HAlMan process: Machine Learning (ML) Modelling of Process Units

Machine Learning (ML) and Artificial Intelligence (AI) are being applied to key metallurgical process units within the HAlMan project to improve process understanding, support operational decision-making, increase efficiency, and identify optimized operating conditions. The work combines experimental data, thermodynamic modelling, advanced machine learning techniques, and multi-objective optimization to address both pyrometallurgical and hydrometallurgical processes.

A central objective is to move beyond conventional process analysis and develop predictive tools capable of identifying relationships between operating conditions, material characteristics, process performance, and energy requirements. The resulting models can support researchers and industrial operators in evaluating different production scenarios and selecting operating conditions according to priorities such as throughput, energy consumption, and operating cost.