Conference Agenda

As systems become increasingly data-centric, interdisciplinary engineering design faces growing complexity and interdependencies. This paper investigates how a combined Design Structure Matrix (DSM) and graph-based modeling approach supports interdisciplinary decision-making by revealing critical data dependencies, compared to standalone DSM or graph models. Based on a case study on autonomous public transportation and expert input, the results illustrate complementary insights enabled by the combined approach and discuss its implications for industrial system design.

Technical Debt (TD) is a buzzword that has gained traction among IT practitioners and researchers, as a financial metaphor explaining how existing elements can hinder future changes. In engineering design terminology, managing TD can be equated to managing the redesign of existing systems, a task in which change propagation plays a key role. Via a partnership with Ubisoft, a game development firm that owns and operates a global IT network, we present a case study showcasing a novel way to explore interfaces and propagations in engineering systems interventions, analyzed using Axiomatic Design.

Product configuration systems support customized design in complex engineering. However, as products grow in complexity, the configuration model also grows, making it important to manage these models effectively. Based on industrial case studies, This study shows how companies structure their configuration models and how modularization helps improve flexibility, maintainability, and scalability. The results provide empirical insights and practical guidance for structuring robust configuration models in complex engineering contexts.

With the introduction of SysML v2—featuring a new metamodel and standardized APIs—new opportunities arise for automating MBSE tasks through generative AI. However, existing LLM approaches lack interoperability due to limited support for complex SysML v2 API operations. This paper presents a framework for implementing Model Context Protocol (MCP) servers for SysML v2, enabling LLMs to interact with system models via the API. This framework provides a foundation for agentic MBSE by allowing automation of modeling tasks while maintaining interoperability across tools and generative AI systems.