Improving the reliability and flexibility of key process assembly schemes is a critical factor in the intelligent management of aircraft production. However, the complexity of aircraft assembly operations, large-scale production, and fierce competition for resources aggravate the difficulty of key process identification in the aircraft assembly manufacturing system. To efficiently recognize the key processes and facilitate the management of the aircraft assembly, this study proposes an adaptive influential node identification framework. The aircraft assembly manufacturing system is transformed into an assembly complex network (ACN) according to the technology. Then, the problem of community detection is addressed by applying the Louvain algorithm to partition ACN into several communities. Moreover, within each community, the structure characteristics and physical information are combined to evaluate the influence of the node. Finally, the experimental results demonstrate the efficiency of the proposed framework in adaptively analyzing ACN and identifying key processes in the aircraft assembly manufacturing system. This study provides an efficient and convenient solution for key process identification in aircraft assembly system management.