Robust Analysis Of Production Supply Chain Network

Artificial intelligence,data science and cloud applications have greatly promoted the rapid development of Internet of Things technology.While the manufacturing industry has obtained numerous development opportunities,it also faces tremendous pressure and challenges.In the fierce competition,business cooperation has gradually developed from a single chain structure to a network structure,which is conducive to helping enterprises complement each other's advantages,mutual benefit and win-win situation,and increase their competitiveness.However,with the continuous expansion of geographical scope and field cooperation,the supply chain network is susceptible to many internal and external factors,which increases supply chain risks and makes the supply chain network appear fragile.How to make the supply chain operate effectively under the interference of many factors is particularly important.Therefore,the topic of the robustness of the supply chain has attracted widespread attention from all walks of life.This article analyzes and summarizes the relevant research on supply chain and robustness of different scholars at home and abroad,clarifies the related concepts of supply chain,supply chain management,and supply chain robustness,and analyzes the influencing factors of the production supply chain on this basis.Aiming at the problem of the robustness of the production supply chain,this article firstly builds a five-level local world network evolution model for the production supply chain based on the BA model from a macro level and according to the evolution characteristics of the production supply chain.The simulation model studies the changes in the number of nodes,clustering coefficient,degree distribution and other network characteristics of the production supply chain network at different time steps,and compares it with the BA model.At the micro level,this paper takes into account the complexity and scalefree characteristics of the production supply chain,introduces complex network theory,conducts quantitative research on the network robustness,and builds a production supply chain robustness analysis model.The improved node contraction method and the triangular fuzzy number method are used to comprehensively and objectively evaluate the importance of nodes in the network,and analyze the robustness changes of the production supply chain network under both deliberate and random attacks.Combined with actual cases,analyze the robustness of the supply chain network.This paper conducts research from two aspects: the evolution of the production supply chain network and the protection of important nodes.In the aspect of network evolution,it is found that the production supply chain network is scale-free and highly agglomerated.With the continuous expansion of the network scale,the overall distribution of the network to approach the power-law distribution with an exponent of3,and in the process of large-scale evolution,the text model is better than the BA model.By changing the weighting coefficients,the changes in the robustness of the production supply chain network under different evolution rules are studied.It is found that the robustness of the network with a weighting coefficient of 0.8 under deliberate attacks is higher than that of the network with a weighting coefficient of 0.6,while under random attacks,the gap between the two networks is not large.Research on the protection of important nodes has found that under deliberate attacks,the attack strategy based on node importance will damage the supply chain network more than the other two attack strategies.The robustness index has the largest decline and the fastest speed.The supply chain network has better robustness under random attacks.Corresponding improvement measures are proposed to improve the robustness of the production supply chain network in response to the problems that arise,which provides certain research ideas for network optimization design and protection of important nodes in actual work.