Cognitive digital thread supporting agile reuse of knowledge in model-based systems engineering

With the increasing complexity of systems, ModelBased Systems Engineering (MBSE) has become the mainstream approach for managing structured information through digital models and enabling automated verification. However, enterprises have accumulated substantial engineering documents over decades, which preserve valuable design knowledge and domain expertise. In the context of digital engineering, digital artifacts such as documents and digital models constitute complementary elements that will coexist throughout the industry's digital transformation. Transforming existing documents into MBSE models therefore represents a sustained capability for minimizing MBSE adoption cost while preserving organizational knowledge assets. Yet, automated document to model transformation faces significant challenges due to incompatible tool formats, diverse document structures, and knowledge scattered across unstructured content. This paper presents an agile knowledge reuse framework based on the Cognitive Digital Thread (CDT) concept. The framework employs Open Service for Lifecycle Collaboration (OSLC) compliant adapters for documents and modeling tools to unify content and operations as service interfaces. Mapping rules derived from document structures guide a rule engine to automatically extract document knowledge and generate system architecture models. A case study of landing gear system design demonstrates that the generated models remain consistent with their source documents, providing a practical solution for agile MBSE transformation based on existing knowledge assets.