Newswise — In the field of supply chain management (SCM), traceability is vital for ensuring operational efficiency, product quality, and stakeholder trust. However, existing solutions face significant limitations: traditional systems lack multi-tier coverage and real-time dynamics, struggle to integrate emerging technologies like blockchain and multi-agent systems (MAS) practically, overlook human-centric adoption factors, and have gaps in data privacy and security. Additionally, complex supply chains (e.g., gasoline manufacturing and distribution) suffer from issues like data inaccuracies, integration challenges, and single points of failure, making comprehensive traceability difficult to achieve.
Therefore, a research team from the Department of Computer Science at Berhampur University conducted a study titled “Constructing an intelligent agent-centric framework for supply chain traceability with blockchain integration”.
This study proposes an intelligent agent-centric framework integrating blockchain technology (BCT) to address these gaps. The framework adopts a multi-agent system (MAS) with distinct roles: a Primary Agent (P-Agent) overseeing the entire supply chain, and phase-specific agents (S-Agent for supply, M-Agent for manufacturing, D-Agent for distribution, R-Agent for retail). It uses smart contracts (e.g., PSC, SOMSC) to automate processes and ensure immutability, and employs pseudocodes (e.g., PAgtTraceability, PAgtTraceThresholdCal) to track operational states (success marked by Trc_Index_Bit_val=1, failure by -1) and calculate traceability thresholds. The framework was validated in a gasoline manufacturing and distribution supply chain (GMDSC) case study, using AgentPy for agent simulation, Remix Solidity IDE for smart contracts, and Web3.py for blockchain-agent integration.
Results show the framework effectively enhances traceability: it achieves end-to-end tracking (from crude oil procurement to retail), reduces human intervention, and improves real-time responsiveness. In GMDSC, it resolved issues like data inaccuracies and integration challenges, with BCT ensuring immutable records and MAS enabling decentralized coordination. The framework demonstrates rationality (clear agent roles, sequential workflows), sustainability (error alerts, real-time monitoring), and robustness (resilience to node failures, decentralized control).
The paper “Constructing an intelligent agent-centric framework for supply chain traceability with blockchain integration” is authored by Satyananda SWAIN and Manas Ranjan PATRA. The full text is available at Front. Eng. Manag. 2025, 12(3): 558–580.
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