An Enhanced Performance to Monitor Process Mean with Modified Exponentially Weighted Moving Average – Sign Control Chart

Abstract

The purpose of this research is to enhance performance for detecting a change in process mean by combining modified exponentially weighted moving average and sign control charts. This is nonparametric control chart which effective alternatives to the parametric control chart so called MEWMA-Sign. The nonparametric control chart can serve when process observations is deviated from normal distribution assumption. Generally, the performance of control charts are widely measured by average run length (ARL) divided into two cases; in control ARL (ARL0) and out of control ARL (ARL1). In this paper, the performance comparison is investigated when processes are non-normal distributions. The performance of the MEWMA-Sign is compared EWMA-Sign control chart by considering from a minimum value of ARL1. The numerical results found that the MEWMASign performs better than EWMA-Sign in order to detect a very small shift of mean process. Additionally, the real application of the MEWMA-Sign and EWMA-Sign are presented.

Design and Analysis of Extended Exponentially Weighted Moving Average Signed-Rank Control Charts for Monitoring the Process Mean

“…Furthermore, we compare the proposed ARL performance to the Modified Exponentially Weighted Moving Average sign control chart (MEWMA-Sign) under the Laplace distribution and ARL 0 = 370 with 5 and 10 subgroups [14]. The simulation results proved that the proposed chart is superior to the MEWMA-Sign charts in all shift dimensions.…”

“…In this experiment, we choose the smoothing parameters γ = 0.10, γ = 0.25 in the EWMA, EWMA-SN, and EWMA-SR charts, but employ γ 1 = 0.10, γ 2 = 0.03 and γ 1 = 0.25, γ 2 = 0.10 in the EEWMA, EEWMA-SN, and proposed charts with 5 and 10 subgroups in Monte Carlo simulations under ARL 0 = 370. The smoothing parameter was used in the simulation because it is commonly used and encountered in manufacturing; it can be found in [5,14,16,18,19]. The distributions employed in this study are normal (0,1), lognormal (0,1), and Laplace (1,1), with specific shifts ranging from 0 to 1.5.…”

“…The assessment revealed that the proposed chart outperforms its competitors in detecting small and medium shifts in process location. Taboran and Sukparungsee investigate the MEWMA-Sign control chart for monitoring procedure mean under abnormal distributions [14], and the findings show that the chart exceeds EWMA-Sign in detecting tiny shifts. Abbas et al designed the nonparametric progressive mean control chart based on the Wilcoxon signed-rank statistic (NPPM-SR), and the results show that it is more efficient than the nonparametric EWMA sign (NPEWMA-SN) chart or the nonparametric EWMA based on Wilcoxon signed-rank statistic (NPEWMA-SR) chart using average run length criteria [15].…”

Efficiency enhancement of the modified EWMA control method with conditional expected delay for change detection in processes

“…Haq and Woodall [8] proposed a method to calculate CED for the modified EWMA control chart. More applications of EWMA control charts can be seen in Li et al [9], Supharakonsakun and Areepong [10], and Taboran and Sukparungsee [11].…”