尤杨, 陈军, 和倩倩. 面向油料装备的产品族聚类划分方法[J]. 油气储运, 2016, 35(3): 290-294, 301. DOI: 10.6047/j.issn.1000-8241.2016.03.011
引用本文: 尤杨, 陈军, 和倩倩. 面向油料装备的产品族聚类划分方法[J]. 油气储运, 2016, 35(3): 290-294, 301. DOI: 10.6047/j.issn.1000-8241.2016.03.011
YOU Yang, CHEN Jun, HE Qianqian. POL-equipment-oriented product family clustering method[J]. Oil & Gas Storage and Transportation, 2016, 35(3): 290-294, 301. DOI: 10.6047/j.issn.1000-8241.2016.03.011
Citation: YOU Yang, CHEN Jun, HE Qianqian. POL-equipment-oriented product family clustering method[J]. Oil & Gas Storage and Transportation, 2016, 35(3): 290-294, 301. DOI: 10.6047/j.issn.1000-8241.2016.03.011

面向油料装备的产品族聚类划分方法

POL-equipment-oriented product family clustering method

  • 摘要: 为了解决油料装备面临的部队需求多样化、个性化与低成本、短交货期的矛盾, 采用产品族设计方法对油料装备进行产品族规划。综合分析了油料装备产品族及后勤保障的特点, 基于产品族的模块性和通用性, 以及油料装备自身特征, 提出了模块化、通用性、军事用途和油料保障这4项影响产品族聚类划分的属性。评价装备集合关于这4项属性的关联性, 运用层次分析法确定各属性权重后, 建立装备综合关联度矩阵。运用改进的层次聚类算法对油料装备产品族进行聚类划分, 装备在不同划分粒度下的族类归属用聚类树图表现, 实现了在不同相似度阈值的取值下, 油料装备的相似聚类, 即油料装备产品族划分, 最后用实例证明了该划分方法的可行性。

     

    Abstract: To satisfy demands of the army for oil facilities characterized by diversity, individualization, low costs and short delivery time, techniques for product family design are deployed for product family planning of oil facilities. Upon comprehensive analyzing of specific features of product family of oil facilities and logistic services, and with consideration to the two basic features of product family - modularity and generality, together with specific features of oil facilities, four attributes for product family clustering are highlighted, modularity, generality, military use and fuel oil guarantee. Weights of these attributes are determined through hierarchy process to construct comprehensive correlation matrix for facilities to assess relevancy of these four attributes. Improved hierarchy clustering algorithm is used for clustering of product family of oil facilities. Family classification of facilities under different clustering granularities can be expressed by using clustering tree to achieve clustering of oil facilities under different thresholds of similarity, i.e. clustering of product family of oil facilities. Finally, applicability of the clustering technique is verified by using specific examples.

     

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