Researchers from the University of Antwerp, Belgium, and the University of Antwerp Management School have developed a framework to streamline experimentation in Model-Based Systems Engineering (MBSE). The team, led by Johan Cederbladh and including Loek Cleophas, Eduard Kamburjan, Lucas Lima, Rakshit Mittal, and Hans Vangheluwe, presents a case-based reasoning approach to efficiently reuse experimental data, potentially saving time and resources in system design.
The researchers highlight the growing importance of experiments in MBSE, particularly in digital engineering and early validation and verification processes. As systems become more complex, managing experimental configuration metadata and results becomes crucial for accelerating overall design efforts. The team identified a key challenge: determining when previously performed experiments can be reused to answer new questions, thereby avoiding redundant, time-consuming, and resource-intensive tests.
To address this, the researchers developed a framework that intelligently manages experiments on both digital and physical assets. The framework leverages case-based reasoning combined with domain knowledge to decide whether an existing experiment’s results can be applied to new, potentially different questions. This approach aims to save engineers time and effort by reusing relevant data without the need to set up and perform new experiments.
The team validated their approach using an industrial case study focused on vehicular energy system design. This practical application demonstrates the framework’s potential to enhance efficiency in real-world engineering scenarios. By intelligently reusing experimental data, the framework could significantly reduce the time and resources required for system design, making the engineering process more agile and cost-effective.
This research underscores the importance of intelligent data management in MBSE. As the maritime industry increasingly adopts digital engineering practices, similar frameworks could be adapted to optimize ship design and maintenance processes. For example, in the maritime sector, where systems are highly complex and experiments can be costly, this approach could help streamline the design and testing of new vessels, ensuring that valuable data is reused effectively. The framework’s ability to integrate domain knowledge with case-based reasoning could also enhance decision-making in maritime engineering, leading to more efficient and sustainable ship designs.
The researchers’ work provides a robust foundation for future developments in MBSE, particularly in industries where experimentation is both critical and resource-intensive. By focusing on intelligent reuse of experimental data, the framework offers a promising path toward more efficient and effective system design processes. Read the original research paper here.