OptiFlex

OptiFlex

Algorithm-based optimization of separation processes using the example of paper recycling

The paper industry is in a state of transformation as sustainability goals are increasingly taken into account by customers and resources such as recovered paper, water, and energy become more expensive. Today's plants, whose design has been fixed at the time of construction and can be changed merely in the wake of reconstruction, are able to meet the changing requirements only at the expense of inefficiency. The collaborative project aims to investigate the potential of efficiency improvement at different levels by studying recycling plants in which the individual separation processes can be flexibly interconnected. For these plants, modern decision-making methods based on machine learning algorithms are to be developed, which are capable of suggesting promising circuit configurations for complex setups and multi-criteria optimization objectives. In this way, it should be possible to meet sustainability criteria and customer requirements in the future, whether for paper with reduced CO2-footprint, lower water consumption, or optimized process yield, in a cost-efficient manner.

Project duration October 2022 – September 2023
Project partner Chair of Paper Technology and Mechanical Process Engineering
Project Funding Funding Initiative Interdisciplinary Research at TU Darmstadt
Project staff Constantin Wildt