Analyzing the robustness of technical products by combining MBSE approaches and knowledge graphs with query templates

Technical product development aims to fulfill stakeholder requirements by delivering products with demand-driven functionality. Numerous influencing factors, such as external disturbances, input variable variations, and changes in internal product characteristics (e.g., wear and deformations), can affect the product functions and lead to unintended behavior. To improve the robustness of technical products, it is essential to identify and analyze these factors and their potential impacts during the concept phase of product development. This requires structured and reusable knowledge. Model-Based Systems Engineering (MBSE) supports the development of complex technical products but can only serve as a basis for determining robustness to a limited extent due to the available information and the degree of maturity in the models. Reusing existing product knowledge within a specific context is essential for product development, especially to improve robustness. Coupling MBSE approaches with reusable knowledge representations, such as knowledge graphs, can support analysis and decision-making. To achieve this, knowledge representation must provide empirical knowledge about potential failures, influencing factors, and so forth. This contribution presents an approach for coupling knowledge graphs with MBSE models using SysML to perform context-specific queries in the knowledge graph based on the specifications in the SysML model. Additionally, the contribution proposes a structured approach for enriching the knowledge graphs. The approach is presented and implemented using an example application of a mobile robot.