Embodied intelligence-driven adaptive collaboration in supply chains: A four-dimensional synergy framework and...

Area of Science:

• Supply Chain Management
• Artificial Intelligence
• Cognitive Systems

Background:

• Current AI research in supply chains prioritizes data-driven optimization.
• This overlooks the physical and digital integration of supply chains, causing a disconnect in AI and physical collaboration.

Purpose of the Study:

• Introduce embodied intelligence into supply chain management.
• Propose an adaptive collaboration framework integrating embodied perception, reasoning, and execution.
• Bridge the digital-physical divide in intelligent supply chain systems.

Main Methods:

• Deconstruct core issues in supply chain embodied intelligence, such as fragmented perception and delayed feedback.
• Develop a four-layer architecture based on embodied cognition and complex adaptive systems theory.
• Clarify the mechanisms of embodied perception, contextual reasoning, physical execution, and closed-loop feedback.

Main Results:

• Identified fragmented perception and delayed feedback as key challenges in current supply chain AI.
• Constructed a novel four-layer architecture for embodied supply chain intelligence.
• Outlined future research and practical applications for embodied AI in supply chains.

Conclusions:

• Embodied intelligence offers a new paradigm for supply chain management, moving beyond traditional data-driven approaches.
• The proposed framework enhances integration between digital AI and physical supply chain operations.
• This research advances supply chain management towards embodied adaptive systems for next-generation intelligence.