A control chart for COM-Poisson distribution using a modified EWMA statistic

Aslam, Muhammad; Saghir, Aamir; Ahmad, Liaquat; Hussain, Jaffer

doi:10.1080/00949655.2017.1373114

Cited by 27 publications

(12 citation statements)

References 36 publications

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“…Many authors 26,[29][30][31][32] proposed several control charts for COM-Poisson data to detect shifts in the location parameter assuming that the dispersion parameter was fixed. Saghir and Lin 28 proposed three kinds of CUSUM charts for COM-Poisson data to detect shifts in the location parameter (fixed ), in the dispersion parameter (fixed ) and in both of them.…”

Section: The Design Of Cmp-dewma Chartmentioning

confidence: 99%

“…Aslam et al applied the multiple dependent sampling (MDS) and the repetitive sampling schemes, respectively, in an EWMA chart for the COM‐Poisson distribution. Aslam et al proposed a control chart for the COM‐Poisson distribution based on the modified EWMA scheme. Aslam et al proposed a hybrid EWMA control chart for data following the COM‐Poisson distribution.…”

Section: Introductionmentioning

confidence: 99%

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A double exponentially weighted moving average control chart for monitoring COM‐Poisson attributes

Alevizakos

Koukouvinos

2019

Quality & Reliability Eng

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The Conway‐Maxwell‐Poisson (COM‐Poisson) distribution is a two‐parameter generalization of the Poisson distribution, which can be used for overdispersed or underdispersed count data and also contains the geometric and Bernoulli distributions as special cases. This article presents a double exponentially weighted moving average control chart with steady‐state control limits to monitor COM‐Poisson attributes (regarded as CMP‐DEWMA chart). The performance of the proposed control chart has been evaluated in terms of the average, the median, and the standard deviation of the run‐length distribution. The CMP‐DEWMA control chart is studied not only to detect shifts in each parameter individually but also in both parameters simultaneously. The design parameters of the proposed chart are provided, and through a simulation study, it is shown that the CMP‐DEWMA chart is more effective than the EWMA chart at detecting downward shifts of the process mean. Finally, a real data set is presented to demonstrate the application of the proposed chart.

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Section: The Design Of Cmp-dewma Chartmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A double exponentially weighted moving average control chart for monitoring COM‐Poisson attributes

Alevizakos

Koukouvinos

2019

Quality & Reliability Eng

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“…Reference [11] proposed the control chart based on COM-Poisson distribution using the resampling approach. Reference [12] designed modified EWMA chart based on the COM-Poisson distribution. More details on such control charts can be seen in [13,14].…”

Section: Complexitymentioning

confidence: 99%

Design of a Control Chart Based on COM‐Poisson Distribution for the Uncertainty Environment

Aslam

AL-Marshadi

2019

Complexity

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This paper will introduce the neutrosophic COM-Poisson (NCOM-Poisson) distribution. Then, the design of the attribute control chart using the NCOM-Poisson distribution is given. The structure of the control chart under the neutrosophic statistical interval method will be given. The algorithm to determine the average run length under neutrosophic statistical interval system will be given. The performance of the proposed control chart is compared with the chart based on classical statistics in terms of neutrosophic average run length (NARL). A simulation study and a real example are also added. From the comparison of the proposed control chart with the existing chart, it is concluded that the proposed control chart is more efficient in detecting a shift in the process. Therefore, the proposed control chart will be helpful in minimizing the defective product. In addition, the proposed control chart is more adequate and effective to apply in uncertainty environment.

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“…The EWMA charts are extensively used and have many applications in the field of process monitoring. Various contributions are made to the literature by many authors, for example [8,9,10,11,12,13,14,15,16,17,18].…”

Section: : Introductionmentioning

confidence: 99%

“…The Modified-EWMA chart detects a quick shift in the process as compared to the classical EWMA chart when an extra parameter is introduced in the model [45]. Aslam et al [17] used Modified-EWMA for the COM-Poisson distribution. Anwar et al [46] proposed a Modified-mxEWMA chart for the process location in the presence of auxiliary information.…”

Section: : Introductionmentioning

confidence: 99%

An improved Bayesian Modified-EWMA location chart and its applications in mechanical and sport industry

Aslam

Anwar

2020

PLoS ONE

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Control charts are popular tools in the statistical process control toolkit and the exponentially weighted moving average (EWMA) chart is one of its essential component for efficient process monitoring. In the present study, a new Bayesian Modified-EWMA chart is proposed for the monitoring of the location parameter in a process. Four various loss functions and a conjugate prior distribution are used in this study. The average run length is used as a performance evaluation tool for the proposed chart and its counterparts. The results advocate that the proposed chart performs very well for the monitoring of small to moderate shifts in the process and beats the existing counterparts. The significance of the proposed scheme has proved through two real-life examples: (1) For the monitoring of the reaming process which is used in the mechanical industry. (2) For the monitoring of golf ball performance in the sports industry.

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A control chart for COM-Poisson distribution using a modified EWMA statistic

Cited by 27 publications

References 36 publications

A double exponentially weighted moving average control chart for monitoring COM‐Poisson attributes

A double exponentially weighted moving average control chart for monitoring COM‐Poisson attributes

Design of a Control Chart Based on COM‐Poisson Distribution for the Uncertainty Environment

An improved Bayesian Modified-EWMA location chart and its applications in mechanical and sport industry

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