Use MBSE to Optimize Systems

MBSE models can be used to generate impact assessments that help decision makers understand the likelihood of system availability and to optimize maintenance schedules or plan for spares.

Model Based System Engineering advances enterprise reliability, availability, and maintainability.

By Tracy Gregorio, G2 Ops

As infrastructures increase in complexity to become integrated “systems of systems” that include components created and managed by different entities, ensuring their reliability, availability, and overall operational resilience becomes more challenging. The challenge is spreading across industry and public infrastructure with the arrival of autonomous vehicles, smart cities, and multi-directional power grids. The U.S. military deals with this issue in nuclear submarines, aircraft carriers, and other multi-mission platforms. Why and how the Department of Defense (DoD) is adopting a new approach to maintaining mission-readiness can be instructive to reliability engineers working in plants.

To better understand some of the parallels of military work and industry, consider the DoD needs to keep war systems mission-ready in any situation—including when under cyberattack or struck by the unexpected failure of a single component. A nuclear submarine has hundreds of different systems manufactured and integrated by dozens of vendors. As components are switched out it can become very complex to identify what the impact is on actual mission readiness and resiliency. Sound familiar?

The DoD’s new approach goes beyond reliability block diagrams (RBD) by using Model Based System Engineering (MBSE) as the foundation for the design, development, and maintenance of their systems. The DoD is requiring MBSE in new projects such as the Smart Warehouse being created for Naval Base Coronado.

MBSE is a great resource for improving RAM analysis for systems of systems in the military or industry because it operates as a holistic model, interfaces seamlessly with external data sources, and simplifies data management.

Powerful Tool

The MBSE methodology, unlike document-centric systems, defines requirements, handles feedback and edits, and otherwise exchanges information through unified digital models. MBSE models encompass every component and operational thread and can quickly and accurately generate reliability block diagrams (RBD) for any scenario a RAM analyst might envision. Graphical RBDs generated by MBSE help analysts identify and evaluate any failure mode that might impact the system’s ability to serve its purpose.

MBSE models interface with external data using exchange standards such as Systems Modeling Language (SysML) and Unified Modeling Language (UML). The use of these common language standards means that RAM analysts can be confident they are using the latest and most accurate component-level data.

Serving as a central repository for all reliability planners, system designers, and cybersecurity analysts, MBSE models greatly simplify software and data management. Any stakeholder can tap into this database in real time and be sure they are working with the latest information. This helps eliminate inconsistencies and errors that can arise when each group uses their own version of the same information.

RAM Models

MBSE models can be used to generate impact assessments to identify how different risks can affect system availability. This can help decision makers understand the likelihood that their system will be available when it is most needed, and how those scenarios might play out. That information can then be used to adjust RAM strategies to build in back-up plans for resilience, optimize maintenance schedules, or plan for spares.

By identifying potential vulnerabilities, MBSE models can enable the development of proactive mitigation strategies. Systems engineers can start modeling threats early in the design process, allowing them to incorporate mitigation strategies and reduce overall system security risk. By identifying and modeling potential threats, planners can develop tests or procedures to detect and respond before those threats occur. This includes developing a threat-classification system and devising countermeasures.

MBSE can help planners optimize resource allocation, such as prioritization of maintenance tasks, stocking of spare parts, and preventive-maintenance scheduling. Since the MBSE model provides a comprehensive view of the system’s architecture and structure, the costs and impacts of component failures can be modeled in view of their effect on the priorities for the infrastructure. System attributes in the models enable engineers to analyze threats early and optimize resources needed to mitigate.

Models can help determine how well-prepared an infrastructure system is to serve its purpose. Readiness reports can be generated for plant executives. By using Monte Carlo modeling of failure scenarios, RAM strategies can be developed to optimize infrastructure resilience. Engineers can use these models to simulate how the system will perform under different conditions or scenarios. This can drive the best design decisions when it’s difficult or impossible to build physical prototypes, saving time and resources.

Designers can perform trade-off analyses through MBSE models to help create alternative configurations and evaluate them for projections of reliability, performance, and cost. This enables informed trade-offs to be evaluated and selection of the best design approach. These model-based, decision-support tools include trade-off and sensitivity analyses to inform and optimize decisions about RAM based on the infrastructure’s mission parameters and objectives.

MBSE models can be used to simulate and analyze mission scenarios, including downtime for repairs or component failures. Mission planners can create and evaluate different mission profiles, considering factors such as time, resource allocation, and risk. This helps in selecting the most feasible and efficient operational plan.

It’s optimal to create MBSE models from the initial conception of a system, but such models can also be generated for existing systems. In either case, RAM planners will find MBSE to be a powerful tool for ensuring their plant’s complex system-of-systems can meet the needs of its customers.EP

Tracy Gregorio is CEO of G2 Ops Inc., Virginia Beach, VA (g2-ops.com), a certified woman-owned small business that provides cloud migration, model-based systems engineering (MBSE), and security engineering solutions to the U.S. Navy, U.S. Coast Guard, U.S. Air Force, and commercial businesses. She is the Cybersecurity Committee Chair of the Virginia Ship Repair Association and a board member of the Virginia Maritime Association and the Commonwealth Cyber Initiative.