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基于故障预测信息的维修资源优化决策技术与系统

Research on Optimal Decision of Maintenance Resource Based on Prognostics

【作者】 陈少将

【导师】 邱静;

【作者基本信息】 国防科学技术大学 , 机械工程, 2010, 硕士

【摘要】 随着维修模式从事后维修到视情维修、状态维修的转变,装备维修资源保障也朝着信息化、网络化、智能化的方向发展。自主维修保障系统通过故障预测健康管理系统与联合分布式信息系统共同完成装备的维修保障,准确的故障预测信息对装备维修资源决策起到十分重要的作用。因此,开展基于故障预测信息的维修资源优化决策技术的研究,对于现代装备维修保障系统具有重要的意义。本文根据自主维修保障系统的特点,重点从系统体系结构分析、维修备件库存策略、供应链优化三个关键问题着手,采用理论分析与案例应用相结合的办法,进行了基于故障预测信息的维修资源优化决策技术与系统研究,论文的主要内容包括:1.系统地分析了自主维修保障系统的工作原理,应用系统设计方法进行基于故障预测信息的维修资源优化决策系统的总体设计,为优化决策技术研究和系统开发奠定基础。2.分析了自主维修保障系统调度机制,提出基于故障预测信息的维修备件多级库存优化决策技术。在功能单元风险成本模型、维修备件缓冲库存模型的基础上,建立维修备件多级库存边际成本模型,进行维修备件库存优化,并以正态分布故障件为例进行了仿真分析。案例结果表明了该项技术的可行性和有效性。3.分析了传统装备供应链的不足,建立联合分布式供应链模型,提出了基于故障预测信息的供应成本优化决策技术,案例结果表明联合分布式供应链模型和决策技术符合当前的保障需求。4.利用VisualBasic.Net、SuperMap Objects.NET 6R和Microsoft Access 2007进行基于故障预测信息的维修资源优化决策系统实现,并以某导弹发射车的维修保障为对象进行应用。应用效果表明:基于故障预测信息的维修资源优化决策系统能够有效、合理的进行装备维修资源决策。

【Abstract】 With the equipment maintenance innovation from Run to Breakdown Maintenance (RBM) and Preventive Maintenance (PM) to Condition-Based Maintenance (CBM), maintenance resource logistics are improved by information, network and intelligence. The Autonomic Logistics System (ALS) implements maintenance and logistics actions by combining Prognostics and Health Management(PHM) with Joint Distributed Information System(JDIS). The accuracy of the fault prognostics has great influence on the optimal decision of maintenance resource. Thus, research on the optimal decision of maintenance resource based on prognostics is important for current equipment maintenance logistics. According to the characters of the ALS, this reaecrch mainly involves with three key issues: system structure analysis, spare parts inventory strategy and supply chain optimization. The contens of this paper is as follows:1. Firstly, the operational mechanism of the ALS is analyzed and the optimal decision system of maintenance resource based on prognostics is constructed. It is the foundation of the optimal decision-making method and system.2. Secondly, the schedule mechanism of the ALS is analyzed and an optimal multi-echelon inventory decision method on based on PHM is proposed. This decision method is composed of an opportunity cost model, a spare parts inventory mode and a margin cost model of lost utilization. The spare part inventory is optimized based on the models. And then a simulation is performed in which the failure probability distribution function subjected to normal distribution. The numerical examples illustrate the validity and feasibility of the method.3. Thirdly, a model of joint distributed supply chain is proposed to eliminate the insufficiency of traditional supply chain. An optimal decision of supply cost based on PHM is put forward. The case application shows that the model of joint distributed supply chain and the porposed method can improve the current maintenance logistics.4. Finally, a demonstration system is developed using the following softwares: VisualBasic.Net, SuperMap Objects.NET 6R and Microsoft Access 2007. A missile vehicle maintenance logistics is discussed to demonstrate the applicability of the proposed methodology. The result shows that maintenance resources decision can be optimized effectively through this optimal decision system.

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