Design and Implementation of the Extended Exponentially Weighted Moving Average Control Charts

Tai, Shih-Hung; Lin, Ching-I; Chen, Yan-Haw

doi:10.1109/icmss.2009.5302801

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…Tai et al 81 proposed a composite Shewhart‐GWMA (

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S^{2}

) scheme using separate charting statistics at each sampling point and they showed that it is more effective in quickly detecting OOC observations compared to the corresponding composite Shewhart‐EWMA (

\overset{X}{true}

S^{2}

) scheme.…”

Section: Shewhart‐gwma Schemesmentioning

confidence: 99%

Generally weighted moving average monitoring schemes: Overview and perspectives

Mabude

Malela‐Majika

Castagliola

et al. 2020

Quality & Reliability Eng

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An overview of monitoring schemes from a class called generally weighted moving average (GWMA) is provided. A GWMA scheme is an extended version of the exponentially weighted moving average (EWMA) scheme with an additional adjustment parameter that introduces more flexibility in the GWMA model as it adjusts the kurtosis of the weighting function so that the GWMA scheme can be designed such that it has an advantage over the corresponding EWMA scheme in the detection of certain shift values efficiently. The parametric and distribution‐free GWMA schemes to monitor various quality characteristics and its existing enhanced versions (ie, double GWMA, composite Shewhart‐GWMA, mixed GWMA‐CUSUM, and mixed CUSUM‐GWMA) have better performance than their corresponding EWMA counterparts in many situations; hence, all such existing research works discussing GWMA‐related schemes (ie, 66 publications in total) are documented and categorized in such a manner that it is easy to identify research gaps. Finally, a number of possible future research ideas are provided.

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“…Tai et al 81 proposed a composite Shewhart‐GWMA (

\overset{X}{true}

S^{2}

\overset{X}{true}

S^{2}

) scheme.…”

Section: Shewhart‐gwma Schemesmentioning

confidence: 99%

Generally weighted moving average monitoring schemes: Overview and perspectives

Mabude

Malela‐Majika

Castagliola

et al. 2020

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…They showed that the -GWMA scheme performs better than the -EWMA scheme in monitoring small shifts in the process mean. Thereafter, a number of researchers investigated the performance of parametric GWMA schemes, to count a few, Sheu and Yang (2006), Sheu and Hsieh (2009), Tai and Lin (2009), Teh et al (2012), Aslam et al (2017), Chakraborty et al (2017), etc. SPM schemes have been applied to a variety of fields, including engineering, production, manufacturing, finance, food industry, chemistry and biochemistry, see Simoglou et al (1997), Black et al (2011), Bag et al (2012), Lim et al (2017), etc.…”

Section: Introductionmentioning

confidence: 99%

A new distribution-free generally weighted moving average monitoring scheme for detecting unknown shifts in the process location

Mabude¹,

Malela‐Majika²,

Shongwe³

2020

10.5267/j.ijiec

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Distribution-free (or nonparametric) monitoring schemes are needed in industrial, chemical and biochemical processes or any other analytical non-industrial process when the assumption of normality fails to hold. The Mann-Whitney (MW) test is one of the most powerful tests used in the design of these types of monitoring schemes. This test is equivalent to the Wilcoxon ranksum (WRS) test. In this paper, we propose a new distribution-free generally weighted moving average (GWMA) monitoring scheme based on the WRS statistic. The performance of the proposed scheme is investigated using the average run-length, the standard deviation of the runlength, percentile of the run-length and some characteristics of the quality loss function through extensive simulation. The proposed scheme is compared with the existing parametric and nonparametric GWMA monitoring schemes and other well-known control schemes. The effect of the estimated design parameters as well as the effect of the Phase I sample size on the Phase II performance of the new monitoring scheme are also investigated. The results show that the proposed scheme presents better and attractive mean shifts detection properties, and therefore outperforms the existing monitoring schemes in many situations. Moreover, it requires a reasonable number of Phase I observations to guarantee stability and accuracy in the Phase II performance.

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“…To remedy this problem, Sheu and Lin 8 also introduced the composite Shewhart‐GWMA scheme (denoted as CSG scheme) to efficiently monitor small and large shifts in the mean of a normally distributed process. To jointly monitor the mean and variability of a normally distributed process, Tai et al 27 proposed a CSG scheme with separate mean and variance charting statistics. Next, for Poisson distributed attributes data, Lin 28 investigated the performance of the CSG scheme in monitoring the number of nonconformities in an inspection unit.…”

Section: Introductionmentioning

confidence: 99%

Distribution‐free composite Shewhart‐GWMA Mann‐Whitney charts for monitoring the process location

Mabude

Malela‐Majika

Aslam

et al. 2020

Quality & Reliability Eng

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The Mann‐Whitney (MW) statistic is one of the most recommended two‐sample statistical tests when the assumption of normality fails to hold due to its robustness and fascinating properties especially when small sample sizes are involved. In order to improve the sensitivity of the generally weighted moving average (GWMA) monitoring scheme toward the detection of large shifts, in this paper, a new distribution‐free phase II composite Shewhart‐GWMA (CSG) scheme is proposed using the MW U statistic. The performance of the proposed scheme is investigated using the average run‐length (ARL) and average extra quadratic loss (AEQL) values through extensive simulations. The performance of this newly proposed monitoring scheme is found to be superior when compared to numerous memory‐type MW schemes (some existing and others introduced in this paper) in many situations. An illustrative example is given to demonstrate the implementation of the CSG MW U scheme using real‐life data.

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Design and Implementation of the Extended Exponentially Weighted Moving Average Control Charts

Cited by 4 publications

References 13 publications

Generally weighted moving average monitoring schemes: Overview and perspectives

Generally weighted moving average monitoring schemes: Overview and perspectives

A new distribution-free generally weighted moving average monitoring scheme for detecting unknown shifts in the process location

Distribution‐free composite Shewhart‐GWMA Mann‐Whitney charts for monitoring the process location

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