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Universitat de Girona. Departament dâ€™InformÃ tica i MatemÃ tica Aplicada  
Vives Mestres, Marina
Daunis i Estadella, Josep MartÃn FernÃ¡ndez, Josep Antoni 

On standard control charts, the hypothesis of normality is usually assumed without any additionalverification. Nevertheless, in some cases this assumption is not accurate and might cause errors inprocess quality monitoring. In particular, for the control of the proportion of nonconforming units(pchart) the normality is doubtful when p is small and consequently, lower control limit less than orequal to zero are frequent. Some authors have proposed new techniques to define limits in the pchart.Others have proposed transformations to improve the detection of special causes.In Xbar charts, the mean of a critical to quality (CTQ) characteristic is monitored. When thevariable is far from normality, then parametric, or even nonparametric, control charts might be used.Recent works suggest applying transformations to make the data quasinormal. This kind of lack ofnormality 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 compositionalpoint of view. New strategies are proposed and illustrated trough a case study where a proportionhas the role of a CTQ  
http://hdl.handle.net/2072/273440  
eng  
Universitat de Girona. Departament dâ€™InformÃ tica i MatemÃ tica Aplicada  
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Could CODA Methodology be Useful in Control Chart Techniques?  
info:eurepo/semantics/conferenceObject  
Recercat 