【作者】 孙蕾；

【导师】 左洪福；

【作者基本信息】 南京航空航天大学 ， 载运工具运用工程， 2013， 博士

【摘要】 航材的全方位支援能力已经成为影响飞机制造商抢占市场的重要因素。面对新趋势，上海飞机客户服务有限公司在成立早期便面临极大的挑战。在当前形势下，本文以航材为研究对象，以提高航空公司飞机签派可靠性为目的，根据历史需求信息进行需求预测，同时考虑到成本费用、修理级别等因素，从系统的角度来解决实际应用中各种情况下的航材库存配置决策问题，并在解决难点问题的基础上，对航材工程数据进行信息化管理，开发了比较完整的支撑系统。本论文的主要研究内容如下：(1)对航材需求预测方法进行研究。首先介绍了波音、空客在对航空公司进行初始备件推荐时用到的航材需求量计算模型；接着，对于后续需求预测问题，介绍了常用的连续性及间断性需求方法。针对高价周转件的低需求、随机性、不确定特性，采用模糊逻辑与神经网络相结合的模糊神经网络预测模型，同时采用PSO进化寻优来优化预测模型；最后将模型预测值与其他预测方法，如回归模型方法，以及间断预测方法等，根据预测误差的对比研究证明，该方法有效提高了预测精度。(2)周转件多级库存优化配置研究。针对周转件供应链上主制造商总部、航空公司基地的航材配置问题，提出了主制造商管理库存模式下面向系统优化的多级库存配置模型。模型在建模中对维修保障供应链等级与维修层级进行抽象及简化。首先，通过分析选取衡量民机效能的关键指标；然后，根据航空公司的运营计划、保障站点组织、航线结构，得到基地的年平均需求量,并根据需求差均比选择合适的分布，描述基地和总部的需求到达过程；接着，为解决民机这种复杂系统的优化效率问题，以机队的保障效能为目标，费用为约束，采用边际分析法进行优化求解；最后给出实例，详细介绍了求解优化过程及结果，并与波音的基于单基地、单航材的数量确定方法进行对比，表明了本文方法的实用性与优越性。(3)具有横向供应的多级库存优化模型。针对符合(S-1,S)库存策略的周转件多级库存问题，考虑当基地短缺航材时，从邻近基地横向转借，而非从距离更远的主制造商总部申请的情况。首先对随着库存状态变化而改变的基地航材需求率建模。当库存为正的时候，需求等于正常的需求率加上横向供应给其他基地的平均需求率；当库存为零或负值时，此时的需求率等于航材的短缺率；接着建立马尔科夫稳态方程，利用近似算法分别对基地立刻满足的需求概率、通过横向供应满足的需求概率以及短缺的需求概率进行数值求解，利用仿真实验进行验证；最后以航材满足率为约束、库存成本为目标建立库存优化模型，并用启发式算法求解。(4)以维修BOM为核心对航材支援数据进行集中管理。首先，将来源于设计院、制造厂、供应商、库存与商务管理以及飞机用户等多来源的航材支援所需数据进行梳理分类，从中提取航材属性信息，并基于国际规范和行业标准，建立代码化的航材参数体系；接着，根据修理级别、IPC的可拆卸原则，确定维修BOM的底层结构，以复合式维修BOM取代单树式BOM集中存储航材资料信息；最后，采用模块化的构型管理模式对维修BOM进行有效性控制，并在此基础上提取基于构型的潜在航材集（S集）。通过以上研究为C919大型客机航材的信息化管理和航材计划工作奠定数据基础。(5)建立了基于数据管理的航材预测与库存配置系统。系统采用浏览器/服务器（B/S）模式组建，是一个覆盖航材基础数据库和航材需求预测、库存优化配置等主要管理功能的综合性软件系统。系统作为航材支援的唯一数据源及管理系统，运行高效，提供的数据全面、可靠,并且具有可扩展性，是C919大型客机航材支援系统的基础性支撑系统之一。更多还原

【Abstract】 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更多还原