AISep 3, 2021

Will bots take over the supply chain? Revisiting Agent-based supply chain automation

arXiv:2109.01703v157 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the lagging industrial uptake of agent-based systems in supply chain management by identifying convergence effects and research challenges, though it is incremental as it builds on existing concepts.

The paper revisits agent-based supply chain automation, finding that technological advancements like IoT and digital ledgers have matured the concept, making it applicable to a wider range of functions and enabling new possibilities for automation and autonomy.

Agent-based systems have the capability to fuse information from many distributed sources and create better plans faster. This feature makes agent-based systems naturally suitable to address the challenges in Supply Chain Management (SCM). Although agent-based supply chains systems have been proposed since early 2000; industrial uptake of them has been lagging. The reasons quoted include the immaturity of the technology, a lack of interoperability with supply chain information systems, and a lack of trust in Artificial Intelligence (AI). In this paper, we revisit the agent-based supply chain and review the state of the art. We find that agent-based technology has matured, and other supporting technologies that are penetrating supply chains; are filling in gaps, leaving the concept applicable to a wider range of functions. For example, the ubiquity of IoT technology helps agents "sense" the state of affairs in a supply chain and opens up new possibilities for automation. Digital ledgers help securely transfer data between third parties, making agent-based information sharing possible, without the need to integrate Enterprise Resource Planning (ERP) systems. Learning functionality in agents enables agents to move beyond automation and towards autonomy. We note this convergence effect through conceptualising an agent-based supply chain framework, reviewing its components, and highlighting research challenges that need to be addressed in moving forward.

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