Ferrous Scrap

Ferrous scrap recycling is crucial for environmental and economic sustainability in steel production, but efficient and reliable sorting and classification remain significant challenges. Current research focuses on automating these processes using advanced machine learning techniques, including deep learning models like Vision Transformers and YOLOv4, and reinforcement learning algorithms such as TD3, SAC, and PPO, to optimize sorting robots and improve classification accuracy. These advancements aim to increase throughput, reduce energy consumption, and enhance the safety and reliability of scrap metal handling, ultimately improving the efficiency and sustainability of the steel industry.