On t and EWMA t charts for monitoring changes in the process mean

Zhang, Lingyun; Chen, Gemai; Castagliola, Philippe

doi:10.1002/qre.1012

Cited by 71 publications

(82 citation statements)

References 30 publications

(7 reference statements)

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“…These charts, intended to monitor the process mean were first proposed by Zhang et al [30], by presenting an X-bar t-chart and a EWMA t-chart. The applicability of these two charts to short production runs was described by Celano et al [9], who also studied their statistical properties.…”

Section: Spc For Short Production Runs -Literature Reviewmentioning

confidence: 99%

Selection of the Most Suitable Statistical Process Control Approach for Short Production Runs: A Decision-Model

Marques¹,

Cardeira²,

Paranhos³

et al. 2015

IJIET

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Abstract-Nowadays, customers are increasingly claiming not only for better quality products at the lowest possible cost, but also demanding customized solutions to satisfy their specific, sometimes unique, needs and wants. Due to this, manufacturing companies are seeking to adopt higher agile production models, such as mass customization strategies. In the quality control field, statistical process control (SPC) methods have been widely used to monitor process performance and detect abnormal situations in its behavior; however, traditional SPC approaches are usually not appropriate for small lot or batch sizes, for the start-up of a process, and for situations where a high variety of mixed products exist. Such situations are within the scope of the so called short production runs. Several SPC schemes have been proposed for short-run environments; all of them have their own advantages, shortcomings, and more suitable for certain production scenarios. This paper provides an up-to-date literature review on the topic, identifies classes of SPC short-run methods, and presents a decision-model that guides production managers in the choice of the most appropriate SPC short-run approach. The model was validated in a textile production company, and is being incorporated into a software package.Index Terms-Decision-model, short-run, statistical process control (SPC).

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Section: Spc For Short Production Runs -Literature Reviewmentioning

confidence: 99%

Selection of the Most Suitable Statistical Process Control Approach for Short Production Runs: A Decision-Model

Marques¹,

Cardeira²,

Paranhos³

et al. 2015

IJIET

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Section: Introductionmentioning

confidence: 99%

“…Unfortunately this is not always the case in practice [20]. Therefore Zhang et al [20] proposed the EWMA t chart to overcome this problem, by showing that the EWMA t chart is more robust than the EWMA X chart in preventing estimation errors or changes in the process standard deviation. In addition, it was shown that the EWMA t chart always has a lower size of the Type II error than the EWMA X chart for mean shifts a[0, 0.5] when the charts are optimally designed for a quick detection of moderate and large shifts (see Figure 7 in Zhang et al [20]).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore Zhang et al [20] proposed the EWMA t chart to overcome this problem, by showing that the EWMA t chart is more robust than the EWMA X chart in preventing estimation errors or changes in the process standard deviation. In addition, it was shown that the EWMA t chart always has a lower size of the Type II error than the EWMA X chart for mean shifts a[0, 0.5] when the charts are optimally designed for a quick detection of moderate and large shifts (see Figure 7 in Zhang et al [20]). However, when the two charts are optimally designed for a quick detection of small shifts, the EWMA X chart has a slightly lower size of the Type II error than the EWMA t chart, but the difference is very small -for mean shifts a[0, 0.5] (again, see Figure 7 in [20]).…”

Section: Introductionmentioning

confidence: 99%

“…The EWMA t chart proposed by Zhang et al [20] is optimally designed when based on the ARL alone. Thus this paper studies the MRL performance of the EWMA t chart, and also provides an optimal design procedure, based on the MRL and the computed optimal parameters of the chart.…”

Section: Introductionmentioning

confidence: 99%

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A STUDY OF THE MEDIAN RUN LENGTH (MRL) PERFORMANCE OF THE EWMA t CHART FOR THE MEAN

Chin

Khoo

2012

sajie

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The exponentially weighted moving average (EWMA) X chart is effective in detecting small shifts. However, the EWMA X chart is not robust enough to prevent errors in estimating the process standard deviation or a changing standard deviation. To overcome this problem, Zhang et al. suggested the EWMA t chart in 2009. The existing optimal design of the EWMA t chart is based on the average run length (ARL) criterion. This paper proposes that the optimal design of the EWMA t chart be based on the median run length (MRL). The MRL performances of the optimal EWMA X and optimal EWMA t charts are compared. OPSOMMINGDie eksponensiaalgeweegde bewegende gemiddelde (EWMA) X -kaart is geskik om klein verskuiwings te bespeur. Die EWMA X -kaart is egter nie robuust genoeg om foute in die beraming van die proses standaardafwyking of 'n veranderende standaardafwyking te voorkom nie. Om die probleem te oorkom het Zhang et al. in 2009 die EWMA t-kaart voorgestel. Die bestaande, optimale ontwerp van die EWMA t-kaart is gebaseer op die gemiddelde lopielengte kriterium. Dié artikel stel voor dat die optimale ontwerp van die EWMA t-kaart eerder op die mediaanlopielengte gebaseer word. Die resultate van die gebruik van die mediaanlopielengte met die EWMA X -en die optimale EWMA t-kaarte word vergelyk.

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Diabetes Metabolism Res

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On t and EWMA t charts for monitoring changes in the process mean

Cited by 71 publications

References 30 publications

Selection of the Most Suitable Statistical Process Control Approach for Short Production Runs: A Decision-Model

Selection of the Most Suitable Statistical Process Control Approach for Short Production Runs: A Decision-Model

A STUDY OF THE MEDIAN RUN LENGTH (MRL) PERFORMANCE OF THE EWMA t CHART FOR THE MEAN

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