Comparative study of process capability indices variables distributed with no normal

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This paper evaluates the performance of process capability indices, PCI in non-normal situations percentiles using the methods of Clements (CCP CCpk) and Burr (BCP BCpk). Although the PCI is used in industry, there is insuffi cient literature to determine their accuracy by taking into account modera...

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Detalles Bibliográficos
Autores: Valdiviezo, Martha, Fermín, José
Formato: artículo
Fecha de Publicación:2010
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Lenguaje:español
OAI Identifier:oai:ojs.csi.unmsm:article/6187
Enlace del recurso:https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/6187
Nivel de acceso:acceso abierto
Materia:Process Capability Indices. Burr and Generalized pareto distributions
Burr & Clements percentiles.
Índices de capacidad de procesos no normales
distribuciones Burr y Pareto generalizada
percentiles de Clements y Burr
Descripción
Sumario:This paper evaluates the performance of process capability indices, PCI in non-normal situations percentiles using the methods of Clements (CCP CCpk) and Burr (BCP BCpk). Although the PCI is used in industry, there is insuffi cient literature to determine their accuracy by taking into account moderate and severe deviations of the normality. To study these deviations, it performs a comparison of both methods considering simulated data distributions with the Weibull, Lognormal, Beta and Generalized Pareto, GP. In calculating the PCI the CCpk generates smaller deviations with the Weibull distribution, whereas that the BCpk, deviations are higher. On the other side with each distribution the BCP generates lower average deviation from the CCP. Finally a real case considering the distribution GP.
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