Multivariate Statistical Process Control (MSPC) is the practical application of models developed using Multivariate Data Analysis (MVDA) to real world applications. Examples include,
- Process Control Using Process Analytical Technology (PAT).
- Multiple Sensor Assessment Using Internet of Things (IOT).
- Forecasting Share Prices and Market Trends Based on Multiple Real Time Inputs.
MSPC is highly graphical in its approach and provides detailed outputs that can be used for Early Event Detection (EED) to prevent process shutdowns before they occur, where this data can be used for Root Cause Analysis.
MSPC Outputs can also be condensed into Traffic Light Signals that are based on multiple variables all meeting specific criteria simultaneously and any deviations can signal a process engineer or process scientist to investigate further using the detailed outputs of multivariate models.