Generation of MBSE models from system requirements
George Hwang, Thomas A. Mazzuchi, Shahram Sarkani · 2022
Cancellations of DoD acquisition programs have resulted in billions of dollars of losses annually, which reduces resources for new capabilities. One area identified is a lack of proper requirement scoping, which is prohibitively complex when tracing architectures for large systems. MBSE was developed to address these issues and provide a common framework to rapidly represent, convey, and synchronize information. This research explores the maturity of NLP and ML methodology needed to automatically generate and trace requirements in MBSE models, thus providing the tools to rapidly generate models from requirement documents and reducing the risk of program cancellation due to requirement scoping problems.