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ISSN      1003-9775
CN        11-2925/TP
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架构约束条件下产品模块识别的可视化方法

卫军朝1), 张国渊2)*, 闫秀天1,3)
1) (西北工业大学机电学院 西安 710072)2) (西安电子科技大学机电工程学院 西安 710071)3) (Design Manufacture & Engineering Management, University of Strathclyde Glasgow G1 1XJ )
分类号: 中图法分类号: TP391.41 DOI: 10.3724/SP.J.1089.2018.16554
出版年,卷(期):页码: 2018 , 30 ( 5 ): 936-945 卫军朝
摘要: 为了在考虑架构约束条件的产品模块化过程中直观地识别出模块, 提出一种基于可视化对角矩阵的方法. 首先通过包含架构约束条件的遗传算法自动产生一组优化的模块划分方案; 其次根据优化解集构建出成组可能性矩阵(GLM)并对其对角化, 得到对角GLM(DGLM); 再将DGLM的非对角单元根据可能性值进行着色; 最后通过DGLM辨识出系统的典型结构和各种潜在的模块. 以磁共振成像设备中的注射器为实例, 验证了该方法的有效性.
关键词: 模块识别; 架构约束; 成组可能性矩阵; 可视化
A Visual Method for Identifying Modules Considering Architectural Constraints
Wei Junchao1), Zhang Guoyuan2)*, and Yan Xiutian1,3)
1) (School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072) 2) (School of Mechano-Electronic Engineering, Xidian University, Xi’an 710071)3) (Design Manufacture & Engineering Management, University of Strathclyde, Glasgow G1 1XJ)
abstract: In order to intuitively identify modules in the product modularization process with considering the architectural partitioning constraints, a visual diagonalized matrix-based method was proposed. First, a genetic algorithm incorporating architectural constraints was used to generate automatically a set of optimized module partition solutions. Then, a grouping likelihood matrix(GLM) was obtained using these optimized solutions and was diagonalized to form a diagonalized GLM (DGLM). Next, off-diagonal cells of the DGLM were color-encoded according to their likelihood values. Finally, the typical system structures were displayed in the visual DGLM, and potential modules were identified. A case study of designing a MRI machine injector was carried out to verify the effectiveness of the proposed method.
keyword: module identification; architectural constraints; grouping likelihood matrix; visualization
 
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