An MBE Manifesto
In April, 2018, a small group of systems engineers, scientists, and researchers assembled at
the 19th International Federation for Systems Research (IFSR) Conversation in Linz, Austria,
to use systems analysis methods to model a Systems Engineering approach that would
optimize modern model-based engineering methods and tools.
One result of that Conversation was a manifesto on model-based engineering. The purpose of
the manifesto is to summarize and make explicit key values and principles motivating the
transformation to model-based engineering (MBE). While we started with the concept of
model-based systems engineering, we now feel that the values and principles in the manifesto
are relevant to all engineering disciplines. We will present the manifesto at the upcoming 2018
INCOSE International Symposium, with the specific intent to seek feedback and input from
across the INCOSE community.
The IFSR Conversation
The International Federation for System Research sponsored the Nineteenth IFSR
Conversation, this year in Linz, Austria. Conversations were introduced by Bela H. Banathy
around 1980 as an alternative to the classical conferences. In a Conversation a small group of
scientists meets for several days to discuss in a self-guided way a topic of scientific and social
importance. No papers are presented; the participants discuss their topic face-to-face. Teams
of four to eight members meet for five days to develop conceptual models and intensify their
understanding of the session topic. After the Conversation the teams document their findings
in the proceedings of the Conversation. The manifesto is the output from the sessions that
discussed Data Driven Systems Engineering Approaches at the 2018 Conversation.
Data Driven Systems Engineering Goals
This Conversation session explored the application of analytic and modeling techniques to the
Systems Engineering problem space. Systems Sciences can be described as the application
of a systematic approach (systems thinking) that includes tools and techniques from systems
analysis, data analysis, computer science, efficiency/ecology, human factors, systems
dynamics, and complexity theory towards topics in nature, society, health, and engineering.
The application of systems science toward engineering the total system (Systems
Engineering), particularly the analysis of high fidelity data to drive engineering decisions in
complex systems, systems of systems, and massively complicated systems is of particular
interest. Research shows that many of the systems we take for granted, such as automobiles
and airplanes, and the infrastructures that support these systems (system of systems) are
becoming increasingly more complicated. The automobile of today contains over a million lines
of code (LOC); an airplane can contain over 10 million LOC. At the same time, economic and
political pressures are being applied to drive down cost and reduce schedules. Systems
analysis and data analytic methods are being used effectively in many business use cases.
Systems Engineering is held responsible for the understanding and control of complex
systems.
