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A retrospective view of statistical quality control research and identification of emerging trends: a bibliometric analysis

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  • Pedro Veiga

  • Luis Mendes

  • Luis Lourenço

Abstract

This study aims to identify the fundamental contributions on applications of statistical methods in the area of quality and process control, determining lines of research and statistical methods forming the dominant intellectual structure, evolution over time and identifying future tendencies and relationships between the most relevant themes. A quantitative approach linked to bibliometric analysis was used, based on research made in the Thomson/Reuters-ISI online database. Among the main results, it stands out that the importance of statistical applications applied to process and quality control continues to grow. The contributions with greatest impact are related to principal component analysis and multivariate analysis as well as in the area of clinical assessment. Besides multivariate analysis, the dominant techniques are control charts, use of data-mining tools and autocorrelation/time series. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • Pedro Veiga & Luis Mendes & Luis Lourenço, 2016. "A retrospective view of statistical quality control research and identification of emerging trends: a bibliometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 673-692, March.
    • Handle: RePEc:spr:qualqt:v:50:y:2016:i:2:p:673-692
    DOI: 10.1007/s11135-015-0170-8
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    References listed on IDEAS

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    1. Bersimis, Sotiris & Psarakis, Stelios & Panaretos, John, 2006. "Multivariate Statistical Process Control Charts: An Overview," MPRA Paper 6399, University Library of Munich, Germany.
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    4. Donald McTavish & Ellen Pirro, 1990. "Contextual content analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 24(3), pages 245-265, August.
    5. Wu, Chien-Wei & Pearn, W.L. & Kotz, Samuel, 2009. "An overview of theory and practice on process capability indices for quality assurance," International Journal of Production Economics, Elsevier, vol. 117(2), pages 338-359, February.
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