Risk Evaluation In Supply Disturbance Under Emergencies

In recent years, all types of emergencies have brought heavy casualties and huge economic losses, aroused the enthusiastic attention of the community. Emergency management is effective to reduce the incident of the loss of emergencies. Classification discussions on the causes of the incident, the process of development is the key to improve the applicability of the contingency plans. Now, Competition between enterprises has became a competition between supply chains. Occurrence of emergencies greatly reduces the stability of the supply chain, and causes a variety of risks. Supply disturbance risk under emergency emphasis have more on that.Bases research on the emergent supply chain, emergency management, and the coordination and optimization, emergencies and supply disturbances risk as a whole from the perspective of system theory, analyzes the output factors of emergencies and the input、 state、 output factors of the risk of supply disturbances. Supply disturbance risk research focuses on the economic benefits and the losses of economic efficiency after taking emergency measures and the comparisons between them.First demonstrates the mechanism of the interaction between the risk of emergencies and supply disturbances as degree of coupling theory, and establishes the degree of coupling model, then researches the degree of coupling model node variables qualitatively and quantitatively. Through the description of the elements of the transfer and drivers of risk factors, analysis emergencies and supply disturbances risk diffusion mechanism in the chain of supply chain and mesh evolution of the supply chain, transfer Path and so on. Supply chain topology is effcct Supply disturbance risk transfer and sums up the measures of risk and key risk indicators management process. Bases on the coupling between emergencies and supply disturbances, the establishment of Bayesian networks requirements, builds disturbance of the supply chain Bayesian networks, including the node variable selection and topology learning. Determine the probability of the variable conditions of the network nodes, mainly with reference to historical data and expert opinion. By using the group tree propagation algorithm on the supply disturbances risk factor store, researches the trend analysis. More accurate expression of the quantitative calculation on the volatility of the risk factors, obtains it is weak to Simply by overtime production, but should be more attention to the potential loss of the customer number and honor the loss resulting. Finally, an automotive supply chain as an example, to instance verify the modeling method and specific research on the risk of supply disturbances.