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Polymer Molar Flow Rate Prediction using Machine Learning

This case study focuses on measurements of Melt Flow Rate (MFR) to determine the polymer viscosity based on reactor conditions. An accurate model is desirable so that the infrequent lab samples (every 2-8 hours) are supplemented with a virtual and continuous "soft sensor". A model that runs in real-time simulation alongside the physical reactor is called a digital twin.

Objective: Develop a prediction of the reactor MFR from the polymer reactor data set.

Inspiration: https://apmonitor.com/pds/index.php/Main/PolymerMeltFlowRate