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Interpreting The Out-Of-Control Signals Of Multivariate Control Charts Employing Neural Networks
2010
Zenodo
Multivariate quality control charts show some advantages to monitor several variables in comparison with the simultaneous use of univariate charts, nevertheless, there are some disadvantages. The main problem is how to interpret the out-ofcontrol signal of a multivariate chart. For example, in the case of control charts designed to monitor the mean vector, the chart signals showing that it must be accepted that there is a shift in the vector, but no indication is given about the variables that
doi:10.5281/zenodo.1071567
fatcat:yjz5b5bk7vgo3ddbblfzgwwi7y