EWMA and DEWMA repetitive control charts under non-normal processes

Nawaz, Muhammad Shujaat; Azam, Muhammad; Aslam, Muhammad

doi:10.1080/02664763.2019.1709809

Cited by 18 publications

(5 citation statements)

References 28 publications

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“…Reference [36] proposed a control chart using RGS when observations are unclear and indeterminate by using the neutrosophic statistics. Later on, [37] designed an EWMA and DEWMA control chart for the non-normal process using RGS.…”

Section: Introductionmentioning

confidence: 99%

A Nonparametric Repetitive Sampling DEWMA Control Chart Based on Linear Prediction

et al. 2020

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Distribution-free control charts can be useful in statistical process control (SPC) when only limited or no information about the distribution of the data of the process is available. In this paper, a linear prediction related double exponentially weighted moving average (DEWMA) sign control chart using a repetitive sampling scheme (RSNPDEBLP) has been considered for a binomially distributed process variable to improve the efficiency of detecting small drifts in its place of small changes. The proposed RSNPDEBLP control chart is assessed in average run length (ARL) for the various values of sample sizes. The efficiency of the proposed RSNPDEBLP control chart is compared with the existing EWMA and DEWMA sign control charts using single sampling and repetitive sampling schemes in terms of ARLs. When there are small changes in the process after the stabilization period, the proposed control chart is used to control small trends rather than small shifts.

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Section: Introductionmentioning

confidence: 99%

A Nonparametric Repetitive Sampling DEWMA Control Chart Based on Linear Prediction

et al. 2020

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“…An extension of the usual EWMA control charts has been proposed by Shamma and Shamma 33 (see also, Shamma et al 34 ), where the exponential smoothing is performed twice on the initial observations 𝑀 𝑖 . This chart is known as DEWMA chart and has been studied by several authors, see, for example, Mahmoud and Woodall, 35 Teh et al, 36 Raza et al, 37 Nawaz et al, 38 and references therein.…”

Section: The Ewma Dewma and Tewma Sign Charts For Dispersionmentioning

confidence: 99%

Deciles‐based EWMA‐type sign charts for process dispersion

Godase

Rakitzis

Mahadik

et al. 2022

Quality & Reliability Eng

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In this paper, we propose and study nonparametric exponentially weighted moving average (EWMA) control charts based on the sign statistic, which are suitable for detecting changes in process dispersion. The sign statistic is defined by using appropriate deciles of the in‐control process distribution. The statistical performances of the proposed charts are determined through Monte Carlo simulation. Practical guidelines are provided for the statistical designs of these charts. We evaluate the statistical performances of the proposed charts by comparing them with that of the deciles‐based CUSUM sign chart and the EWMA lnS2 chart. The comparisons show that the proposed charts are viable nonparametric methods for monitoring the process dispersion. Finally, we provide an illustrative example to demonstrate the implementation of the proposed charts in practice.

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“…The simulation study shows that the HEWMACV control chart has the ability to detect a shift in the manufacturing process. Muhammad [10] provides a repetitive sampling technique to create control charts utilizing EWMA and double exponentially weighted moving averages (DEWMA) control charts to detect process shifts based on a non-normal distribution. Later, Phanyaem [11] discussed the efficiency of this sampling technique with EWMA-sign and GWMA-sign control charts for monitoring the mean change in the process.…”

Section: Introductionmentioning

confidence: 99%

A New Hybrid Exponentially Weighted Moving Average Control Chart with Repetitive Sampling for Monitoring the Coefficient of Variation

Petcharat

Areepong

2023

Symmetry

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The implementation of Statistical Quality Control (SQC) has been tracked in various areas, such as agriculture, environment, industry, and health services. The employment of SQC methodologies is frequently employed for monitoring and identification of process irregularities across various fields. This research proposes and implements a novel SQC methodology in agricultural areas. A control chart is one of the SQC tools that facilitates real-time monitoring of multiple activities, including agricultural yield, industrial yield, and hospital outcomes. Advanced control charts with symmetrical data are being subjected to the new SQC method, which is suitable for this purpose. This research aims to develop a novel hybrid exponentially weighted moving average control chart for detecting the coefficient of variation (CV) using a repetitive sampling method called the HEWMARS-CV control chart. It is an effective tool for monitoring the mean and variance of a process simultaneously. The HEWMARS-CV control chart used the repetitive sampling scheme to generate two pairs of control limits to enhance the performance of the control chart. The proposed control chart is compared with the classical HEWMA and Shewhart control charts regarding the average run length (ARL) when the data has a normal distribution. The Monte Carlo simulation method is utilized to approximate the ARL values of the proposed control charts to determine their performance. The proposed control chart detects small shifts in CV values more effectively than the existing control chart. An illustrative application related to monitor the wheat yield at Rothamsted Experimental Station in Great Britain is also incorporated to demonstrate the efficiency of the proposed control chart. The efficiency of the proposed HEWMARS-CV control chart on the real data shows that the proposed control chart can detect a shift in the CV of the process, and it is superior to the existing control chart in terms of the average run length.

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EWMA and DEWMA repetitive control charts under non-normal processes

Cited by 18 publications

References 28 publications

A Nonparametric Repetitive Sampling DEWMA Control Chart Based on Linear Prediction

A Nonparametric Repetitive Sampling DEWMA Control Chart Based on Linear Prediction

Deciles‐based EWMA‐type sign charts for process dispersion

A New Hybrid Exponentially Weighted Moving Average Control Chart with Repetitive Sampling for Monitoring the Coefficient of Variation

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