An Efficient Robust Nonparametric Triple EWMA Wilcoxon Signed-Rank Control Chart for Process Location

The adaptive exponentially weighted moving average (AEWMA) control charts are the advanced form of classical memory control charts used for efficiently monitoring small-to-large shifts in the process parameters (location and/or dispersion). These AEWMA control charts estimate the unknown shifts using exponentially weighted moving average (EWMA) or cumulative sum (CUSUM) control charts statistics. The hybrid EWMA (HEWMA) control chart is preferred over classical memory control charts to detect early shifts in process parameters. So, this study presents a new auxiliary information-based (AIB) AEWMA (IAEWMAAIB) control chart for process location that estimates the unknown location shift using HEWMA statistic. The objective is to develop an unbiased location shift estimator using HEWMA statistic and then adaptively update the smoothing constant. The shift estimation using HEWMA statistic instead of EWMA or CUSUM statistics boosts the performance of the proposed IAEWMAAIB control chart. The Monte Carlo simulation technique is used to get the numerical results. Famous performance evaluation measures like average run length, extra quadratic loss, relative average run length, and performance comparison index are used to evaluate the performance of the proposed chart with existing counterparts. The comparison reveals the superiority of the proposed control chart. Finally, two real-life applications from the glass manufacturing industry and physicochemical parameters of groundwater are considered to show the proposed control chart’s implementation procedure and dominance.

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“…[ 14 ] and Rasheed et al . [ 15 ] suggested mixed memory and nonparametric triple EWMA control charts for improved process location monitoring.…”

Section: : Introductionmentioning

confidence: 99%

“…Recently, Anwar et al [13] introduced AIB double homogeneously weighted moving average (AIB DHWMA) control chart to monitor process location. Also, Rasheed et al [14] and Rasheed et al [15] suggested mixed memory and nonparametric triple EWMA control charts for improved process location monitoring.…”

Section: : Introductionmentioning

confidence: 99%

Improved adaptive EWMA control chart for process location with applications in groundwater physicochemical parameters and glass manufacturing industry

et al. 2022

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“…Recent studies have shown that EWMA-type charts are the most useful tools for researchers. For example, Haq [8], Abbas et al [9], Ali et al [10], Tang et al [11], Haq [12], Rasheed et al [13], Rasheed et al [14], etc., are the few recent references in this regard.…”

Section: Introductionmentioning

confidence: 99%

New Hybrid EWMA Charts for Efficient Process Dispersion Monitoring with Application in Automobile Industry

Liu¹,

Khan²,

Rasheed³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

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The EWMA charts are the well-known memory-type charts used for monitoring the small-to-intermediate shifts in the process parameters (location and/or dispersion). The hybrid EWMA (HEWMA) charts are enhanced version of the EWMA charts, which effectively monitor the process parameters. This paper aims to develop two new uppersided HEWMA charts for monitoring shifts in process variance, i.e., HEWMA1 and HEWMA2 charts. The design structures of the proposed HEWMA1 and HEWMA2 charts are based on the concept of integrating the features of two EWMA charts. The HEWMA1 and HEWMA2 charts plotting statistics are developed using one EWMA statistic as input for the other EWMA statistic. A Monte Carlo simulations method is used as a computational technique to determine the numerical results for the performance characteristics, such as average run length (ARL), median run length, and standard deviation run length (SDRL) for assessing the performance of the proposed HEWMA1 and HEWMA2 charts. In addition, to evaluate the overall performance of the proposed HEWMA1 and HEWMA2 charts, other numerical measures consisting of the extra quadratic loss (EQL), relative average run length (RARL), and performance comparison index (PCI) are also computed. The proposed HEWMA1 and HEWMA2 charts are compared to some existing charts, such as CH, CEWMA, HEWMA, AEWMA HHW1, HHW2, AIB-EWMA-I, and AIB-EWMA-II charts, on the basis aforementioned numerical measures. The comparison reveals that the proposed HEWMA1 and HEWMA2 charts achieve better detection ability against the existing charts. In the end, a real-life data application is also provided to enhance the implementation of the proposed HEWMA1 and HEWMA2 charts practically.

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“…Later, Alevizakos et al [9] presented one and twosided TEWMA control chart, observing the time between k ≥ 1 events using the gamma distribution. After that, Rasheed et al [10] and Rasheed et al [11] presented two control charts for efficiently monitoring the process mean.…”

Section: Introductionmentioning

confidence: 99%

A Distribution-Free THWMA Control Chart under Ranked Set Sampling

Zhang

Rasheed

Khan

et al. 2022

Mathematical Problems in Engineering

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The basic assumption of the parametric control charts is that the underlying process follows the specific distribution. The appropriateness of parametric control charts is questionable when different industrial applications do not support this desired assumption. Recently, nonparametric control charts have been introduced to overcome this deficiency of parametric control charts. Nonparametric control charts have the same in-control run-length characteristics for all continuous distributions and are in-control robust. On the other hand, the ranked set sampling technique is preferred over the simple random sampling technique with control charts because it reduces variability and improves the control chart’s performance. So, this study aims to propose a nonparametric triple homogenously weighted moving average control chart under Wilcoxon signed-rank test with a ranked set sampling technique (regarded as NPTHWMA RSS ) to further enhance the process location monitoring. Monte Carlo simulations are used for computational purposes. The proposed control chart’s run-length performance is compared with competing control charts, like TEWMA-SR, TEWMA- X ¯ , TEWMA-SN, TEWMA- SR RSS , and NPDHWMA RSS control charts. The comparison revealed that the proposed NPTHWMA RSS control chart outperformed the other competing control charts, particularly for small to moderate shifts in process location. Finally, a real-life application is presented for quality practitioners to illustrate the effectiveness of the proposed control chart.

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An Efficient Robust Nonparametric Triple EWMA Wilcoxon Signed-Rank Control Chart for Process Location

Cited by 14 publications

References 36 publications

Improved adaptive EWMA control chart for process location with applications in groundwater physicochemical parameters and glass manufacturing industry

Improved adaptive EWMA control chart for process location with applications in groundwater physicochemical parameters and glass manufacturing industry

New Hybrid EWMA Charts for Efficient Process Dispersion Monitoring with Application in Automobile Industry

A Distribution-Free THWMA Control Chart under Ranked Set Sampling

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