This study investigates the cost measurement and optimization of aviation material sharing under multi-client and multi-fleet conditions, and develops a systematic theoretical framework and implementation model. First, using the average annual flight hours of each customer’s fleet and a Poisson distribution model, the demand for each part number in the sharing pool is accurately forecast. Based on these forecasts, optimal stock quantities are determined to meet varying protection requirements, thereby maximizing the scale pooling effect and effectively reducing the unit cost of spare parts. Second, the cost structure of aviation material sharing is systematically analyzed, integrating four cost categories—depreciation, capital consumption, labor management, and agreed expenditures—into a unified model. An innovative cost-sharing mechanism is proposed that combines the “flight hour ratio” with the “probability of spare parts consumption,” balancing fairness with incentive constraints and effectively preventing “free-riding” behaviors. To validate the method, a software system is designed and developed, integrating parameter setting, data management, preprocessing, calculation execution, and result visualization, thereby automating the process from historical data import to hourly cost output. Case applications demonstrate that the proposed approach significantly reduces hourly costs, greatly improves measurement efficiency in typical sharing scenarios, and achieves further cost savings in the initial coverage stage through multi-location sharing and dual-source supply strategies.
