Toward Self-Organizing Production Logistics in Circular Factories: A Multi-Agent Approach

Abstract

Production logistics in circular factories is characterized by structural uncertainty due to variability in product-core quality, availability, and timing. These conditions challenge conventional deterministic and centrally planned control approaches. This paper proposes a vision for a multi-agent system based on decentralized decision-making through negotiations and event-driven communication serving as an enabler for self-organizing production logistics (SOPL) in circular factories. The envisioned system architecture integrates embodied agents, a shared semantic knowledge layer, and dynamically instantiated digital twins to support monitoring, prediction, and scenario evaluation. By shifting decision-making closer to execution and enabling agents to interpret tasks, assess capabilities, and negotiate responsibilities, the approach is expected to increase responsiveness and improve resilience to disruptions inherent in circular factories. Building on this vision, a three-phase development roadmap is introduced and characterized using the self-organizing logistics (SOL) typology, providing a structured pathway toward the realization of SOPL in circular factories.

Figures (5)

• Figure 1: Methodology linking emerging drivers, the system vision, and a three‑phase development roadmap.
• Figure 2: Recent industrial pilot deployments of humanoid robots performing production logistics tasks across global manufacturing companies.
• Figure 3: Conceptual vision of an SOPL system in the circular factory, combining heterogeneous assets, agent-based decision-making and shared knowledge. Based upon elements from klein_digital_2023li_survey_2024 and tran_multi-agent_2025.
• Figure 4: A three-phase development roadmap toward self-organizing production logistics.
• Figure 5: Phase 1 experimental setup in the IPU Lab at KTH, where heterogeneous agents collaboratively perform a single pick‑and‑delivery task.