Steel Manufacturing

Steel manufacturing research currently emphasizes optimizing production processes and enhancing quality control through advanced data analysis and machine learning. Key areas of focus include predicting material properties and surface textures using various machine learning models, from simpler linear regressions to deep learning architectures like ROCKET, and employing reinforcement learning to improve process control and efficiency. These advancements aim to improve the efficiency, sustainability, and product quality of steel manufacturing, impacting both industrial practices and the development of new algorithms and data analysis techniques.