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What is MBSE, and seven steps to its successful adoption

 

Quick Release_ can often shape or influence the processes and systems utilised by our clients. The extent of this is often continent on how established our clients are in terms of processes and systems, but our approach is always to improve and better leverage data to inform impact decision making that accelerates and drives programme efficiencies. 

To align with the best industry practices, different methodologies need to be investigated so we can tailor our solutions to the needs of clients and their unique circumstances. 

One of the most promising is Model-Based System Engineering (MBSE). A system engineering methodology that focuses on creating and exploiting domain models as the primary means of information exchange, rather than on document-based information exchange, MBSE is the formalised application of modelling to support system requirements, design, analysis, verification, and validation activities beginning in the concept design phase and continuing throughout development and later life cycle stages. This provides a framework to drive full requirement traceability across business disciplines and product development, by defining the relevant business architecture, from system modelling to enterprise architecture.

Comparing MBSE with a traditional approach to system engineering – where all information, knowledge and data associated to a system is owned and contained in a set of documents – a “model” acts as the abstraction of the system and single source of truth. It contains “enough” information to represent the system. Different collections of information, each known as a “view”, make up the foundation of the model. The system can be described as a bowl full of views.

For each view, there are multiple stakeholders that should be notified of changes through a communication element known as a “notation”. A notation is communicated through a “spoken language”. This spoken language is completely unique to the specific stakeholder involved and it can be in the form of text, code, visuals, charts, or diagrams. Just like a traditional spoken language, the view can be translated to another stakeholders’ spoken language. 

For the model to be effective, measurable, and comparable we must make sure the views are consistent with each other. The template and the structure of each view is defined by a “viewpoint”. The International Standards Organisation defines a viewpoint as the template or structure for a view and it clearly identifies who are the stakeholders for each view. To assure consistency amongst the viewpoints we rely on an “ontology” which uses a domain-specific language – as opposed to the spoken language used in a notation – to identify and define concepts used in different viewpoints. Ontology combined with viewpoint forms the framework that acts as the blueprint for the model and the information contained in it. A “process set”, is as the name suggests, a set of processes to follow in order to use the framework to form the model. 

Based on this analogy, the framework and the process set are the approach to creating the views that form the actual model. The notation is the visualisation of the model that is unique to the relevant audience of a particular view. 

Deploying MBSE is partly a technical, but first and foremost, an organisational change challenge. Any organisation can benefit from formally implementing such practice, especially when aiming at:

  • Maximising value from data constructs and their utilisation
  • Optimising, or at least improve their understanding of their business model(s)
  • Implementing continuous improvement solutions across data, people, tools, enterprise platforms and their interfaces with the wider application landscape

Typical MBSE adoption considerations include the following 7 steps:

1. Understand the system strategy, goal and boundaries: what are the specific development, manufacturing, assembly, sourcing, commercialisation, support, and other strategies?

2. Map business stakeholders, functions, and interdependencies: how do people collaborate and exchange information; what kind of information, when, in what format, how often, what for?

3. Map communication and usage patterns: how do people and functions communicate, use, and transform data, and connect to share information?

4. Define the relevant data patterns, associated change processes operating governance: what is the modus operandi surrounding the use and maturation of data across the lifecycle of the system or product?

5. Assess the logical data sets, and associated system and sub-system dependencies, and their alignment with the as-realised elements: how are these linked to requirements across the V-model for verification (doing things right) and validation (doing the right things)?

6. Derive process improvement recommendations and value implementation approach: what are the gaps or overlaps to improvement, and what are the required levels of automation, digitalisation, training required to close the gaps?

7. Build the implementation roadmap and drive the plan to execution: what will be the first small steps to get right along the transformation journey?

This article was adapted from an internal Discussion Forum knowledge sharing exercise, convened by Omid Hosseinitabar. The description of MBSE is based off Jon Holt’s contributions, and the deployment considerations and seven steps to adoption coming from Lionel Grealou.

Lionel Grealou is a senior advisor to Quick Release and the Business Transformation Director with Xlifecycle, helping organizations make the most of their digital strategies, PLM-ERP-CRM-MES implementations and business change driven initiatives. With 20+ years of industry experience, Lionel has been instrumental in architecting and leading concurrent teams delivering technology-enabled business change initiatives for engineering and manufacturing OEMs and their supply chain. He initiated and led global client engagements, from small to multi-million-dollar initiatives, covering solution architecture, program management, integration, deployment and operations.

Jon Holt is a leading figure in the world of systems engineering, a professor of Systems Engineering at Cranfield University and a Director for Scarecrow Consultants. He has been working in the field of systems modelling for the last 30 years. An international award-winning public speaker and author, he is the author of seventeen books in the field of applied Model-based Systems Engineering and a Fellow of both the IET and the BCS. Jon also holds a Chair in Systems Engineering at the UK Defence Academy and is the Technical Director of INCOSE UK. Apart from working magic with systems, he is also a professional magician. Commenting on the synergies, Jon remarks, “both require effective people, process and tools; both produce miracles under seemingly impossible conditions and, when done properly, both should leave the audience wondering how you pulled it off!”