TY - GEN
T1 - Cognitive Digital Thread for Intelligent Traceability Establishment in Model-Based Systems Engineering
AU - Huang, Jianyu
AU - Wang, Guoxin
AU - Wu, Shouxuan
AU - Lu, Jinzhi
AU - Zhang, Haoxuan
AU - Qiao, Jiaxing
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Traceability plays an important role in model-based systems engineering (MBSE) practices, which helps engineers to ensure information consistency and correct constraint propagation throughout the system lifecycle. However, intelligently establishing trace links between heterogeneous models still faces several challenges, including those from tool interoperability and their inner scale complexity. To address these challenges, this paper employs a Cognitive Digital Thread (CDT) to develop a tool-chain to support intelligent trace links establishment between MBSE models. The CDT tool-chain first transform model information into unified services for tool interoperability using the Open Services for Lifecycle Collaboration (OSLC) standard. After that, a traceability engine are developed to intelligently capture and establish trace links based on model semantics in the proposed CDT tool-chain. A case study based on the design of a landing gear system demonstrates the feasibility and effectiveness of the proposed CDT tool-chain. The result of the case study indicates that the proposed CDT tool-chain improves the scalability and efficiency when establishing trace links between different MBSE models.
AB - Traceability plays an important role in model-based systems engineering (MBSE) practices, which helps engineers to ensure information consistency and correct constraint propagation throughout the system lifecycle. However, intelligently establishing trace links between heterogeneous models still faces several challenges, including those from tool interoperability and their inner scale complexity. To address these challenges, this paper employs a Cognitive Digital Thread (CDT) to develop a tool-chain to support intelligent trace links establishment between MBSE models. The CDT tool-chain first transform model information into unified services for tool interoperability using the Open Services for Lifecycle Collaboration (OSLC) standard. After that, a traceability engine are developed to intelligently capture and establish trace links based on model semantics in the proposed CDT tool-chain. A case study based on the design of a landing gear system demonstrates the feasibility and effectiveness of the proposed CDT tool-chain. The result of the case study indicates that the proposed CDT tool-chain improves the scalability and efficiency when establishing trace links between different MBSE models.
KW - Artificial intelligence (AI)
KW - Cognitive digital thread
KW - Digital thread
KW - Modelbased systems engineering (MBSE)
KW - Semantic
KW - Traceability
UR - https://www.scopus.com/pages/publications/105034994073
U2 - 10.1109/ISSE65546.2025.11370120
DO - 10.1109/ISSE65546.2025.11370120
M3 - Conference contribution
AN - SCOPUS:105034994073
T3 - ISSE 2025 - 11th IEEE International Symposium on Systems Engineering, Symposium Proceedings
BT - ISSE 2025 - 11th IEEE International Symposium on Systems Engineering, Symposium Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Symposium on Systems Engineering, ISSE 2025
Y2 - 28 October 2025 through 30 October 2025
ER -