Demonstration of a Novel AI-Based Approach for Digitalization Ladle Metallurgy Facility
In 2023, a major steel manufacturer initiated a pilot project aimed at the digital transformation of a Ladle Metallurgy Facility (LMF). The project, supported by governmental and technological partnerships, focused on addressing the digitalization challenges within heavy industries, which often lag behind other manufacturing sectors. This study explores the implementation of advanced digital technologies, including machine learning-based video analytics, novel sensing technologies, Industrial Internet of Things (IIoT) integration, real-time cognitive computing, big data analytics, and digital twins. The primary objective of this initiative was to enhance process efficiency by reducing manual interventions, minimizing process variability, and improving the final metallurgical properties of the steel. This work provides valuable insights into the digitalization process, technical execution, data standardization requirements, and workforce impact in a heavy manufacturing environment. The results demonstrate the potential of these technologies to advance operational efficiency in the steelmaking industry, laying the groundwork for future technology trials.
Authors
- Esraa Hassan (ORCID: https://orcid.org/0000-0002-1021-717X)
- Amir Eaman
Institutions
- Acadia University (CA)
Publication Details
- Published
- 2024-12-05
- DOI
- https://doi.org/10.1109/icir64558.2024.10976823
- Primary Topic
- Metallurgical Processes and Thermodynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00