An adaptive chart for monitoring the process mean and variance
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Data
2007-11-01
Autores
Costa, Antonio F. B.
De Magalhaes, Maysa S.
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Editor
Wiley-Blackwell
Resumo
Traditionally, an (X) over bar chart is used to control the process mean and an R chart is used to control the process variance. However, these charts are not sensitive to small changes in the process parameters. The adaptive ($) over bar and R charts might be considered if the aim is to detect small disturbances. Due to the statistical character of the joint (X) over bar and R charts with fixed or adaptive parameters, they are not reliable in identifing the nature of the disturbance, whether it is one that shifts the process mean, increases the process variance, or leads to a combination of both effects. In practice, the speed with which the control charts detect process changes may be more important than their ability in identifying the nature of the change. Under these circumstances, it seems to be advantageous to consider a single chart, based on only one statistic, to simultaneously monitor the process mean and variance. In this paper, we propose the adaptive non-central chi-square statistic chart. This new chart is more effective than the adaptive (X) over bar and R charts in detecting disturbances that shift the process mean, increase the process variance, or lead to a combination of both effects. Copyright (c) 2006 John Wiley & Sons, Ltd.
Descrição
Palavras-chave
Shewhart charts, AATS, adaptive charts, non-central chi-square distribution, single charts to, control the process mean and variance, joint (X)over-bar and R charts
Como citar
Quality and Reliability Engineering International. Chichester: John Wiley & Sons Ltd, v. 23, n. 7, p. 821-831, 2007.