A modified control chart for monitoring non-normal characteristics

John, Boby; Subhani, S.M.

doi:10.1504/ijpqm.2020.105990

Cited by 7 publications

(5 citation statements)

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“…The first step in the analyse phase is to verify whether the problem is due to the presence of assignable causes or not. This can be done by plotting the CTQ values in an appropriate control chart [36,37]. Since the dry content is an autocorrelated characteristic, the dry content values are plotted on an exponentially weighted moving average (EWMA) control chart [38].…”

Section: Analyse Phasementioning

confidence: 99%

Minimizing the Dry Content Variation in the Pulp Drying Process Using Six Sigma Methodology

John

Chowdhury

2021

Oper. Res. Forum

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Section: Analyse Phasementioning

confidence: 99%

Minimizing the Dry Content Variation in the Pulp Drying Process Using Six Sigma Methodology

John

Chowdhury

2021

Oper. Res. Forum

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“…The control chart has three horizontal lines, namely the center line (CL), upper control limit (UCL), and lower control limit (LCL) [8] [9]. The average value of the process quality characteristics is around the CL if there are no unusual sources of variability.…”

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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“…¿cómo construir evidencias que apoyan el mejoramiento de la calidad en práctica. De esta misma manera, [14] los autores ratifican esta metodología para la mejora de sistemas productivos, en la que el objetivo es reducir la variabilidad, lo que conlleva a una gran reducción de defectos en la entrega de un producto o servicio al cliente. Basándose en este concepto, se argumenta que el uso sistemático de metodologías mejora los procesos y permite mejorar la capacidad de procesos de forma significativa, al utilizar los conceptos de rendimiento Y, nivel de calidad sigma Z y los defectos en partes por millón DPMO.…”

Section: Introductionunclassified

Evaluación con curvas de operación de métricas Seis Sigma el desempeño de sistemas productivos mixtos

Fontalvo Herrera,

Mejia Zambrano,

Oyuela Rodríguez

2024

Investigación e Innovación en Ingenierías

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Objetivo: En esta investigación se proponen nuevas curvas de operación de las métricas seis sigma para evaluar el desempeño de un sistema productivo mixto (Serie y en paralelo). Marco teórico: Para lo anterior se utiliza como marco teórico los conceptos de curva de operación, control estadístico de la producción, métricas seis sigma y sistemas de producción mixto. Metodología: se aborda un enfoque heurístico y un análisis de sensibilidad para analizar el comportamiento de los defectos en parte por millón, rendimiento Y, para lo cual se proponen las curvas de operación al variar en rango de 0 a 6 el nivel sigma Z del sistema y de los procesos. Resultados: se muestran que el sistema productivo evidencia como máxima capacidad de desempeño de calidad en términos de sigma los valores de Z 5,25, 5,43 y 5,08 respectivamente para los procesos 1, 5, 6. Conclusión: Se aporta un método innovador que permite monitorear el desempeño de la calidad en condiciones cambiantes, y analizar como incide estos cambios en la reducción de defectos de cualquier sistema productivo

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A modified control chart for monitoring non-normal characteristics

Cited by 7 publications

References 0 publications

Minimizing the Dry Content Variation in the Pulp Drying Process Using Six Sigma Methodology

Minimizing the Dry Content Variation in the Pulp Drying Process Using Six Sigma Methodology

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

Evaluación con curvas de operación de métricas Seis Sigma el desempeño de sistemas productivos mixtos

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