Embedded Requirements Engineering
An Introduction to Integrating the ‘R’ into MBSE
Thursday, 12. May 2022 | 20:30 – 21:30 CET
Requirements Engineering (RE) is central to the successful development of complex systems – as is Systems Engineering (SE). Therefore, RE is a vital part of all SE-Methodologies, including Model-Based approaches in MBSE.
In this webinar we will look at the potential of MBSE to integrate RE and make it a truly native component of the development methodology. Using a real-life example, we will explain the process, highlight the differences to a document-centric RE approach and illustrate the benefits for your projects and teams. We also invite you to discuss the potential impact of such a close integration on quality, effort, and cost of RE in your industries.
In this presentation, we will discuss:
The scope and importance of Requirements Engineering
RE in the context of an SE development project
An approach for embedding RE natively within an MBSE methodology
The pros and cons of this approach and its potential impact for your work, e.g. if you are working in a safety critical industry
Who Should Attend?
This webinar is for anyone who is:
Interested in the development of complex Systems
Responsible for or working in Requirements Engineering
Curious about the potential (and promises) of MBSE
Enthusiastic about modelling complexity to make it simpler
Limited spaces available. Save your seat and register now for FREE.
About your host…
Marco Di Maio
Marco has had many roles in Systems Engineering: Professor at a technical university, Consultancy for, and Work in the development of complex systems for large scale research programmes and automotive innovation projects.
- Professor of Systems Engineering at TH Ingolstadt
- Management of projectglobe ltd, London, a consultancy specialising in the support of research driven industry (automotive and robotics) and publicly funded projects (nuclear fusion research).
- Expert in model-based systems engineering and information modelling.
- Head of development for CLOSE, a MBSE methodology based on a semantic graph that integrates Experimentable Digital Twins for reducing cycle times.
- Inventor of a fractal data model that allows for unlimited scalability in managing complex information from any domain.
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