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)
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.