| dc.description.abstract | Abstract. Engineering changes are inevitable in product design, especially during the development of complex products, where they often affect multiple-domain engineering entities. Traditional single-domain change models cannot capture the multidimensional nature of products; thus, they may fail to effectively predict change propagation paths or assess impacts. To address this challenge, a multilayer network change model is proposed, consisting of the assembly, feature, face, and parameter layers. This model enables the coupled propagation of changes between parameters and structures. The first three layers represent the product's geometric topology and shape, whereas the parameter layer defines functional relationships among parameters. A parameter change prediction method based on the breadth-first search (BFS) algorithm is introduced to automatically identify and optimize change propagation paths within the parameter layer. Meanwhile, through the interlayer connections between parameters and structures, the structural entities affected by parameters can be identified. A graph isomorphism algorithm is used to accurately locate and identify structural topology change entities. Structural topology change propagation among parts is predicted based on their mating entities. The identified change entities are further used to assess their impact on manufacturing processes. A software system based on the multilayer network change model is developed, and a case study is presented to demonstrate its application in product change design, which shows that the affected manufacturing entities can be pinpointed even when design parameters are changed, and change solutions can be determined in a time-consuming and cost-effective way. | |
