Understanding design change propagation in complex engineering systems using a digital twin and design structure matrix

Purpose As the engineering design process becomes increasingly complex, multidisciplinary teams need to work together, integrating diverse expertise across a range of disciplinary models. Where changes arise, these often find it difficult handle due complexity and interdependencies inherent in systems. This paper aims develop an innovative approach clarifying system predicting change propagation at asset level complex systems based on digital-twin-driven structure matrix (DSM). Design/methodology/approach The first defines DSM terms elements interdependencies, where authors have defined three types interdependency, namely, geospatial, physical logical, level. digital twin model was then used generate large-scale DSMs cluster analysis further conducted improved Idicula–Gutierrez–Thebeau algorithm (IGTA-Plus) decompose such into modules for convenience efficiency propagation. Finally, prediction method has been developed by (CPM), load-capacity fuzzy linguistics. A section infrastructure mega-project London selected as case study illustrate validate approach. Findings formally spatial algebra Industry Foundation Classes (IFC) schema. Based definitions, (1) automatically through use IFC files, (2) IGTA-Plus (3) predict DSM, CPM, From study, results showed that can help designers manage quantitatively conveniently. Originality/value research contributes new perspective management be beneficial assist making reasonable decisions when changing designs