Research On Multi-echelon Inventory Allocation Method And Management For Civil Aircraft

The spare parts supporting capability has become the key factor for the manufactures to seize themarket. In the new situations, the costumer service company faces a great challenge in the initial stage.This thesis focuses on studying spare parts supporting technologies to improve the aircraft dispatchreliability. Based on information management of the spare parts engineering data, the spare partsdemand is forecasted according to the historic demand data. Further considering other factors such asthe cost and the level of repair, the stock allocation decision method in the real situation is developedin a systematic perspective. Based on the research of the thesis, a comprehensive software system isdeveloped. The main contents of the thesis are as the follows:The aircraft spare part demand forecasting methods are studied. The commonly used continuousand discrete demand forecasting methods are introduced, then in view of the low demand, stochasticand uncertain characteristics of the high price turnover parts, the advanced non-linear signalprocessing method-the wavelet transform (WT)-is used to analyze the spare part demand time seriesdata; Based on the sub-signals, the Fuzzy Neural Network forecasting model, which combine thestrength of the fuzzy logic method and neural network method, is developed and the Particle SwarmOptimization (PSO) method is adopted to optimize the furcating model parameters; Finally the sparepart demand forecasting result are obtained based on the wavelet reconstruction of the prediction ofthe sub-signals. The forecasting errors are analyzed and compared with other forecasting methods,such as the regression method and the discrete forecasting method, which shows the effectiveness ofthe proposed forecasting method.The optimization method for the multi-echelon inventory allocation of the turnover parts is studied.In view of the allocation of the spare parts of the manufactures and the airliners in the supply chain ofthe turnover parts, the multi-echelon inventory allocation model with the vendor managed inventoryas the main body while considering the systematic optimization. In the model construction the level ofthe maintenance and support supply chain and level of repair are abstracted and simplified. Firstly, thekey indexes for civil aircraft effectiveness evaluation are established, then according to the airlineroperation plan, the structure of the supporting spots, structure of the route, and the average annualspare parts demand of the base is estimated. The arrival process of demands for the depot and baseswas described by the distribution which was chosen by the ratio of variance-to-mean. In view of thecomplexities of aircraft system, with the fleet support as the target and the cost as the constraint, themarginal analysis method is used to resolve the optimization problem. A case study is carried out, presenting a detailed optimizing process and results. The result is compared with the Boeing proposedsingle base and single part method, which shows the effectiveness and advantage of the proposedmethod.The demand rate at a base depending on the inventory situation is modeled. With positive inventoryon hand the total demand is normal demand plus demand from horizontal transshipments from otherbases. With no positive inventory on hand, the only real demand is the lack rate of the spare parts. TheMarkov equation is adopted to model the problem and the approximation algorithm is used tocompute the instant demand probability, the horizontal transshipments demand probability and thelack probability. With the stock cost as the optimization target and the spare parts demand satisfyingrate as the constraint, the model is established and the heuristic algorithm is used to resolve theproblem.Firstly, Centered on the maintenance BOM, the spare parts support data is managed in a centralizedstyle. Firstly, the data from designers, the manufactures, the suppliers, the stock and businessmanagers as well as the operators is sorted out, then the air material related information is extractedand the coded air material parameter system is established; according to the level of repair, thedetachable principle of the IPC, the underlying structure of the maintenance BOM is determined andinstead of the tree type BOM, the compound maintenance BOM is adopted to centrally store the airmaterial data; Modularized configuration management method is used to control the effectiveness ofthe maintenance BOM, based on which the configuration–based potential spare parts (S files) areextracted. Through this study the data foundation for air material information management andplanning has been established for C919aircraft.The data management based spare parts forecasting and stock allocation software system isdeveloped. The B/S architecture is adopted, covering the basic spare parts data, spare parts demandforecasting, stock allocation optimization and so on. The system, as the sole data source for spareparts support and management, can run efficiently, providing comprehensive and reliable data. Thesystem is extendible and is basic one of the C919aircraft spares parts supporting systems...