| 引用本文: | 董骁雄,车飞,陈云翔,等.备件保障效能动态评估方法.[J].国防科技大学学报,2019,41(1):176-182.[点击复制] |
| DONG Xiaoxiong,CHE Fei,CHEN Yunxiang,et al.Dynamic evaluation methods for spare parts support effectiveness[J].Journal of National University of Defense Technology,2019,41(1):176-182[点击复制] |
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| 备件保障效能动态评估方法 |
| 董骁雄1,2, 车飞1, 陈云翔1, 何桢3, 朱强4 |
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(1.空军工程大学 装备管理与安全工程学院， 陕西 西安 710051;2.空军编余飞机储存中心， 河南 平顶山 467300;3.空军研究院， 北京 100085;4.空军指挥学院， 北京 100089)
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| 摘要: |
| 针对目前效能评估方法多重视效能指标的静态观测值，对时序状态数据所蕴含的趋势信息关注较少的缺点，提出基于灰色聚类-粗糙集和集对分析的备件保障效能动态评估方法。针对主客观赋权方法各自的优缺点，引入依赖度和重要度的概念，建立灰色聚类-粗糙集组合赋权模型；将指标权重引入集对理论，提出集对同势、均势和反势的定义，描述备件保障效能的变化规律，构建基于马尔可夫链的集对分析动态模型。实例分析结果表明，该方法可以有效反映备件保障效能的动态变化特征，为决策者制定备件保障长期计划提供科学依据。 |
| 关键词: 备件 保障效能 动态评估 灰色聚类 粗糙集 集对分析 |
| DOI：10.11887/j.cn.201901024 |
| 投稿日期：2018-02-28 |
| 基金项目:国家自然科学基金资助项目（71601183） |
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| Dynamic evaluation methods for spare parts support effectiveness |
| DONG Xiaoxiong1,2, CHE Fei1, CHEN Yunxiang1, HE Zhen3, ZHU Qiang4 |
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(1.Equipment Management & Safety Engineering College, Air Force Engineering University, Xi′an 710051, China;2.Air Force Surplus Aircraft Storage Center, Pingdingshan 467300, China;3.Air Force Research Institute, Beijing 100085, China;4.Air Force Command College, Beijing 100089, China)
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| Abstract: |
| According to the fact that current effectiveness evaluation models lay more emphasis on the static observations of indicators and less on the trend information inherent in sequential observations, a new dynamic evaluation methods for spare parts support effectiveness based on grey clustering-rough set and set pair analysis was proposed. Compared with the subjective and the objective weight-deciding method′s virtue and disadvantage, the weight of every index was decided by using grey clustering-rough set combinational method. By establishing the set of spare parts support effectiveness evaluation set pair, the dynamic variation law of the protection of spare parts was described by definition of set pair equal power balance power and opposite power, Based on Markov chain, the dynamic set pair model was analyzed, The results show that the model can reflect the spare parts support effectiveness dynamic characteristics effectively, giving the decision makers a scientific reference to develop a long-term plan for the support of spare parts. |
| Keywords: spares support effectiveness dynamic evaluation grey clustering rough set set pair analysis |
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