Supporting Systems Modeling Using Semantic Cues for Concept Development

Engineering complex systems requires integrating multiple perspectives to create a cohesive whole without overlooking critical elements. In the early stages of concept development, systems engineers often work independently, with limited time and minimal stakeholder input. This constraint increases the likelihood of missing essential system components, leading to models that lack completeness and detail due to cognitive limitations. This work presents an approach for traversing a knowledge graph to extract semantically related concepts from words used in diagrams. The graph search strategy is based on exploration and refinement activities as defined in the systems lifecycle management standard, ISO/IEC/IEEE 24748-1:2024. The weighted concepts are provided as semantic cues to aid word retrieval, optimizing the use of working memory capacity. The proposed method is implemented as a plugin for the diagramming tool Draw.io, utilizing the semantic network, ConceptNet. The plugin dynamically extracts related words and their relationship strengths, visualizing them as word clouds to enhance conceptual modeling. The approach was evaluated using 25 Systemigrams from the literature for measuring its ability to highlight critical features and reduce ambiguity in system representation. Results indicate that the approach helps identify 24.15% more critical features and provides detailed elaboration on 15.5% of them, aligning with key conclusions drawn from the Systemigrams. Additionally, findings suggest that the tool's effectiveness depends on its ability to provide domain-specific vocabulary, particularly in scenarios requiring scientific and engineering comprehension.