Human-in-the-loop validation of a decision-support interface for blast furnace operation

Abstract

To achieve the efficient and stable operation of a blast furnace (BF) in the steel industry while retaining the critical skills of expert human operators, we developed a novel human-machine interface (HMI) grounded in ecological interface design (EID) principles. The BF is a complex, large-scale chemical reactor to produce hot metal where internal temperatures can reach up to 2000 °C. Due to the inherent difficulty of full process automation, the EID framework was adopted to support operators’ situation awareness and keep human expertise central to decision-making. The developed ecological interface (EI) enhances manual control using a transient model, allowing operators to explore the best control action by showing the predicted future states of controlled variables resulting from their hypothetical control actions. Furthermore, the developed EI provides operators with explicit information on the mass and energy balances linking control means and ends, which is intended to support situation awareness. To facilitate comprehensive training, an operation simulator, capable of running at 300 times real-time speed, was integrated with the developed EI. Human-in-the-loop experiments with 16 subjects showed that the EI significantly reduced the number of control actions in both scenarios and reduced the HMT control error and the duration of ΔP upper-bound violations in the complex scenario, whereas no statistically significant reductions were observed in coke rate or carbon intensity.