Predictive Statistical Process Control
Predictive statistical process control of a batch process, such as for a batch-based fermentation process like that used for brewing and distilling. Real-time data monitoring combined with a prediction engine allows operators to make adjustments to batch productions as deviations occur.
The model creates predictions based on past behavior and process parameters of previous batches. Real-time visibility and prediction enables immediate action, either manually or automatically, directly at the point of deviation.
Benefits for the company
Real-time process monitoring using data analytics can help ensure that a process stays on track and allows to make early adjustments to correct any deviations that would affect the final product taste or quality.
Feasability
High
Type of expertise/ AI domain
Statistical process control uses a framework known as model predictive control (MPC) based on multivariate projection models created using two data analytics methods: Partial Least Squares (PLS) and Principal Component Analysis (PCA).