System and method of real-time enzymatic activity detection and dynamic formulation for pulp and paper production

A method of automatically providing real-time dosing corrections for an industrial process wherein one or more enzymatic compositions are applied to fibers for producing a pulp or paper product, the method comprising:

• for each of a plurality of pulp or paper products, developing predictive machine learning models by observing correlations over time between outcomes, associated with properties for the respective pulp or paper product, and various combinations of process inputs, comprising characteristics of a respective enzyme blend;
• for a pulp or paper product to be produced via the industrial process, using an associated model to select an initial enzyme blend to be applied, and respective dose rates for one or more components thereof, based at least in part on input data comprising one or more target properties for the pulp or paper product;
• upon application of the initial enzyme blend and respective dose rates for the one or more components thereof, providing real-time feedback data comprising measured values corresponding to enzyme activity of at least one of the one or more enzyme blend components;
• during the industrial process, dynamically adjusting the respective dose rates for at least one of the one or more components of the enzyme blend, based at least in part on the measured enzyme activity.