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Multivariate multinomial T2 control chart using fuzzy approach

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  • María Nela Pastuizaca Fernández
  • Andrés Carrión García
  • Omar Ruiz Barzola

Abstract

Quality of a product is often measured through various quality characteristics generally correlated. Multivariate control charts are a response to the need for quality control in such situations. If quality characteristics are qualitative, it sometimes happens that the product quality is defined by linguistic variables – where quality levels are represented by some specific words – and product units are classified into several linguistic forms categories, depending on the degree of fulfilment of expectations, creating a situation of fuzzy classifications. This study first reviews the concepts found in the literature on the development of fuzzy multivariate control charts. We propose a method to control these fuzzy quality evaluations, with correlated multiple attributes quality characteristics, through the use of a Hotelling T2 control chart.

Suggested Citation

  • María Nela Pastuizaca Fernández & Andrés Carrión García & Omar Ruiz Barzola, 2015. "Multivariate multinomial T2 control chart using fuzzy approach," International Journal of Production Research, Taylor & Francis Journals, vol. 53(7), pages 2225-2238, April.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:7:p:2225-2238
    DOI: 10.1080/00207543.2014.983617
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    Cited by:

    1. Pamela Chiñas-Sanchez & Ismael Lopez-Juarez & Jose Antonio Vazquez-Lopez & Jose Luis Navarro-Gonzalez & Aidee Hernandez-Lopez, 2021. "Out-of-Control Multivariate Patterns Recognition Using D 2 and SVM: A Study Case for GMAW," Mathematics, MDPI, vol. 9(5), pages 1-14, February.

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