Towards understanding dynamic design change propagation in complex product development via complex network approach

Design change propagation is a primary source of risk and innovation in complex product (CP) development. Soundly predicting and managing the design change propagation have become critical issues. Dynamicity is the non-negligible nature of design change propagation. However, existing specific case studies and static predicting methods are inadequate to analyze the dynamicity quantitatively. Here, a general model based on complex network is developed to depict the dynamic design change propagation. Numerical simulations are conducted to explore the general law of the propagation and investigate the influences of design change tolerance capacity distribution ( $\alpha ,\beta $α,β), attack strategies, and recovery capacity ( $\gamma $γ). The results show that the model can well portray the real design change propagations. The dynamic design change propagation can be controlled by adjusting the parameter $\alpha $α, $\beta $β, and $\gamma $γ. A new indicator ${\alpha ^\ast } $α∗ is proposed to represent the robustness of the CP network, which is negatively related to β and positively related to γ. The influences of attack strategies and recovery capacity decrease with the increase of β. The cost-effective trade-off criteria to conclude the design change propagation within limited time are provided. This paper provides a basic framework to understand the dynamic design change propagation in CP development.