A graphical user interface for PCA-based MSPC: A benchmark software for multivariate statistical process control in MATLAB

Abstract A Graphical User Interface (GUI) is developed in MATLAB as a tutorial for understanding the PCA-based MSPC strategy. The software allows users to analyze both simulated and external data sets. Simulated data are obtained from a nonlinear model of a binary distillation column implemented in Simulink. The nonlinear model has four manipulated variables, four controlled variables and three input measured disturbances, plus 41 M fractions corresponding to every column stage. The methodology for PCA-based MSPC is implemented in two phases. During Phase I, the user can simulate the distillation column under normal operating conditions at three different operating points. When the simulation is finished, the GUI obtains the corresponding PCA model automatically. In Phase II, the user can simulate several scenarios with different combinations of disturbances and failures and monitor them using Squared Prediction Error (SPE) and T 2 control charts. Contribution plots are used to diagnose the original variables responsible of such abnormal situations. The software also incorporates the possibility to analyze external multivariate process datasets.