In the second episode of a recent series on the Industry Forward Podcast, Dale and I sat down with Mike Crist and Scot Morrison to further explore the shift-left and how aerospace and other companies are adapting to the rapid shift towards software-defined product development. You can listen to the episode in the player, or read a summary of the second part below.

To begin part two, Mike shared his philosophy on managing complexity in large systems: “Controlling the interface boundaries really helps us to decompose that system… Once we establish that contract, if we also add in the functionality that’s expected to be exposed, now we can start bringing in compatibility with hardware and software.”

He compared unmanaged complexity to an infection that can spread through a system, creating unexpected behavior. By defining and controlling interfaces, organizations can encapsulate complexity and prevent it from propagating across domains.

SysML V2 Supports Digitalization and Shift-Left

The conversation then turned to SysML V2, the upcoming standard for systems modeling. Crist explained that while many see it as an evolution of SysML V1, Siemens is taking a broader approach: “We’re using SysML V2 as a technology… not just to describe architectures, but as a payload for data exchange and interoperability across multiple topics.”

He emphasized the benefits of machine readability and automation: “V2 opens up a lot more potential for machine-based interaction as well as cross-domain and cross-industry interaction.” Dale added that the standardization of these interactions will make it easier to apply artificial intelligence once companies have well-structured, connected data.

Digital Twins and Workflow Integration with SysML V2

Scot Morrison highlighted how SysML V2 is already influencing Digital Twin development: “We are seeing it in system-level Digital Twin modeling. It’s a much richer language that allows us to describe multi-behavioral, multi-physics systems.”

He noted that the standard improves interoperability between tools, enabling more comprehensive workflows for system-level design and analysis. This integration supports the creation of a connected digital thread, which is essential for a comprehensive Digital Twin.

Crist reinforced this point by describing Siemens’ progress: “We’ve got that threaded requirement set now integrated and interacting with the V2 repository. As those requirements and parameters are being defined at the system level, you can continue that thread into verification in a threaded fashion.”

Dale summarized, “Once you have those requirements threaded into all the different models that make up the Digital Twin, now you’re actually able to do the co-development of hardware and software.”

Big MBSE vs. Little MBSE

The discussion also addressed the maturity of systems engineering practices. Crist observed that many companies are still focused on what he calls “little MBSE,” which emphasizes architecture and requirements but stops short of full lifecycle integration.

“Our approach is one of the big MBSE that says the practice of systems engineering doesn’t start or stop with requirements and architecture,” Crist explained. By embracing big MBSE, companies can leverage SysML V2, Digital Twins, and automation to manage the entire system lifecycle.

The Role of AI in Systems Engineering

Artificial intelligence was another key topic of our conversation. Crist cautioned against limiting AI to text-based tools: “That’s all the rage right now, but we’ve already got AI-enabled technologies for systems engineering.” He cited Siemens’ Simcenter Studio as an example, where AI can generate valid and viable system topologies based on requirements, then refine millions of combinations down to the most promising options, vastly accelerating the initial architectural definition of a system.

To conclude part two, Dale focused on how these capabilities are essential for companies aiming to manage complexity, accelerate development, and deliver innovative products in an increasingly software-driven world.

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Siemens Digital Industries Software helps organizations of all sizes digitally transform using software, hardware and services from the Siemens Xcelerator business platform. Siemens’ software and the comprehensive digital twin enable companies to optimize their design, engineering and manufacturing processes to turn today’s ideas into the sustainable products of the future. From chips to entire systems, from product to process, across all industries. Siemens Digital Industries Software – Accelerating transformation.