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Multivariate attribute control chart using Mahalanobis D2 statistic

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  • Arup Ranjan Mukhopadhyay

Abstract

Process control involves repeated hypothesis testing based on several samples. However, process control is not exactly hypothesis testing as such since it deals with detection of non-random patterns of variation as well in a fleeting kind of population. Compare this with hypothesis testing which is principally meant for a stagnant population. Dr Walter A. Shewhart introduced a graphic method for doing this testing in a fleeting population in 1924. This graphic method came to be known as control chart and is widely used throughout the world today for process management purposes. Subsequently there was much advancement in process control techniques. In particular, when more than one variable was involved, process control techniques were developed mainly by Hicks (1955), Jackson (1956 and 1959) and Montgomery and Wadsworth (1972) based on the pioneering work of Hotelling in 1931. Most of them have worked in the area of multivariate variable control chart with the underlying distribution as multivariate normal. When more than one attribute variables are involved some works relating to test of hypothesis was done by Mahalanobis (1946). These works were also based on the Hotelling T2 test. This paper expands the concept of 'Mahalanobis Distance' in case of a multinomial distribution and thereby proposes a multivariate attribute control chart.

Suggested Citation

  • Arup Ranjan Mukhopadhyay, 2008. "Multivariate attribute control chart using Mahalanobis D2 statistic," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(4), pages 421-429.
    • Handle: RePEc:taf:japsta:v:35:y:2008:i:4:p:421-429
    DOI: 10.1080/02664760701834980
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    Cited by:

    1. Wilson Rojas-Preciado & Mauricio Rojas-Campuzano & Purificación Galindo-Villardón & Omar Ruiz-Barzola, 2023. "Control Chart T2Qv for Statistical Control of Multivariate Processes with Qualitative Variables," Mathematics, MDPI, vol. 11(12), pages 1-32, June.

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