Abstract
The global steel industry is undergoing a deep transformation as sustainability becomes a strategic priority. Ironmaking, historically one of the largest sources of industrial CO₂ emissions, faces increasing pressure to reduce its environmental footprint while maintaining efficiency and product quality. Achieving significant reductions requires precise control of iron ore processing, particularly when working with low-grade ores. This challenge creates opportunities for beneficiation and pelletizing plants to adopt advanced analytical technologies that enable greener operations.
This study presents three case studies demonstrating how online Pulsed Fast Thermal Neutron Activation (PFTNA) cross-belt elemental analysis (CNA) and at-line X-ray Diffraction (XRD) can be used to optimize iron ore beneficiation, sintering, pelletizing, and Direct Reduced Iron (DRI) production.
Online CNA provides continuous elemental data directly on the conveyor belt, enabling real-time ore sorting and blending. In iron ore screening processes, CNA achieves Fe precision of 0.34% and accuracy of 0.40% across the 26–50% Fe range, with comparable performance for Si, Al, Na, K, and Ti. In sinter applications, static precision for Fe is 0.48%, while CaO and SiO₂ show 0.23% and 0.18%, respectively, supporting accurate results for basicity control of the raw mix through precise real time lime dosing. These capabilities allow operators to maintain consistent feed chemistry, reduce variability, and minimize energy-intensive corrective actions. For example, reducing coke consumption by just 1 kg per ton of sinter translates into €1.4 million annual savings at typical production scales.
At-line XRD analysis provides mineralogical insights critical for impurity removal, including clays, carbonates, and silicates during ore washing. One case study demonstrates XRD effectiveness in grade monitoring of goethitic and magnetitic ores, where rapid phase identification and Rietveld refinement quantify complex gangue minerals such as clinochlore, tremolite, talc, and carbonates alongside magnetite and hematite. In one example, magnetite ore analysis revealed 51.8% magnetite, 17.9% clinochlore, and minor phases including pyrite (3.0%) and calcite (4.7%). These data support accurate mass balancing and washing strategies, reducing silica and carbonate contamination.
In iron ore pelletizing, XRD enables prediction and control of key quality parameters, such as swelling, cold crushing strength, reducibility, and tumble index, while monitoring magnetite-to-hematite conversion during induration. This fine-tuning improves pellet performance and lowers energy consumption. In DRI production, XRD combined with Partial Least Squares Regression (PLSR) predicts process parameters such as total Fe and metallization with high accuracy (R² = 0.977 for total Fe and R² = 0.995 for metallic Fe), enabling responsive control in both DRI-EAF-GAS and DRI-EAF-H₂ pathways.
The synergy of CNA and XRD fosters a data-driven approach to sustainable ironmaking. Real-time elemental monitoring reduces reliance on corrective measures, while mineralogical insights enable proactive adjustments. Together, these technologies improve resource efficiency, reduce waste, and support compliance with stringent environmental regulations, thus positioning ironmaking as a proactive contributor to global decarbonization.