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Matrix-based hierarchical clustering for developing product architecture

机译:基于矩阵的层次聚类用于开发产品架构

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Product architecture can influence different aspects of product lifecycle including manufacturing, assembly, and supply chain. The purpose of this article is to employ hierarchical cluster analysis for developing product architecture to support product variety. Design structure matrix is used to visualize and analyze product architecture in view of product modules, overlapping modules, and bus components. The proposed method for design structure matrix clustering consists of three phases. The first phase is component filtering to identify components that should be classified as bus components. The second phase is approximate structure formation that preliminarily organizes similar components to form a diagonal matrix. The third phase is partitioning analysis that finalizes the modules' boundary to yield the structured matrix as the solution of design structure matrix clustering. To examine the solution's quality, minimum description length from literature is used. Then, the proposed method is demonstrated via two literature examples and compared with the solutions by the manual and genetic algorithm approaches. One unique advantage of the proposed method is that the user can obtain and inspect the approximate structure in view of the diagonal matrix before finalizing the structured solution (e.g. estimate the number of modules).
机译:产品体系结构可以影响产品生命周期的各个方面,包括制造,组装和供应链。本文的目的是采用层次聚类分析来开发产品体系结构以支持产品多样化。设计结构矩阵用于根据产品模块,重叠的模块和总线组件来可视化和分析产品体系结构。所提出的设计结构矩阵聚类方法包括三个阶段。第一阶段是组件过滤,以识别应归类为总线组件的组件。第二阶段是近似结构形成,该结构初步组织相似的组件以形成对角矩阵。第三阶段是分区分析,最终确定模块边界以产生结构化矩阵作为设计结构矩阵聚类的解决方案。为了检查解决方案的质量,使用了文献中描述的最小长度。然后,通过两个文献实例对提出的方法进行了说明,并与手动和遗传算法方法的解决方案进行了比较。所提出的方法的一个独特优点是,用户可以在完成结构化解决方案(例如,估计模块的数量)之前,根据对角矩阵获得并检查近似结构。

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