Prof. Bing Ji Yan is a leading researcher in metallurgical process intelligence, specializing in intelligent ironmaking, optimization of blast furnace raw materials and fuel resources, and multi-scale numerical simulation of complex ironmaking processes. His work integrates metallurgical engineering fundamentals with advanced computational modeling, data-driven analytics, and deep-learning-based industrial perception technologies to enhance the efficiency, stability, and sustainability of blast furnace operations. He has developed intelligent control systems, visual diagnostic tools, and decision-support platforms that significantly improve air volume regulation, burden distribution prediction, hearth erosion modeling, and operational state perception in large-scale furnaces. His research also advances the comprehensive utilization of solid waste resources, particularly in transforming metallurgical by-products such as titanium-bearing blast furnace slag into high-value glass-ceramic materials through innovative crystallization control and stress-mechanism analysis. Prof. Yan has led and contributed to major scientific and industrial projects related to data-driven ironmaking optimization, model development for resource procurement and batching strategies, and intelligent smelting operation guidance for enhanced energy efficiency. He has published influential work in internationally recognized journals in ironmaking, materials science, and process simulation, and holds multiple national invention patents and software copyrights in areas including slag processing systems, softening-melting detection devices, and intelligent furnace perception technologies. His contributions extend to industrial collaborations that translate research into real-world furnace optimization solutions, supporting advances in efficient, low-carbon, and intelligent metallurgical production.
Profile: Scopus
Featured Publication
Jianfeng, W., Yici, W., Guo, H., & Yan, B. (2024). Blast furnace hearth erosion modelling based on the dataset approach. Ironmaking & Steelmaking.
Mu, Y., Wu, Z., Yan, B., Liang, H., He, H., & Guo, H. (2024). Development and application of closed-loop-oriented intelligent control system for blast furnace air volume addition or reduction. Ironmaking & Steelmaking.
Dang, Z., Yan, B., Wang, D., Guo, H., Zhao, W., & Li, H. (2024). One-step preparation of cast stone from TBFS: Dual effects of TiO₂ content on glass network and precipitation behavior. Journal of Non-Crystalline Solids, 629.
Wang, D., Yan, B., Dang, Z., Li, P., Guo, H., & Song, Z. (2024). Analysis and mechanism study of residual stress during the spontaneous crystallisation process of molten titanium-containing blast furnace slag. Crystals.
He, Q., Liang, H., Yan, B., & Guo, H. (2024). Angle diagnosis of blast furnace chute through deep learning of temporal images. IEEE Transactions on Instrumentation and Measurement, 73.