Influential process nodes identification strategy for aircraft assembly system based on complex network and improved PageRank

In the manufacturing network, the fluctuation of process operation time can result in the delay of the total completion time, which brings a huge challenge to controlling entire production schedule. For aircraft manufacturing industries, the processes that have a significant impact on the completion time of the assembly line need to be identified and monitored in order to ensure the final assembly efficiency and reliability. However, due to the large number of process nodes and the complexity of resource constraints and relationship constraints, traditional node centrality algorithms cannot identify influential nodes accurately. Therefore, based on complex network theory, this paper studies the influential nodes identification problem in the context of assembly lines. Firstly, The Resource-Process Coupling Network for the assembly line is constructed based on the production background and network resource characteristics. Then, based on PageRank algorithm and the idea of resource iteration, Improved PageRank Algorithm (IPRA) is proposed to identify influential process nodes, which brings the resource and time parameters into the allocation rules. Finally, according to simulation results, a comparative analysis of IPRA and existing algorithms is conducted and concludes that our method can better identify influential nodes in actual complex production networks. Furthermore, this paper identifies influential process nodes of aircraft assembly line based on the case of the commercial aircraft manufactory.