A Visual Method for Identifying Modules Considering Architectural Constraints

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.