Model-Based Systems Engineering (MBSE)
Model-Based Systems Engineering (MBSE) is the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases[^c1]. It represents a paradigm shift from document-centric systems engineering, where system specifications are scattered across text documents, spreadsheets, and diagrams, toward a model-centric approach in which structured, interconnected domain models serve as the primary means of information exchange and the authoritative source of truth. In traditional engineering, a document is a static, standalone artifact requiring manual updates, while a model is a dynamic, interconnected representation built on structured data that maintains relationships between system elements automatically[^c5].
The term "model-based systems engineering" was first prominently used by A. Wayne Wymore in his 1993 book of the same name. The SysML Partners consortium later adopted the term between 2003 and 2005, and the standardization of SysML in 2006 established a common language for MBSE. In September 2007, INCOSE introduced its MBSE 2020 Vision, which stated that MBSE "is expected to replace the document-centric approach that has been practiced by systems engineers in the past"[^c2]. The INCOSE MBSE Initiative was launched at the 2007 INCOSE International Workshop to promote and institutionalize MBSE practice.
INCOSE's SE Vision 2035 declares that "The Future of Systems Engineering Is Predominantly Model-Based"[^c3], envisioning virtual models using digital twin-based model-assets, cloud-based global collaboration, and unified modeling and simulation frameworks. However, as of 2025, INCOSE's envisioned state has not been fully achieved[^c4]. MBSE adoption faces challenges spanning technical, cultural, organizational, and educational dimensions, including tool interoperability issues, workforce competency gaps, and organizational resistance to change. Adoption spans aerospace, defense, automotive, rail, manufacturing, and other sectors, with organizations reporting quantified benefits including reduced development cycle lengths, earlier detection of design flaws, and improved cross-disciplinary collaboration.