MBSE Transforms and Simplifies Complex Systems Planning

Modeling the Downstream Impacts of System Changes

NASA used a systems modeling language (SysML) approach, utilizing MBSE methodologies, to create a digital twin of the electrical system on the Orion spacecraft used in the Artemis 1 mission, an uncrewed moon-orbiting flight that took place in late 2022. The Orion chief engineer wasn’t previously satisfied with the technical insight of the project, Hill explains. Such highly complex, systems of systems are prime candidates for MBSE.

“The model captured all of the diagrams that you would expect on an electrical schematic, but with all the systems’ data, channelization information, and connectivity behind it as well,” Hill says. “You can do real-time simulations and connect the model to analytical tools. This is really about how we manage systems information. Instead of managing siloed documents, we’re managing integrated models, data systems, and tools.”

Recently, MBSE workflows helped cut a preliminary design review process from six weeks to three, Hill says.

Models created in an MBSE framework utilize SysML, designed specifically for systems engineering applications. Hill describes those models as “a database in the back end with a graphical front,” which allows project stakeholders to instantly see the downstream impacts of any changes made within the system being modeled.

“If your system is configured properly, you change a variable, such as mass, and push that down through your product lifecycle management tool, down to the responsible engineers who now know they need to redesign a part,” he says.

Real-Time Model Collaboration

Allan Dianic, director of software engineering for systems engineering and architecture in the Office of the Undersecretary of Defense (Research and Engineering), says that MBSE is being used in pockets throughout the federal government, and “those communities are growing.”

“We are starting to bring groups together to develop and advance best practices,” he says, adding that digital models lead to better decisions early in the project design process.

“You can see whether a set of requirements is not achievable and what adjustments you can make,” Dianic says. “With MBSE, you’re doing better, deeper thinking earlier in the process, which saves a lot of time later on.”

By using a model to simulate systems before they’re built, he says, teams can identify errors and inconsistencies when it’s still relatively simple and inexpensive to correct them.

Across the department, teams rely on several graphical and modeling tools that support software and data engineering efforts, including Microsoft Visio and detailed data modeling programs such as erwin.

“As we move to the next phase of integrated and AI-enabled engineering, we are looking to transition to structured data tools that integrate with DevSecOps pipelines and support AI,” says Tim Gorman, a spokesperson for the Office of the Secretary of Defense.

In addition to preventing errors, a model-based approach allows for real-time co-authoring and collaboration. “Multiple groups can look at the model and modify it at the same time, rather than only one person opening a file,” Dianic says.

Technology has become an increasingly important component of practically all Defense Department projects, he says, noting that some have described the F-35 stealth combat aircraft as a “supercomputer with wings.”

“Many of our platforms are software-defined in many ways, and that’s powerful,” Dianic says. “But at the same time, it’s important to be able to model that.”

MBSE Supports 5G Innovation

When the Navy began designing its 5G smart warehouse at Naval Base Coronado, engineers adopted MBSE practices to integrate the work of different tech vendors and promote visibility into all of the complex systems embedded in the facility. As a result, the Navy streamlined approval processes, helping to unlock the benefits of the 5G warehouse more quickly.

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“One of the success stories for this project was the risk management framework accreditation process,” says David Nacario, a model-based systems engineer at Naval Information Warfare Center (NIWC) Pacific and the MBSE lead for the 5G smart warehouse. “We were able to use artifacts directly coming out of the model to submit all of our data for accreditation. That streamlined our accreditation process down to weeks, versus months.”

The existence of a rich digital engineering model also sped up the interim-authority-to-test process, says Andrew Leidy, lead systems engineer for NIWC Pacific’s Enterprise Communications and Networks Division.

“Our IATT was received relatively quickly, in large part due to the really good documentation we had because of the MBSE tools,” he says. “I think the project would have been much more delayed if we didn’t have MBSE in place.”

The 5G Smart Warehouse features a full radio-frequency ID grid, which helps track inventory in real time and prevents spillage (loss due to misplacement of parts or theft). The facility also features automated vehicles that can drive to the location of a part, retrieve containers from high shelves and identify parts with a laser pointer.

Over time, the model will simplify maintenance for the facility and prevent scenarios where upgrades are delayed because engineers can’t find the data they need, Nacario says.

“You won’t have a situation where someone leaves, and then someone else needs their documentation and we don’t know where it is,” Nacario says. “With everything in the model, anyone can access the information they need at any time.”

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