Industrial System

Industrial system research focuses on improving efficiency, safety, and predictive capabilities through advanced data analysis and automation. Current efforts concentrate on developing AI-driven solutions for predictive maintenance, leveraging techniques like deep learning (including autoencoders and VAEs), large language models for automated asset management, and physics-informed neural networks for system modeling in heterogeneous environments. These advancements aim to optimize industrial processes, reduce downtime, and enhance overall system reliability, impacting both scientific understanding of complex systems and practical applications across various sectors.