Elevating MBSE with SysML: Jama Connect® and CATIA Magic in Action
What happens when Jama Software®’s Traceable MBSE™ combines with Dassault Systèmes’ enterprise and system architecture modeling expertise in systems engineering?
This powerful and intuitive integration between CATIA/Cameo Systems Modeler and Jama Connect® aligns business and engineering, bridging the gap between requirements management, system architecture, design, and product management.
This engaging webinar features Cary Bryczek – Jama Software and Saulius Pavalkis – Dassault Systèmes as they discuss the intersection of this technology and give a live demonstration.
What you’ll gain:
- Key trends shaping the future of MBSE across the aerospace & defense industry
- Challenges keeping Systems Engineers up at night
- The impact of Jama Connect Traceable MBSE in defense applications
- How Cameo Systems Engineering enhances system architecture
- A live demonstration of Cameo DataHub’s integration with Jama Connect
Don’t miss this opportunity to see how this integration can transform your MBSE approach, driving success from concept to deployment.
Below is an abbreviated transcript of our webinar.
Cary Bryczek: To kick things off, I want to set the stage with some trends across the aerospace and defense industry that we’re seeing. I’ll talk about how those trends are creating challenges for chief engineers and describing what keeps them up at night, then I’ll set the stage for Saulius’s presentation by showing you what Jama Connect’s Traceable MBSE looks like and how it’s designed to solve those challenges. Saulius is going to take you on a deeper dive to show you how system models and Jama Connect interoperate.
So in the aerospace and defense industry, we are developing a new system that has complexity that far exceeds commercial product development. For example, the FAA’s program to develop the Unmanned Aircraft Traffic Management system involves not just a pilot and drone, but is designed to enable autonomous and semi-autonomous operation of multiple air systems, including the passenger and cargo delivery, in a really tightly integrated civil airspace. The elements in blue on the diagram are all distinct systems of their own, and the new traffic management system needs to integrate communications and data across all of those systems to provide this new capability.
In the highly constrained environment of outer space, for example, NASA’s Cislunar and I’m pretty sure the Artemis programs are focusing on the operation and survivability of autonomous systems. To develop a space system, NASA doesn’t do this in their own silo, but they have lots and lots of contracts and companies that they work with deliver parts of the system, just like in the DoD. For example, you have Blue Origin. They are developing a friction stir additive manufacturing part of the system in partnership with Langley, right? You have Redwire out of Erie, Colorado. They are developing another in-space manufacturing system. You have Canopy out of Denver. Colorado seems to be a popular place for space. They’re developing low-cost reusable thermal protection systems, right? And there’s really dozens more. The Cislunar and the Artemis programs are developing ecosystems and the ecosystems of those partners, right?
In the government agencies and aerospace and defense companies, they’re always evolving their strategies to be able to deal with this high degree of complexity to help streamline their engineering processes. For example, the DoD, they have published a new adaptive acquisition framework. So even not just in the engineering parts of it but the acquisition parts of it as well, there’s a new framework. This particular pathway is intended for large-scale traditional hardware acquisitions to help facilitate rapid and iterative delivery, like what the software capability programs are doing.
In 2018, we had the Digital Engineering Strategy outlining a vision to modernize how DoD designs develops, delivers, operates, and even sustains systems, right? By connecting people and process and data and developing these end-to-end digital enterprises.
The International Council on Systems Engineering, their Vision 2035 is intended to guide and inspire the strategic direction of systems engineering for the global systems engineering community, right?
The DoD’s Systems Engineering and Architecture group within the DoD itself is focusing on modernizing the systems engineering practice and they’re leveraging the capabilities coming out of SERC and MOSA to build systems that can be upgraded to incorporate new technology and respond to emerging threats, right?
With this new modernization of the SE approach, and now I know this is sort of an eye chart, you guys can look at it after the fact, the DoD has moved away from visualizing its process using that shape of the V model in favor of what more realistically takes place from a process standpoint, which is that modern systems engineering is highly cyclic in nature. Now, the outermost ring is as close to what the old V model, where concept definition is in the upper left, moves to system definition through architecture and design, over to V&V, and back around to start the next cycle. What’s important is that there’s a strong emphasis on measuring not just the system being built, but the process to build that system and that data and models are at the heart of it all. To the fullest extent, models should be used in favor of documents and data should inform the decision-making.
There really is a challenge to using a data-driven approach in the models. The DoD, I love this quote, “There’s a lack of an integrated approach to implementing systems engineering focus areas that’s creating a delay in implementing the digital transformation, which is necessary to ensure relevant guidance, skills, and training are available to deliver a disciplined approach to acquiring a weapon system.” Continuing to use legacy tools and approaches is what making integrated approaches gravely difficult. What’s necessary is to take a federated approach to data across the tool ecosystem and use tools with robust APIs, modern architectures that are standards-based. An MBSE approach requires an integrated approach to connect that system model’s architecture and requirements to program teams and software and hardware teams. It doesn’t mean using a siloed system modeling tool and expect those teams to be able to consume and understand that model. In fact, kind of what I hear a lot is, “How do I achieve the benefits of MBSE when no other engineers can access model parameters they need to use to make downstream decision-making, and how do I make decisions on tests and other things that’s downstream from the system model?” I hear that quite a lot.
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Bryczek: Those with technical oversight and responsibility for program success who are executing MBSE or even just traditional systems engineering commonly raise these following questions. This is what I think keeps chief engineers up at night. “How do I know if the architecture and system requirements are satisfying all the needs?” “How do I know if a change in the architecture will impact those needs?” “How do I know if a change in the architecture will impact hardware or software teams?” And, “How do I streamline model design reviews?” I have a fourth one, too, “How do I detect unallocated systems architecture and requirements that sort of transcends the system model area and goes into the software models and the hardware models?” So that’s another favorite that I have.
So these questions really, we think, can be answered using what we term Traceable MBSE. The reality at most companies is that the end-to-end systems development processes is fragmented into domain-specific tools and spreadsheets that really don’t have a lot of collaboration or any, and this leads to fragmented requirements traceability and requires significant manual effort through emails and meetings and maybe even luck to try and prevent delays, defects, rework, cost overruns, right? Most companies have come to accept this situation as an unchangeable reality given the lack of a single platform to enable this entire process, nor a method to integrate spreadsheets and desktop tools. Using Traceable MBSE, the system model in the modeling tool is joined with the Jama Connect model. Jama [Connect] is continually calculating traceability and coverage and provides scores that can be used to identify high-risk areas that can be drilled into to determine corrective actions, the system model can detect those changes, and the modeling engineers can take corrective action.
Keep in mind that model-based systems engineering is more than using the power of SysML. It is powerful. Systems engineering’s superpower to enable digital transformation comes when it’s able to connect to the entire development effort and facilitate software and mechanical teams with the ability to align their efforts to the system model, systems engineers being able to manage the state of development across the disciplines and automatically identifying risks through all stages of development.
So let’s maybe see what this looks like in Jama [Connect.] This is Jama Connect in a web browser. I’m showing a Traceable MBSE project for development of a cube set. In it, I’m managing the end-to-end development of the program mission goals and objectives, stakeholder needs, concept of operations, system requirements, subsystems, software and hardware requirements, architecture, safety risks, verification and validation, and even user stories from Jira. Jama [Connect] is going to provide that measurable end-to-end traceability for all of their elements. Their version control and baselines provide design, review, and approval, plus make the data visible onto a series of dashboards.
All the interactions with Jama [Connect] are done in this web browser. Just to give you a little bit of navigation overview, if you’ve never seen Jama [Connect], you can see the data. You can organize the data pretty much however you want. You’re not constrained to how you want to call the data. Want to look inside stuff, you can open up and look inside the dashboards. The series of dashboards can be laid out however you want. You can have multiple dashboards. So this is my main one. I want to see a trace exception dashboard, I’m able to just organize them how I want, surface up that information. And they’re live too, so if I wanted to go and look at what any of these are, show me my objectives, needs, or goals, I can just click on them and it takes me pretty much right to where I want to be.
One of the things that makes Jama [Connect] special is the ability to define a data model for the information that you’re going to be managing in the model or the Jama [Connect] project and define how the traces are related together. And then our Live Trace Explorer™ is used to show real-time progress against expected traceability. So I open up my Live Trace Explorer for this particular project. The Live Trace Explorer is used to show the real-time state of progress of all of the items that are being managed in the system against the expected traceability according to those rule sets. When integrated with system modeling tools, like managing architecture, Jira managing the flow of tasks, using Live Trace Explorer, you can obtain this holistic view of quality across your entire system development and software factory process.
So this left-hand side shows requirements coverage and the right-hand side of the Live Trace Explorer shows test coverage, similar to a V model. Here you can see the program system-level requirements. So here we scroll down, we have the program system level requirements and all of the relationships established for traceability. This is based on the project’s traceability rule set, remember? Your project might use different names than what you see here. You’re not really constrained to using what comes out-of-the-box Jama [Connect] at all.
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Bryczek: The Trace Explorer in the upper right, this Trace Score™ shows an overall traceability score for your project that you can use to gauge how quality changes, hopefully improves over time. So all of these metrics are real-time from what’s happening right now, and so 64% traceability, this is probably maybe early to midstream in development. We’re still seeing people still establishing traceability, right? But by increasing your traceability score, we really hope to reduce the risk of defects, cost overruns, and delays.
So what about some of those questions that keep chief engineers and program managers up at night? What about the ones that we were asked about? So question one is, “How do I know if architecture and system requirements are satisfying all the needs?” This is tracked in our Live Trace Explorer as a percentage of coverage between the linkages. So here we see a 55% coverage between these stakeholder expectations, which we have 36 stakeholder expectations, so 55% traceability established so far between those. And we only have, and if you scroll down, if you want to see what the architecture is, the architecture, we only have 50% coverage between the architecture and requirements.
So what about, “How do I know if a change in architecture is going to impact testing”? You can really easily see that here, the changes between what’s happening to testing. You can even see a percentage of the suspect changes. So right now, I might’ve already changed some of the requirements of your architecture. 11% is showing suspect. Right now, I don’t have a lot of test plan coverage. Still kind of in the early phases as well.
What about the third question, “How do I know if a change in architecture will impact hardware or software teams?” Right? Again, you can easily see any of the downstream traces to different things. And this is live, too, so if I wanted to see exactly, show me those objects, I can just click, it’s all interactive, and see exactly what the traceability between architecture and system requirements look like. I want to add more information to the view, maybe I want to see what the rationale is or the status, I can add that kind of view really super easily to my view. Jama [Connect] is really designed to make it easy for anyone to come in, understand what’s going on in the program, click and see instant traceability based on what you’re looking at.
So another question is, “How do I detect unallocated system architecture and requirements?” Unallocated activity can be used by running a query. So I have a filter that says, “Show me all of the unallocated architecture.” So I have four architectural elements that have no traces for requirements, and if I turn my trace view on, you can see these are just standalone objects. There’s no traceability either up or downstream to requirements of any kind. We really want to make this as easy as possible, as powerful as possible for people to measure in real time what does their traceability look like, how do I use traceability to effectively enhance the process and remediate actions before they might possibly happen.
So in summary, as systems development continues to increase in velocity, engineering leaders and program managers really need answers to those really tough questions. System modeling tools alone don’t easily provide that. With Jama [Connect]’s Live Trace Explorer, this is providing that real-time traceability score. Our approach for managing and controlling process is using actual data. Jama [Connect] is really the only one that can provide that holistic view. Very exciting.
And now, Saulius would love to show us how Dassault is connecting Jama [Connect] and CATIA Magic.
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Saulius Pavalkis: So you saw the Jama [Connect]site. Now we’ll talk about the integration part with CATIA Magic leading SysML and MBSE solution for system architecture. So what is the reason, what is the differentiator, why it is the leading solution? So this was first product to support SysML v1, and pretty much all the versions from that was supported with the complete standard, following already for almost 20 years, as we can see, of the SysML appearance. Now we’ll be working on SysML v2, which will be another evolution and, again, the same goals. We became de facto standard for the many different project types in the industry, and pretty much the quality and scalability of the product and strict following of the standard enabled that. You can’t support all the big clients with the custom solutions unless you will follow some standard approach which allows to customize for each specific one later on.
And that brings us to our core values. So it is completely open. Also, as we will see here also from OpenAPI side, because that enabled us integrate in the proper way with the requirement management solution, Jama Software.
Standard compliance, another big deal because if you support the standard, maybe it is a bit harder than to integrate specifically for specific needs, right? But once you follow that, it’ll apply for all the different purposes, plus it will be clear which part of the integration needs to be updated with the standard update and with the tool development, which is not the case when you don’t follow the standards, right?
Efficiency and user-friendliness, ability to customize, and that’s like one of the most significant values because again, if you follow the standard, you get the 90% for the industry needs, but then you need to customize for specific industry, like what type of the data you want, as you saw in the Jama [Connect], you can select data set, what’s needed for specific project, have ability to create your own data set and then synchronize only on that data set and work on that model.
We support mostly system engineering community needs, and that is pretty much 90% or something of the product, because standard compliance is one thing, but then actually system engineering to enable better results with the model than PowerPoint, better tables and data management, and Excel is the key differentiator when you want to work with the model sufficiently.
The big part is continuity to disciplines. As you saw, traceability is big part of the Jama Software solution. Same for us, we dedicate most the attention for these integrations with the rest of the ecosystem. This is perhaps one of the most popular integrations, maybe the most popular integrations which we have. But in general, these are disciplines in engineering and analysis.
And also system engineering life cycle, as Cary mentioned, design reviews, this is very important process. Every organization goes through it and also in collaboration with suppliers, and that’s technically insight but also other processes which requires formal process with the approvals and baselines.
So talking about this integration specifically, we are using DataHub as integration framework. What are the highlights? It comes as a plugin actually for CATIA Magic. It’s built in in CATIA Magic. And this integration is also not an exception. It’s using this major integration framework, which is mostly for requirement tools integration. One of the most used integrations which we have is actually requirement management tools, and the most useful integration, used integration likely will be Jama Software integration from requirements management side. It provides similar experience for all the integrations and already set up operations which are common for the users, not to expect some surprises, but it is also redesigned to be more optimal, more user-friendly, and supports the standards like OSLC v2, but in our case, we are using direct API to Jama Connect, which is always the best case when you have ability to leverage that, and that shows again the openness of Jama Software and CATIA Magic.
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Pavalkis: The workflow is very simple, so pretty much you connect the data source to Jama [Connect]. Jama [Connect] can be on the cloud, on premises. You select the scope for the synchronization. We support only one operation, copy and synchronize, which is by far the most popular one from all the experience we have. We then select the mapping based on the data sets selected, you know, could be new requirement types, could be new relations and so, and then we synchronize, first of all, by copying the data, but later on by checking changes, seeing the changes available and acting on those changes, synchronizing and acting on those changes with suspect links in our site. And also, on top of that, we support diagrams as an image interchange, which is a big deal because then you can actually work independently without all these requiring to see another solution for the part of the data.
Now, when we work together, what are the key connection highlights? So we support advanced authentication methods, simple authentication, and OAuth 2.0. On project selection, we select the data which will be available, what type of data will be available, and that data will allow us to map just to those elements from Jama Software type and see them synchronized to CATIA Magic using DataHub. As you can see here, we have this Cameo DataHub view in CATIA Magic, Cameo, and it is based on the same selected data in Jama Software for the project, right? And then you can see it with the icons with the exact representation that allows you to have the seamless interface.
The leverage, the same dedicated UI for identifying changes, what’s new, what is modified, move, delete it out of scope, and this allows us to see the change before synchronizing, so you can even apply element-by-element synchronization and, based on the direction of synchronization, you can choose one or another way to synchronize, which is always good to choose in advance not to have the conflicts on the authoritative source of truth.
We have number of items, type of elements in Jama Software which we synchronize. You can see the full list. It’s far more than just requirement, the different other types of attachments and so on. We allow, as I said before, to import the images to CATIA Magic and from CATIA Magic export diagrams as images to Jama, which allows you to review the diagrams in Jama Software and also see the architecture views from Jama Software and CATIA Magic and act on them.