Operation Mechanism Management of Parts Supply Chain Driven by Big Data

The current manufacturing parts suppliers have achieved global procurement. The risk of the manufacturing parts supply chain will then cause immeasurable losses to the production enterprise. Therefore it is particularly important to accurately and effectively evaluate the risks in supply chain and carry out effective operation of risk management. This paper, based on the idea of data-driven supply chain as a core, takes small-batch discrete manufacturing as the research sample to build a data-driven supply chain risk management operation mechanism. The research first established risk identification factors for parts suppliers based on data-driven. Based on influence level of identification factors, the paper proposes the collaborative operation mechanism for supplier risk management from the perspective of big data. The research proposes that the effective measures to ensure the dynamics, efficiency and agility of supply chain risk management are from three perspectives: the top-level design is to build a collaborative mechanism for data-driven supply chain risk management; the mid-level design is the two-factor risk assessment mechanism in data-driven supplier risk management and the basic-level design is the establishment of process restructuring of supply chain risk management driven by big data. Finally, the paper verifies the effectiveness of the proposed collaborative operation mechanism driven by big data.