Real‐Time Optimization Using Machine Learning Models Applied to the 4,4′‐Diphenylmethane Diisocyanate Production Process
Author:
Affiliation:
1. TU Dortmund, Process Dynamics and Operations Group Department of Biochemical and Chemical Engineering Emil-Figge-Straße 70 44227 Dortmund Germany
2. Covestro AG Process Technology Kaiser-Wilhelm-Allee 60 51373 Leverkusen Germany
Abstract
Publisher
Wiley
Subject
Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/cite.202200244
Reference23 articles.
1. S.Engell A.Ahmad J.Ehlhardt I.Wolf Patent 2022.EP22209645.5
2. Real-Time Optimization in the Chemical Processing Industry
3. Feedback control for optimal process operation
4. Data‐Driven Process Simulation Using Connected Surrogate Unit Models Exemplified on a Steam Methane Reforming Process
5. Advances in surrogate based modeling, feasibility analysis, and optimization: A review
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