基于ANP-FCE模型的大型航天研制项目风险评估方法研究
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摘要
大型航天研制项目对于社会经济发展和国防安全有着重要的影响,是国家重大工程中一类较为特殊的项目。对于这类高风险性的复杂项目来说,项目风险管理水平的高低已成为项目成功与否的主要决定因素之一。风险评估作为项目风险管理过程中的关键环节,对项目风险管理的质量起着重要的作用。由于大型航天研制项目风险的多样性、多层次性和非线性等特征,使得整个项目的风险因素之间呈现出网络化结构,因此以往的先将项目总风险分解为一种独立递阶层次结构然后再进行综合的风险评估方法不再符合实际情况,需要研究新的风险评估方法来解决这类大型复杂项目的风险评估问题。
     本文在“某大型航天工程系统工程管理研究”课题的支持下,在阐述风险管理理论和方法的基础上,针对大型航天研制项目的风险因素众多,风险因素之间存在相互依赖和相互影响的特点,将网络分析法和模糊综合评价进行集成运用,提出了基于ANP-FCE模型的大型航天研制项目风险评估方法,为解决大型航天研制项目的风险评估问题提供了一种新的思路。论文的主要研究内容和创新点有:
     1.根据大型航天研制项目风险的特征,运用层次全息建模(HHM)的思想和方法,建立了更具代表性和广泛性的大型航天研制项目风险识别的HHM框架。应用该框架可以对影响大型航天研制项目的风险因素进行全面系统地识别与分析。
     2.针对大型航天研制项目风险因素之间存在相互影响的问题,提出了大型航天研制项目风险评估网络化指标体系的构建原则和构建方法。
     3.将网络分析法和模糊综合评价集成运用,提出了基于ANP-FCE模型的大型航天研制项目风险评估方法。该方法弥补了层次分析法在解决大型复杂项目风险评估问题时的缺陷,使各个风险因素相对于项目总风险的权重分配更加合理,在有效地解决风险评估过程中人们认识上的模糊性问题的同时更加细致地对风险因素的多个维度进行描述,并且将对风险因素的评价信息集中体现出来,初步实现了网络分析法和模糊综合评价两种研究思路在更高层次上的统一。
     4.结合某大型航天研制项目的实例,运用网络化指标体系的构建方法,构建了该项目风险评估网络化指标体系,利用基于ANP-FCE模型的风险评估方法,确定了该项目的风险水平和关键风险因素,为该项目的风险控制与管理提供了决策依据。
Large-scale space development project (LSDP) is a kind of project which possesses some small especial characteristics and is significant for the social economy development and national security .To these high risk projects, the quality of the implementation of risk management directly affects projects. Risk assessment is the key step of the project risk management process, and play very important role in the project risk management. The LSDP risks are characterized as diversity, multi-lays, nonlinear , thus, the conventional risk assessment methods which divide the whole project risk into independent and step-by-step structure is not fit for the practice. So it is very important to study new risk assessment methods to solve these large-scale complex projects.
     This dissertation is supported by the system management research of a large-scale space program. Based on the existed theories and methods of risk management, we present a new risk assessment method based on the ANP-FCE model to analyze the LSDP whose risk factors is diverse, interactive and interdependent. The method synthetically involves the analytic network process (ANP) and fuzzy comprehensive evaluation (FCE), and can be used to resolve the LSDP risk assessment problem. The main research and achievements of this dissertation are as follows.
     Firstly, according to the characters of the LSDP, we use the hierarchical holographic modeling (HHM) method to establish a more representative and universal HHM framework of the LSDP risk identify. Using this framework, we could identify risk factors of LSDP more thoroughly and systemically.
     Secondly, for the problem that the risk factors of the LSDP are interactive, we propose some principles and methods to build the risk evaluation indicators system of LSDP which seems like a network.
     Thirdly, we propose a new risk assessment method based on ANP-FCE model for the LSDP which synthetically involves the ANP and FCE. The new method offset the disadvantage of using analytic hierarchical process (AHP) to assess the risk of the large-scale complex system, and makes the distribution of priorities more reasonable. Moreover, it resolves the human’s fuzzy understanding in the risk assessment. Thus, the new method integrates the two methods suitably.
     Finally, we apply the new method to a large-scale space development project, and build the risk evaluation network indicators system. Using the risk assessment method based on ANP-FCE model, we evaluate the risk level of the project and identify the key risk factors. These results can provide decision information for the project risk controlling and management.
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