Determining optimal granularity level of modular product with hierarchical clustering and modularity assessment

Abstract

Modular product architecture is beneficial for the product maintenance, upgrade, components’ concurrent design through team work, and achieving the mass customization eventually. Recent researches tend to group elements into modules as a flat map, but this is inconsistent with the nested composition in product final assembly. Finding the hierarchical modular partition for elements of a product and obtaining its optimal granularity level are still necessary to ease the partition and combination for sub-design tasks. We use the design structure matrix (DSM) to represent the relationships among elements of a product. The hierarchical clustering functions such as pdist and linkage within MATLAB software are utilized to form the hierarchical dendrogram for DSM elements, and the modularity index Q is applied to assess the modular clustering results. The partitions are acquired by various distance threshold values in the vertical axis of the hierarchical dendrogram. The ‘cityblock’ and ‘average’ are found as preferred parameters for pdist and linkage functions, respectively, from loop test experiments. Combining the modularity formula in a research literature, a hierarchical modular architecture design methodology is proposed in this work to determine the optimal granularity level of a modular product and to provide solutions for designer selection. Case studies and comparisons in a benchmark problem and a concrete spraying machine illustrate the effectiveness and efficiency of the proposed method. It is characterized by being able to find stable modular partition results for both float and binary DSM elements and satisfying the recommended modular number rule simultaneously.