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Could CODA Methodology be Useful in Control Chart Techniques?

On standard control charts, the hypothesis of normality is usually assumed without any additional verification. Nevertheless, in some cases this assumption is not accurate and might cause errors in process quality monitoring. In particular, for the control of the proportion of nonconforming units (p-chart) the normality is doubtful when p is small and consequently, lower control limit less than or equal to zero are frequent. Some authors have proposed new techniques to define limits in the p-chart. Others have proposed transformations to improve the detection of special causes. In X-bar charts, the mean of a critical to quality (CTQ) characteristic is monitored. When the variable is far from normality, then parametric, or even nonparametric, control charts might be used. Recent works suggest applying transformations to make the data quasi-normal. This kind of lack of normality is usually present when in those analyses CTQ is a part of a composition. Our proposal is to highlight how above mentioned problems can be treated from a compositional point of view. New strategies are proposed and illustrated trough a case study where a proportion has the role of a CTQ

Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada

Other contributions: Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada
Author: Vives Mestres, Marina
Daunis i Estadella, Josep
Martín Fernández, Josep Antoni
Date: 2011 May 11
Abstract: On standard control charts, the hypothesis of normality is usually assumed without any additional verification. Nevertheless, in some cases this assumption is not accurate and might cause errors in process quality monitoring. In particular, for the control of the proportion of nonconforming units (p-chart) the normality is doubtful when p is small and consequently, lower control limit less than or equal to zero are frequent. Some authors have proposed new techniques to define limits in the p-chart. Others have proposed transformations to improve the detection of special causes. In X-bar charts, the mean of a critical to quality (CTQ) characteristic is monitored. When the variable is far from normality, then parametric, or even nonparametric, control charts might be used. Recent works suggest applying transformations to make the data quasi-normal. This kind of lack of normality is usually present when in those analyses CTQ is a part of a composition. Our proposal is to highlight how above mentioned problems can be treated from a compositional point of view. New strategies are proposed and illustrated trough a case study where a proportion has the role of a CTQ
Format: application/pdf
Document access: http://hdl.handle.net/10256/13605
Language: eng
Publisher: Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada
Collection: CoDaWork 2011. The 4th International Workshop on Compositional Data Analysis
Rights: Tots els drets reservats
Subject: Anàlisi multivariable -- Congressos
Multivariate analysis -- Congresses
Estadística matemàtica -- Congressos
Mathematical statistics -- Congresses
Anàlisi d’error (Matemàtica) -- Congressos
Error analysis (Mathematics) -- Congresses
Title: Could CODA Methodology be Useful in Control Chart Techniques?
Type: info:eu-repo/semantics/conferenceObject
Repository: DUGiDocs

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