This project focuses on developing a large-scale foundation model tailored for smart manufacturing environments. By integrating multimodal industrial data—including process logs, sensor data, and textual production knowledge—the research aims to construct an AI-driven framework that supports adaptive decision-making, predictive maintenance, and intelligent process optimization. The project combines expertise in industrial engineering, artificial intelligence, and data science to build a robust foundation model that generalizes across various manufacturing domains. It also explores collaborative human–AI interaction for sustainable and efficient industrial operations.