The Coronavirus pandemic may have driven a stake through our traditional ways of doing business, but new systems engineering practices such as Model-Based Systems Engineering (MBSE) and DevOps offer an effective approach to developing complex systems in a time of social distancing and remote teleworking. The decentralized workplace offers at least two challenges:

• Communication – Communications deficiencies lead to schedule slippage and cost overruns. Without formal and informal face-to-face contact, systems engineering workflow depends on real-time communication through tools such as Zoom and Slack, as well as project management tools such as JIRA providing common access to progress, status, and assignment of responsibility. We can ease workflow between remote users by automatic notifications, updates and requirement verifications.
• Access/Protection– We need to selectively supply access to users outside protected physical and digital environments. To do their job effectively, team members need to be able to find information stored in multiple repositories, not just their own primary tool. This may involve searching extended chains of traceability without exposing information unnecessarily.

To address these challenges, our systems engineering environment must be

• Integrated - all the engineering models are part of a Digital Thread that users across the project lifecycle can access to find the information they need,
• Distributed – users can access the Digital Thread from multiple locations and portals while maintaining the necessary security, and
• Asynchronous – not all team members maintain the same work schedule, particularly under the disruptive conditions of a pandemic. They must be able to pick up their work on short notice, perform their task, and push it back into the workstream with minimum direct coordination with other team members.

The combination of MBSE and DevOps offers a promising solution to these challenges, not only for the short term but in the long term evolution of our discipline.

The core of MBSE is the provision of a single source of truth about the system in the form of a digital model. For complex cyber-physical systems, this consists of an integrated set of models including requirements, architecture, hardware, and software design, simulation and analysis, and others, which we will refer to as a Digital Thread for short.

DevOps consists of facilitating and automating the transfer of information during system development to enable continuous integration and development, giving rise to faster and more effective adaptation to market/threat environments. In software engineering where this is increasingly practiced, this often includes automated test, build, deployment and feedback processes.

MBSE and DevOps have a great deal in common. They are both digital in nature. Moreover, the data is structured, e.g. a model, so that functionality can be exercised with fine granularity. Perhaps most importantly, both work to break down the barriers between job functions and organizations, involving both technological and cultural change for adoption.

While software is an increasingly important component of modern systems, our interest is in the more complex challenge of cyber-physical systems with both hardware and software. The number of tools and disciplines involved is much broader. The deployment of these systems not only involves their physical transport, but also the deployment of auxiliary systems for operations, refueling, maintenance, and training. Finally, we must make a distinction between the building of the digital system model and the building of the physical system, which is less distinct in software-only systems.

One way to view the problem is that MBSE, through the Digital Thread, provides the structure and DevOps specifies the processes applied to that structure.  With such a perspective, we may layout the environment as in Figure 1.

Figure 1 MBSE-DevOps Interaction for Cyber-Physical Systems

In order to implement this concept in a useful fashion, there must be a digital platform (or platforms) that deliver a variety of services:

• Connect data in different models
• Access data through those connections
• Transform data between modeling domains
• Store connection data in a configuration-managed repository
• Supply connection data for documentation, analysis, and visualization
• Validate connected data in the system model for consistency and completeness
• Verify system performance through simulation, test and analysis
• Detect and publish changes in connected data
• Update connected data

and apply consistent workflow management and automation to all of these services.

In the next three parts of this blog series, we will illustrate these ideas in creating a reference model of a medical ventilator. Part 2 will describe the SysML model, which will be available for download with that post. Part 3 will describe the creation of a Digital Thread for that project using Syndeia™ from Intercax as part of an integrated design environment with SysML, PLM, ALM, requirements, test, and simulation software tools. The final part will demonstrate how Syndeia can supply DevOps-like services to the development of this complex cyber-physical system.

Related posts:

• Systems Engineering in a Time of Social Distancing | Part 1 (this post)
• Systems Engineering in a Time of Social Distancing | Part 2a
• Systems Engineering in a Time of Social Distancing | Part 2b
• Systems Engineering in a Time of Social Distancing | Part 3
• Systems Engineering in a Time of Social Distancing | Part 4