Multidimensional scaling used in multivariate statistical process control

This paper considers the use of multidimensional scaling techniques in multi-variate statistical process control. Principal components analysis, multiple principal components analysis, partial least squares and PARAFAC models have already been established as useful methods for such, but it should be possible to widen the portfolio of techniques to include others that come under the multidimensional scaling class. Some of these are briefly described – namely classical scaling, non-metric scaling, biplots, Procrustes analysis – and are then used on some gas transportation data provided by Transco.