Many in the automotive, electronics and aerospace industries will be familiar with the MBSE (model-based systems engineering) methodology. Previous implementations and toolsets have been used in these industries for decades as an evolution of systems engineering, but a modern MBSE approach works very differently. Perhaps the most important difference is the way in which information about the system is captured, stored and communicated. Instead of diagrams, data is stored centrally with secure links to other relevant information. This results in the system architecture or roadmap from the development process through to service operation. The various processes in product development are supported by digital workflows that connect the decisions and work made in a domain tool with the digital twin. This "single source of truth" makes the data more easily accessible for multidisciplinary product development.

System architecture is the most important aspect of model-based systems engineering. Its main function is to manage development processes across the entire business and value chain. Its creation is the starting point of every project. The system architecture becomes the definition of what the market needs and the blueprint for development. The information in a system architecture can be quite extensive, for example regulatory requirements, manufacturing constraints of the existing infrastructure or even trade-off studies. The effective coordination of this information requires a standardized methodology. Modeling languages such as SysML and modeling tools such as System Modeling Workbench are therefore essential for system engineers. Traditionally, every decision, analysis and process within development was assigned to a small group of systems engineers who passed on the knowledge to the various groups. But the increasing interconnectedness of today's products makes this a difficult endeavor. Instead, companies are beginning to democratize the process through digitalization. Relevant decisions are passed on to the multidisciplinary groups and passed on to everyone who is affected by the changes.

Communicate effectively

A robust system architecture is very important, but without good communication there is no smooth collaboration between departments. Communication has improved dramatically in the MBSE workflow in recent years and will be further optimized with SysML v2, the next generation modeling language for systems engineering. Most innovative industries still work with digital documents to communicate the understanding of their complex systems. However, there is a disconnect between the desire for a reliable common thread from concept to service and the existence of one.

SysML v2 aims to improve communication for MBSE methods between the mechanical, electronic, electrical and software domains. Previous implementations could not model many of the complex systems required for aircraft or automobiles because the modeling language is based on the Universal Modeling Language (UML), which was originally developed for software development only. Due to the lack of native functionality, OEMs and design offices were forced to buy and create custom extensions to SysML to fill the gap. However, this defeated the purpose of a standardized modeling language. The goal of SysML v2 is to remove the limitations imposed by the UML legacy and incorporate a syntax that allows it to handle the models of system architects and organizations.

Downstream applications

Communication is important for creating a precise system architecture, disseminating it within an organization and thus mapping development. It also enables the reuse of the information that these models contain. Downstream reuse is one of the most difficult benefits for an organization to define, as it can occur in a very wide range of applications. One example is the reuse of software functions to reduce code complexity. The ultimate data flow can vary widely, but using system architecture to plan these use cases and optimize processing greatly improves the effectiveness of networked systems. Downstream data applications can also influence the more business-oriented areas of product development. For example, CAD data from design can be used earlier in the design cycle to create marketing materials.