System identification of scrap metal shredders under minimal process and feedstock information
M. Vasileiadis, T. Papageorgiou K. Syrmakezis, A. Kokossis
Computer Aided Chemical Engineering Volume 52,pp 3447-3452, 2023
Scrap metal shredder; mathematical optimization; model identification; energy efficiency
Shredders are essential processes in the metal scrap industry. Their efficiency is critical to sustainable recycling as shredders account for the largest energy consumers and the most expensive units to operate in the plant. While such processes are based on relatively simple principles and in operation for a long time, their feedstock (scrap) is difficult to characterize and relate to standard control schemes; operation is carried out empirically with an apparent scope for energy savings once the system is better understood. The paper presents a mathematical modelling approach, specifically aiming at the identification of a conventional shredder with minimum information about its input and output flows. A set of hypotheses, together with a mathematical optimization approach, are combined to estimate energy consumption and the breakdown of feedstock into the major metals involved. The model can be exploited to minimize energy and to connect with available model-based control technology in applications that are not addressed in this paper.