An Intelligent Recommendation Framework for ERP Systems

A.L. Symeonidis, K.C. Chatzidimitriou, D. Kehagias, and P.A. Mitkas (Greece)


ERP systems, Data Mining, Multi-Agent Systems


Enterprise Resource Planning systems efficiently administer all tasks concerning real-time planning and manufacturing, material procurement and inventory monitoring, customer and supplier management. Nevertheless, the incorporation of domain knowledge and the application of adaptive decision making into such systems require extreme customization with a cost that becomes unaffordable, especially in the case of SMEs. We present an alternative approach for incorporating adaptive business intelligence into the company's backbone. We have designed and developed a highly reconfigurable, adaptive, cost efficient multi-agent framework that acts as an add-on to ERP software, employing Data Mining and Soft Computing techniques in order to provide intelligent recommendations on customer, supplier and inventory management. In this paper, we present the architectural details of the developed framework.

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