The multivariate control charts [Hotelling ({T}^{2}) control chart, multivariate CUSUM (MCUSUM), multivariate EWMA (MEWMA)] have been used for the control of multivariate process and have proved their adequacy to reduce the complexity of such process monitoring.
The second section will be dedicated for the most used multivariate control charts (Hotelling and MEWMA charts).
We anticipate that a similar approach also can be used routinely for screening, batch control and similar analysis settings, for instance by using a multivariate control chart and determine presence of new peaks of significant intensity.
The selected and treated OES wavelengths are then used in modified multivariate control charts (MEWMA and Hotelling) for three statistics (mean, SD and CV) and windowed polynomial regression for mean.
If the process is more sophisticated, one should control several key variables using multivariate control chart.
This multi-agent system uses: multivariate control chart for abnormal detection, neural network for faults diagnosis, Bayesian network for variables identification and expert system for reconfiguration task.
The Raman spectroscopy method was capable of collecting a full spectrum every 30 seconds, from which both ethanol and glucose concentrations could be determined within seconds using multivariate control models.
Multivariate logistic regression using the same control variables was conducted to estimate the relative likelihood of a treatment group member having an event (admission or readmission) relative to comparison members; results are presented as adjusted odds ratios and 95% confidence intervals.
We therefore propose to control the process using multivariate T2 control charts economically designed with the addition of statistical constraints, a design method called economic-statistical design.
An alternative to the decomposition approach (stratification) we have taken is to use multivariate analysis to control statistically for population composition changes over time, and to control for confounding and for effect modification (interactions amongst risk and protective factors).
