A new multi-agent system framework for tacit knowledge management in manufacturing supply chains |
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| Authors: | Khalid Al-Mutawah Vincent Lee Yen Cheung |
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| Affiliation: | (1) Stanford University, Stanford, CA, USA;(2) University of Michigan, Ann Arbor, MI, USA;(3) University of Chicago, Chicago, IL, USA;(4) University of Vermont, Burlington, VT, USA;(5) Harvard University, Cambridge, MA, USA;(6) University of Pennsylvania, Philadelphia, PA, USA;(7) MIT, Cambridge, MA, USA |
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| Abstract: | 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. |
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