Adaptive EWMA-S2 control charts with adaptive smoothing parameter

Descripción del Articulo

Memory charts like EWMA-S2 or CUSUM-S2 are designed to detect a particular change in the process variance efficiently. However, the charts could be inefficient to detect some other shifts. To overcome this constraint, control charts with adaptive schemes that are efficient for a wide range of shifts...

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Detalles Bibliográficos
Autores: Ugaz W., Alonso A.M., Sánchez I.
Formato: artículo
Fecha de Publicación:2020
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/2639
Enlace del recurso:https://hdl.handle.net/20.500.12390/2639
https://doi.org/10.1080/08982112.2020.1776326
Nivel de acceso:acceso abierto
Materia:statistical process control
Adaptive control charts
average run length
CUSUM
EWMA
http://purl.org/pe-repo/ocde/ford#1.01.01
Descripción
Sumario:Memory charts like EWMA-S2 or CUSUM-S2 are designed to detect a particular change in the process variance efficiently. However, the charts could be inefficient to detect some other shifts. To overcome this constraint, control charts with adaptive schemes that are efficient for a wide range of shifts can be used. This work proposes new adaptive EWMA charts for the dispersion (AEWMA-S2) based on an adaptive smoothing parameter that relates its value to the potential shift of the process. A Markov chain approach is used to optimize its design. A simulation experiment shows the advantage of the proposed charts. © 2020 Taylor & Francis Group, LLC.
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