GIBEOM KIM, WOONG-HEE HAN
Steel skull formation on the refractory walls of steelmaking equipment significantly impacts process efficiency and product quality. This study investigates the causal relationship between steel skull formation and process variables in the RH (Ruhrstahl Heraeus) refining process. Using a compact vision camera for internal imaging of an RH vessel, the research employs a deep learning-based object detection technique to quantitatively assess the cross-sectional area of steel skull present. To address the complexities of the RH process, the combined Generalized Propensity Score and Generalized Additive Model methodologies are utilized. Findings reveal that steel skull formation is influenced by factors such as ferro-alloy input and RH arrival temperature, with variations dependent on deoxidation methods and operational conditions. The results aim to provide insights for process optimization strategies that can minimize steel skull formation and enhance the quality of molten steel produced, addressing a critical challenge in the steelmaking industry.
@article{0dbc88ad-f2e2-478b-92d3-2ba95854af75,
title={2025 Gibeom Kim Semi quantitative Analysis of Steel Skull Formation and Causal Relationship with RH Processing Variables through Propensity Score Matching s11663},
author={GIBEOM KIM and WOONG-HEE HAN},
year={2026},
language={en}
}TY - JOUR TI - 2025 Gibeom Kim Semi quantitative Analysis of Steel Skull Formation and Causal Relationship with RH Processing Variables through Propensity Score Matching s11663 AU - GIBEOM KIM AU - WOONG-HEE HAN PY - 2026 LA - en ER -
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