Knowledge Management and Data Mining for Supply Chain Risk Management

Supply chain management is increasingly challenging in today's competitive world. The greater the uncertainties in supply and demand, globalization of the market in complex international supply network relationships have led to higher exposure to risks in the supply chain. In this paper, we develop a framework of knowledge-based supply chain risk management system which includes four modules: basic database, knowledge database management, supply chain risk early warning and risk management strategies module. We analyze the basis process of knowledge-based supply chain risk management which includes four steps: knowledge collection, knowledge discovery, knowledge share and knowledge study. At last, we define three simple association rules application to supply chain risk management.