Digital engineering has become an important strategy in the defense domain for a faster, more efficient route to new platforms and systems. By constructing digi...
Once we think we've got it right, then the customer can decide, yep, we're going to build a prototype. That compresses the schedule. — Pat Meharg, chief architect for model based systems engineering, Noblis.
Chief Architect, Model-Based Systems Engineering, Noblis
The model-based systems engineering return on investment, I believe, is we can build a better system, and have better understanding earlier in the process. We can actually decrease the time for delivery of developing that system. — Pat Meharg, chief architect for model-based systems engineering, Noblis.
Chief Architect, Model-Based Systems Engineering, Noblis
Digital engineering has become an important strategy in the defense domain for a faster, more efficient route to new platforms and systems. By constructing digital representations of a system that includes all the characteristics it would have as a physical entity, digital engineering saves much of the costs and time required to build and test physical prototypes.
Achieving digital engineering, though, requires mastery of a crucial intermediate step known as Model-Based Systems Engineering. Pat Meharg, the chief architect for Model-Based Systems Engineering at Noblis, said model based systems engineering both builds on traditional engineering and provides the next step to full digital engineering.
The difference, he said, is that digital engineering encompasses the activity or business processes of systems development as well as the engineering piece itself.
Meharg said it’s important to understand that Model-Based Systems Engineering is far more than traditional CAD, or computer-aided drawing.
“CAD is also a part of that digital engineering transformation as well. But we’re moving from paper based documents in the past, to digital artifacts that we can share among engineering disciplines.”
Rather than building on CAD though, Model-Based Systems Engineering is what Meharg called a natural progression of systems engineering itself, which has its roots in the 1950s. It sought to look holistically at the collection of parts that make up systems, rather than part by part. Today, the Model-Based Systems Engineering approach models complex collections of interrelated part and the software that controls it all. In fact, software systems themselves, no less than physical systems, benefit from Model-Based Systems Engineering.
Meharg said Model-Based Systems Engineering “also includes the mission or the operation of the system, what do you use it for? How does it behave in the real world? How does it interact with the human beings that operate those systems?”
Model based systems engineering, like all engineering, starts with requirements. Meharg said an advantage of Model-Based Systems Engineering is the way it combines the various components’ requirements with data on the way they interface. In the past, the performance as a system was difficult to gage because requirements and interface data were only loosely coupled. The digital twin – the principal artifact of Model-Based Systems Engineering – incorporates this data so that engineers can test performance and potential pitfalls without a physical prototype.
“In a model based system engineering approach, our requirements are also tied to those interfaces, or to the behavior or the structure,” Meharg said. Data on thermal or mechanical effects, for example, might creep into a system that weren’t apparent from drawings. That means the various engineering sub-disciplines must collaborate in a peer-review environment, to ensure all of the data required by the model actually gets into included in it.
Then, Meharg said, when the engineering and program teams decide the digital twin represents a fulfillment of the requirements, they can proceed to a prototype that’s far more mature than they might have built under traditional engineering.
“So instead of building many, many prototypes, we do it in that digital environment,” Meharg said. “And we can do it very quickly. Once we think we’ve got it right, then the customer can decide, yep, we’re going to build a prototype at this point. What that does is, it compresses the schedule.”
Meharg said a large and competitive base of Model-Based Systems Engineering tools exists that let engineers design and visualize systems using a common language and architecture known as SysML. He estimated it would take an engineer proficient in CAD a solid year to become proficient in Model-Based Systems Engineering tools. Noblis itself provides training in MBSE tools for federal organizations – and there are many – pursuing digital engineering.
And while Model-Based Systems Engineering is what Meharg called hardcore engineering at its essence, its output can help engineers answer program, acquisition and business questions.
“It’s on the system engineers to draw or build that diagram to the level of abstraction needed for that decision maker,” he said. “The model based systems engineering return on investment, I believe, is we can build a better system and have better understanding earlier in the process. I can actually decrease the time for delivery of developing that system.”
Done properly, he added, Model-Based Systems Engineering can take engineers to many levels of abstraction, including system-to-system performance and lifecycle performance.
“We’re building systems that we know in the future, we’re going to have to go back and revisit and change,” Meharg said. “And the model gives us a place to collect information that will travel with the physical system throughout that lifecycle, until we dispose of it.”
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