Research On Optimizing Surplus Manufacturing Capacity Allocation And Coordinating Operations In The Supply Chain Under The Internet Of Things

The application of Internet of Things(IOT) makes resources can be sensored in real time within and without the enterprises in a supply chain, which will make the “things to things” connection across boundary of enterprises become true. Through the IoT, the enterprise in a supply chain can show its own resources or see its partners’ resources status on the IoT platform(Cloud platform) which makes resources penetratingly visible. Meanwhile, resources that embedded IoT intelligent terminals also have the ability of possessing intelligent optimization and can communicate with human or things actively or passively. Based on the emerging of these smart terminals in the supply chain networks, the enterprises can not only connect supply and demand directly, but also can improve the efficiency of resources, which will realize the convenient achievement of resources and then change the transaction mode between enterprises in a supply chain.The new features mentioned above change the geographical and economic relationships between stakeholders in supply chain, promote the new agents(Cloud platform) that provide new relative function services emerge in supply chain and then bring several new problems in supply chain management. On the basic of previous research on supply chain cooperation and coordination, this thesis tries to uncover the internal rule that application of IoT affects the way of enterprise allocating and matching resources on the cloud platform. The content of the project includes: the strategies design for supply chain resources allocation based on Io T; the operations coordination mechanism and Pareto improvement under the cloud platform embedded supply chain.In the third chapter of the thesis, we considered the sharing strategy of manufacturing capabilities between the manufacturers in the complicated cases causing by the emergence of intelligent terminal. We can find that the unit revenue of sharing will have an impact on both manufacturers, and get the strategy to achieve the coordination of the two manufacturers. The content of the fourth chapter mainly consider the impact of the demand information which is updating in real time in the supply chain on the upper manufacturers, the study found that information sharing can help these two manufacturers optimize manufacturing capacity sharing strategy; The fifth chapter considered the two manufacturers’ sharing behaviors in the manufacturing mode of "service oriented”, we can get that the sharing of manufacturing capacity will have a different effects on these two enterprises and the recipient of the capacity is in a more advantage position; In the sixth chapter, we gave a full consideration to the dynamics of cloud platform system. By the method of differential game, we analyzed the coordination strategy between the manufacturer and the cloud platform, and got the prerequisite of coordination; Chapter seven mainly analyzed the capacity sharing strategies on the bullwhip effect, we can see the ability of unit manufacturing capability transformed into the terminal products is an important factor to influence the bullwhip effect and the profits of these two firms.