Product complexity management enabled by a model-based approach

As contemporary engineered systems become more interdependent, there is a growing need to manage their system complexity. However, system complexity only exists as implicit and heterogeneous information. This situation makes it difficult to obtain and analyze system complexity. This paper proposes a model-based approach to supporting system complexity management, called MBCM, where system complexity includes dynamic complexity and structural complexity. The proposed approach includes complexity modeling and complexity analysis. For complexity modeling, a graph-matrix hybrid complexity modeling approach is proposed to describe the dynamic and structural complexity information. Graph-based architecture models are developed by a unified meta-meta modeling approach. The connections among different architecture models are then described using a design structure matrix. For complexity analysis, a general complexity metric provides dynamic and structural complexity values for the designer to evaluate the system. Moreover, automatic ontology modeling is introduced to integrate complexity modeling and complexity analysis. Finally, a case study on aero-engine design was conducted. The complexity management processes of three different scenarios were compared in this case study. The comparison results show that our approach could sensitively represent increased product complexity from both dynamic and structural aspects. Thus, the proposed approach is general and applicable to any engineered system and can support the trade-off between complex product design schemes.