The expected outcomes of this research include: (1) the development of an energy optimization system for machine tools that integrates data analytics with natural language understanding to enhance human-AI collaboration; (2) accurate identification of complex energy consumption patterns and intelligent intervention suggestions enabled by large language models, fostering intelligent green transformation in manufacturing; and (3) generation of quantifiable empirical data evaluating the actual impact of AI on energy savings and emission reductions—such as reductions in energy use, carbon output, and variations in production efficiency. Additionally, this project will offer a new paradigm for applying OpenAI models in industrial optimization, expanding their societal relevance in sustainable manufacturing.
Research
Innovative data-driven solutions for efficient CNC machine operations.
Energy Optimization
Utilizing data to enhance CNC machine energy efficiency and performance.
Data Collection
We gather historical operational data from CNC machines for analysis.
Model Training
Developing predictive models for energy consumption and operational efficiency.