To solve the problem that it is difficult to classify aviation material consumption data, a classification model based on consumption fluctuation clustering analysis is established. Based on the fluctuation of the consumption sequence, the aviation materials are converted into two-dimensional graphs. Due to its short service time and small quantity of aviation material samples, the unsupervised classification algorithm is used to classify the aviation material. Aiming at the limitation of traditional clustering algorithms, a hierarchical partition clustering algorithm is proposed, and the “tolerance to distance ratio” parameter is used to select a good environment for the initial center. The simulation results show that the hierarchical partition clustering algorithm is more stable and efficient.