A new multi-agent system framework for tacit knowledge management in manufacturing supply chains

Participating members in a manufacturing supply chain (MSC) usually make use of individual knowledge for making independent decisions. Recent research, however, indicates that there is a need to handle such distributed knowledge in an integrated manner, especially under uncertain and fast changing environments. A multiagent system (MAS), a branch of distributed artificial intelligence, is a contemporary modelling technique for a distributed system like MSCs in the manufacturing domain. However recent researches indicate that MAS approaches have not adequately addressed the role of sharing tacit knowledge (TK) on MSC performance. This paper, therefore, aims to propose a framework that utilizes MAS techniques with a corresponding TK sharing mechanism dedicated to MSCs. We performed some experiments to simulate the proposed approach. The results showed significant improvements when comparing the proposed approach with another conventional MAS model. The results establish a starting point for researchers interested in enhancing MSC performance using TK management approach, and for managers of MSC to focus on the essentials of sharing TK.