The Modeling And Application Of Knowledge Flows Based On Petri Nets

With the development of information technology, the knowledge flow has played an important role in business management. The information and knowledge’s transfer efficiency affects the normal development of enterprises and supply chain. In order to take advantage of the transfer efficiency, it needs to analyse the knowledge flow in the enterprises and supply chain formally and establish the theoretical framework so that the knowledge flow in the real world can be abstracted. It can realize the knowledge flow systematic and digital in a formal way, then the knowledge flow will play a great role in enterprises and supply chain.There are many methods used for the modeling of knowledge flows. Petri net is a better choice because of the strict mathematical definitions and analysis methodology. If the knowledge flow system becomes more complex, the Petri nets will be too huge and can not detailedly describe various of enterprise knowledge flow. The colored Petri nets (CPN) model overcomes the shortcoming of the traditional Petri nets model. So, we select the colored Petri nets. Various factors during the process of knowledge flow can cause different time delay in the supply chain knowledge flow model. This paper selects the stochastic color Petri net (SCPN) as the modeling tool. This is more in line with the reality.Based on the analysis of knowledge flow, this paper analyses the enterprise knowledge flow model and supply chain knowledge flow model. And it detailedly describes the enterprise interior. After that, the enterprise knowledge flow model based on CPN for Xerox and the supply chain knowledge flow based on SCPN are established respectively.Finally, we will simulate the enterprise knowledge flow model based on CPN by the CPN Tool, and analyse the proportion of explicit and implicit knowledge in the knowledge flow. At the same time, the method of Markov chain is used to analyze the system performance of SCPN for supply chain knowledge flow. We can analyse the konwledge flow’s average execution time, the efficiency of knowledge sharing and efficiency of knowledge assimilation.