HEWMA Control Chart Using Auxiliary Information

Noor‐ul‐Amin, Muhammad; Khan, Sana; Sanaullah, Aamir

doi:10.1007/s40995-018-0585-x

Cited by 29 publications

(17 citation statements)

References 31 publications

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“…Further, it is observed that the multiple measurement method is a remedy against the adverse effect of measurement error. It is recommended to extend the study of measurement error on the control charts that are using the auxiliary variable at the estimation stage such as Riaz [21], Lee et al [22], and Noor-ul-Amin et al [23].…”

Section: Conclusion and Recommendationmentioning

confidence: 99%

Impact of Measurement Error on Mixed EWMA-CUSUM Control Chart

Noor‐ul‐Amin

2020

Scientia Iranica

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In statistical process control, measurement error plays an important role which is usually ignored. Measurement error can lead to incorrect conclusions about the performance of the process. In this paper, we examined the effect of measurement error on the shift detection ability of the mixed exponentially weighted moving average-cumulative sum (EWMA-CUSUM) control chart. We investigated the performance of mixed EWMA-CUSUM chart in case of mean shift by using (i) covariate method (ii) multiple measurement method (iii) linearly increasing variance method. The performance measurement tools such as average run length (ARL) and standard deviation of run length (SDRL) are estimated by using the Monte-Carlo simulation method. It is concluded that the performance of the mixed EWMA-CUSUM control chart is adversely effected by considering the measurement error. It is revealed from the comparative study that the mixed EWMA-CUSUM control chart is performing better than the EWMA and CUSUM control charts in the presence of measurement error. An illustrative example is presented to demonstrate the performance of control charts in case of measurement error.

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Section: Conclusion and Recommendationmentioning

confidence: 99%

Impact of Measurement Error on Mixed EWMA-CUSUM Control Chart

Noor‐ul‐Amin

2020

Scientia Iranica

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“…These charts provide a methodology for utilization of information more than once which causes increased efficiency of the concerned chart. Various authors studied the efficiency of hybrid charts as compared with nonhybrid control charts, like Azam et al., 1 Haq, 2,3 Aslam et al., 4,5 and Noor‐ul‐Amin et al 6 . They proved that hybrid charts are more sensitive as compared to other memory type control charts.…”

Section: Introductionmentioning

confidence: 99%

Maximum hybrid exponentially weighted moving average control chart in the presence of measurement error by using auxiliary information

Javaid¹,

Noor‐ul‐Amin

Hanif

2021

Quality & Reliability Eng

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Hybrid control charts have become part of statistical process control (SPC) but still, need more emphasis. Researchers are developing charts for joint monitoring of process mean and variance shifts just like Max‐EWMA and their hybrid version using auxiliary information but are ignoring the effect of measurement error on the efficiency of charts. We propose maximum hybrid exponentially weighted moving average with measurement error using auxiliary information and name it Max‐HEWMAMEAI control chart. The efficiency of this chart is proved through calculations of average run lengths (ARLs) and standard deviations of run lengths (SDRLs) using the Monte Carlo simulations method whereas, ARLs and SDRLs are shown in tabular form. The effect of measurement error on the efficiency of the chart has been analyzed and the impact of multiple measurements to reduce the error effect has been studied using the covariate model. Real‐life application is also part of this article to support the simulation results.

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“…Some recent developments are given in Refs. 1, 16‐21, and 22 to make sure the quick detection as far as other production circumstances are concerned.…”

Section: Introductionmentioning

confidence: 99%

Two successive occasions resubmitted sampling scheme‐based control chart

Arshad

Azam

Aslam

2020

Quality & Reliability Eng

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In this paper, a resubmitted sampling‐based successive sampling over two successive occasions control chart is proposed to monitor the underlying characteristic of interest. Auxiliary information of the first occasion is utilized to monitor the relative change in the study variable over the second occasion successively despite high degree of correlation. The structural and operational design is presented along with the comparative performance evaluation. The average run length is used as a performance evaluation measure and proved the argument in favor of the presented concept in comparison with the other auxiliary data control charts. The implementation is explained through two real examples.

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HEWMA Control Chart Using Auxiliary Information

Cited by 29 publications

References 31 publications

Impact of Measurement Error on Mixed EWMA-CUSUM Control Chart

Impact of Measurement Error on Mixed EWMA-CUSUM Control Chart

Maximum hybrid exponentially weighted moving average control chart in the presence of measurement error by using auxiliary information

Two successive occasions resubmitted sampling scheme‐based control chart

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