A risk prediction method for change propagation based on industrial design network evolution

Abstract

In the process of complex product design, rapid design changes bring product development risk. The study of complex product change propagation is an important means to reduce change risks. Traditional methods model the product structure into a network and predict the impact of change propagation through network attributes. However, these methods ignore the form elements of industrial design based on product structure, and the influence mechanism of the designer in the process of change propagation. To explore the influence of industrial design in change propagation, this study proposes a risk prediction method for industrial design change propagation based on complex network evolution. A comprehensive evaluation method based on network and design scheme correlation characteristics is developed to map the structure layer and the form layer, resulting in a multilayer industrial design network model. By extracting influencing factors from designers, a designer-constrained and driven industrial design change propagation and evolution method is established to simulate the real-world influence of design team behavior and support dynamic risk prediction. Finally, the effectiveness and reliability of the method are verified through an engineering case involving the industrial design change of an intelligent cabin. For industrial design change, it performed with better accuracy and robustness.