Batch Quality Optimization
Optimization of Chemical Processes
Today, most petrochemical manufacturing companies rely on lab results to determine product quality. This typically delays lab responses by 10 to 40 minutes because the products cannot be released until the lab results are available. Due to the inefficiency of this process, chemical manufacturers are seeking batch process improvements that allow them to release their products more quickly.
Through the use of the manufacturer’s historical data, oPRO.ai can generate machine learning models that will help chemical and oil and gas manufacturers modify the conditions as necessary for the next batch. This application of process optimization in chemical engineering enables the customer to predict the batch quality (lab results), understand the correlation among the process variables, and prescribe the optimal cycle time within the given constraints.