Monitoring of location and dispersion parameters of production processes using hybrid control charts

Czabak-Górska, Izabela D.; Frączek, Daniel; Kucińska-Landwójtowicz, Aneta; Lorenc, M.; Rząsa, Mariusz; Czabak, Mariusz

doi:10.1016/j.cie.2021.107707

Cited by 3 publications

(3 citation statements)

References 27 publications

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“…In the current study, charts are proposed based on a simple moving average, while the usage of the weighted moving average may be a future addition to this study. Moreover, proposing hybrid control chart proposed by [12] under MSS schemes and considering the mixed MA-DMA or mixed DMA-MA location charts under MSS will be interesting future research works.…”

Section: Some Concluding Remarksmentioning

confidence: 99%

“…To monitor the location parameter, Karagöz [21] proposed a robust control chart for the monitoring of skewed and contaminated processes. Czabak-Górska et al [12] proposed a hybrid control chart for location and dispersion monitoring based on the classic and robust estimators. Mehmood et al [26] performed a comparative analysis between FAR and ARL based control charts using run rules.…”

Section: Introductionmentioning

confidence: 99%

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On moving average based location charts under modified successive sampling

Mahmood,

Hyder,

Raza

et al. 2024

Hacettepe Journal of Mathematics and Statistics

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Ceramics are made up of water, clay, and powders. These are categorized as non-metallic and inorganic materials. It is revealed in the literature that Longquan celadon glaze had irregular cracks in glaze layers due to the relatively high content of N a2O. Therefore, it is necessary to monitor the influence of N a2O in the ceramic process. Control charts are a possible tool to monitor the changes in the ceramic process. For single event issues, simple random sampling strategy is utilized; however, modified successive sampling is preferred as the favored sampling strategy at regular intervals of time when the quality of any product is evaluated. Hence, this paper is designed to propose moving average ({MA}_{MSS(S)}) and double moving average ({DMA}_{MSS(S)}) based control charts to detect small to moderate location shifts using the modified successive sampling technique. We have highlighted the performance evaluations of designed control charts with respect to run-length metrics, and their comparison has been made with the existing ShewhartMSS(S) control chart. The results revealed that the ({DMA}_{MSS(S)}) performs more efficiently as compared to the ShewhartMSS(S) and ({MA}_{MSS(S)}) control charts. Further, to demonstrate the application of the designed charts, a dataset of the chemical composition of the ceramic is also utilized.

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Section: Some Concluding Remarksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On moving average based location charts under modified successive sampling

Mahmood,

Hyder,

Raza

et al. 2024

Hacettepe Journal of Mathematics and Statistics

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“…A control chart is one of the statistical tools that can be used to measure the stability of a product process in a controlled state [4]. Control charts are a basic tool commonly used to monitor changes in the production process [5].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Control Chart X ̅ Based on Median Absolute Deviation With S

Mayashari,

Herdiani,

Anisa

2024

BAREKENG: J. Math. & App.

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A stable and controlled process will produce products of good quality following predetermined specifications. A control chart is one of the statistical tools that can be used to measure the stability of a product process in a controlled state. Control charts commonly used to evaluate the statistical control process are Shewhart control charts ( and ). The control chart is used to control the process, as seen from the average and variability of the process. If the data used is not normally distributed or there are outliers, then an alternative control chart, namely the Median Absolute Deviation (MAD), can be used. MAD is used to monitor the process mean and process standard deviation because it has properties that are robust or resistant to deviations. This research aims to form a control chart based on MAD, apply it to data on fat content in animal feed products, and compare control charts based on with the control chart based on control chart based on MAD. The limitations in this study are the quality characteristics used consist of only one variable and the data is not normally distributed, only limited to the mean process, and the data used in this study are observation data on the fat content contained in animal feed products at PT Japfa Comfeed Indonesia Tbk Makassar Unit from December 2021 to January 2022. The results of this study show that the control chart based on MAD detects more out-of-control points than the control based on . The performance of the control chart based on MAD is better at detecting changes in the process than the control chart based on because it has a relatively smaller ARL value.

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