Purpose: This project is based on the concepts of sustainability and circular economy, and aims to develop a green supplier assessment system, sustainable production system, and closed-loop supply chain through deep learning, enhancing it into a green supply chain that covers the entire product lifecycle.

Economic Aspect: This project utilizes deep learning to optimize precise forecasting and meet carbon reduction targets. The results of the project can help enterprises increase market share and comply with emissions reduction requirements, possessing global competitive business value.

Social Aspect: The outcomes of this sub-project have practical applicability; the results can serve as a basis for future planning of production systems in enterprises and promote the integration of a circular and sustainable industrial chain.

Impact on Academic Development: The deep learning methods proposed in this sub-project cover the supply chain and combine natural language processing, circular production system optimization, and value forecasting. They can provide the foundation for integrating circular economy with artificial intelligence, and lay the groundwork for subsequent research developments in this field.