Multivariate attribute control chart using Mahalanobis D2 statistic

Arup Ranjan Mukhopadhyay

Journal of Applied Statistics, 2008, vol. 35, issue 4, pages 421-429

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.

Keywords: Euclidean distance; Mahalanobis distance; multinomial distribution; correlation matrix; variance covariance matrix (search for similar items in EconPapers)

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