart. The accuracy of the explicit formulas was compared to that of the well-known… More >

Kotchaporn Karoon, Yupaporn Areepong^*, Saowanit Sukparungsee

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 743-759, 2022, DOI:10.32604/iasc.2022.023322

Abstract Extended Exponentially Weighted Moving Average (Extended EWMA or EEWMA) control chart is one of the control charts which can quickly detect a small shift. The average run length (ARL) measures the performance of control chart. Due to the derivation of the explicit formulas for ARL on the EEWMA control chart for the autoregressive AR(p) process has not previously been reported. The aim of the article is to derive explicit formulas of ARL using a Fredholm integral equation of the second kind on EEWMA control chart for Autoregressive process, as AR(2) and AR(3) processes with exponential white noise. The accuracy of… More >