Circular production systems require consideration of varying material properties, alternative process routes, and environmental and economic targets. The main reason for this is the fluctuating quality and quantity of secondary material as well as dynamic production goals. A data-driven control system links production and recycling data, evaluates relevant metrics, and enables targeted adjustments of process parameter values and process routes. This modular and transferable approach supports increased resource efficiency as well as reductions in energy consumption, environmental impacts, processing time, and costs.
Aleksandra Naumann
Machine Learning Circular Economy Decision Support Cyber-physical production systems B