Study On Dynamic Allocation Of Manufacturing Resource In Cloud Manufacturing

In the international competition environment, more and more companies tend to lever available resources outside and fully allocate callable resources, so as to meet the demand of changeable market and to win in competition. Therefore, this dissertation mainly studies on dynamic allocation of manufacturing resource in cloud manufacturing.Firstly, analyze the dynamic allocation of manufacturing resource based on cloud manufacturing. Under the conditions of cloud manufacturing, enterprises have a mass of spare resources, and these spare resources are integrated to become the center of the cloud manufacturing services. But because the property relations of these resources are different, it may cause that the result of dynamic allocation of manufacturing resource made by cloud manufacturing service platform contradicts the owners' decisions. In order to weaken the effects of these resources' property relations on the result of dynamic allocation of manufacturing resource, it should consider the whole cloud service system's revenue as decision-making basis from the perspective of cloud manufacturing service platform. Because of the co-opetition relationship between enterprises and network externality, every enterprise will obey the centralized management of the cloud manufacturing service platform in order to ensure their own maximum profit.Then establish a model based on Pareto Optimal for the dynamic allocation of the spare resources. In this model, the rate of CSP and CSD's total manufacturing resources and ability change is determined by natural attenuation of total manufacturing resources and ability, self-propagation of total manufacturing resources and ability, the increase caused by the resource's trade in the mode of cloud manufacturing. This model maximizes the whole cloud service system's revenue by adjusting the proportion of resources provided by cloud service providers. Then using the Pontryagin's maximum principle it gets the Pareto optimal strategy of the allocation of resources under cloud manufacturing service platform.Finally, simulation analyze for the model based on Pareto Optimal for the dynamic allocation of the spare resources, and discover the management meaning. Find an example to verify the feasibility of this method, and discover the relationship between the total manufacturing resources and ability of CSP and CSD with cost coefficient and revenue conversion coefficient, which can provide practical guidance for cloud manufacturing service platform operator and the enterprises involved.