Digital engineering has revolutionized how we capture and use engineering information, which has made models, specifically system models, become central components.
System models are descriptive architecture models that digital engineers typically produce using model-based systems engineering (MBSE) approaches and then capture in the Systems Modeling Language (SysML). These models serve as the authoritative source of truth for system use cases, interfaces, key performance parameters, and functions, including how the planned solution will satisfy system requirements. These models are also the foundation for specialty engineering analysis, integration, verification, validation, training, technical documentation, and sustainment.
Descriptive architecture models are growing in demand, and an increasing number of SAIC's procurements involves providing models as part of the customers' request for proposals (RFPs).
I believe getting a system model right is a key to success, but I also acknowledge how challenging that can be. The language and tools being used to make these models provide modelers with overwhelming options. I call the selection of language and tool options a model style, which can include everything from the type of model elements to use to how a modeler names them.
Most model styles will not violate language rules but rather further restrict what is allowed. This means the automated error checking available in many modeling tools will not enforce model style. So, modelers need to have deep knowledge of the strengths and limitations of the available options to accurately select how to express engineering concepts in a model.
Unfortunately, such deep experience is still rare. A good model style still requires hours of error-prone and tedious manual review, and a poor model style can cripple a model.
SAIC’s Digital Engineering Validation Tool reduces model errors
To improve the quality and functionality of system models, SAIC's digital engineering team developed and released the SAIC Digital Engineering Validation Tool last year to the worldwide engineering community.
Since we launched the free tool, it has been downloaded about 200 times by individuals and organizations, including:
- Aerospace Corporation
- Ford Motor Company
- General Atomics
- Johns Hopkins University
- Lockheed Martin
- Northrop Grumman
- Stevens Institute of Technology
- U.S. Air Force
- U.S. Army
- U.S. Department of Defense
- U.S. Navy
- ZF Friedrichshafen AG
The response was enthusiastic, and we received requests to expand the tool's capability. A member of one of the organizations that used the tool told us, “We are quite impressed! Thanks so much for this helpful tool.”
I am excited by the marked interest in this tool, which is enabling access to better digital engineering models and model styles for the engineering community.
I am likewise excited to announce a major update to the tool. Our team has received a lot of feedback and input to improve its capabilities, and we believe this update will help organizations reach their digital transformation goals even better than before.