上海交通大学学报

上海交通大学学报（自然版） ›› 2011, Vol. 45 ›› Issue (09): 1288-1293.

• 金属学与金属工艺 • 上一篇    下一篇

工序网络的拓扑结构与配置性

闫栋a，董明b   

  1. (上海交通大学a. 机械与动力工程学院， 上海 200240； b. 安泰经济与管理学院， 上海 200052)
  • 出版日期:2011-09-30 发布日期:2011-09-30
  • 基金资助:

    上海市教育委员会曙光计划项目(09SG17)，欧盟合作基金项目(149674-EM-1-2008-1-UKERAMUNDUS)

Topological Structure and Configurability of Process Networks

 YAN  Dong-a, DONG  Ming-b   

  1. (a. School of Mechanical Engineering, Shanghai 200240; b. Antai College of Economics and Management, Shanghai Jiaotong University, Shanghai 200052, China)
  • Online:2011-09-30 Published:2011-09-30

摘要： 以实际的汽轮机制造工序网络为研究对象，分析通用的工序对模体形式和网络的拓扑连通性，以揭示工序对的配置规律.基于复杂网络理论，从微观角度揭示工序网络的模体结构，并从宏观角度分析工序网络的度分布特性.结果表明：复杂的工序网络是简单模体类型的多样化拓扑组合，其拓扑连通性具有衰减幂律的无标度特性，只有少数拥有较大度值的工序才具有较多的配置关系；工序网络的拓扑连通性还具有非协调性，且一部分配置关系具有随机性，表现出较弱的配置性，而另一部分具有技术约束性，表现出很强的配置性.所提出的基于非协调性的度相关系数可以评价任意工序对或整条工序链的配置性.

关键词: 工序网络, 模体, 连通性, 度相关性

Abstract: The machining process network of real industrial steam turbines was chosen to analyze common motif types of process couples, and to study the topological connectivity of the network in order to discover the configuration law of process couples. For connectivity of process network, based on complex network theory, the motif structures of the network were discovered from the microscope view, and its degree distribution features were analyzed from the macro one. The results are as follows: the complex process network is the diverse topology collection of simple motif types; its connectivity reveals the scalefree feature with the decaying power law, so only a few processes with large degree values hold many configuration relationships; and moreover, the connectivity shows disassortativity, so that a part of configuration relationships behaving randomly bears a weak configurability, but others with technology restriction reveal a strong one. The degree correlation coefficients proposed on the basis of disassortativity can be applied to evaluate the configurability of a process couple or whole process chain.

Key words: process network, motif, connectivity, degree correlation

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