Model-Based Engineering: Revolutionizing Systems Design

There is no denying that engineering complex systems poses an immense challenge. As technologies advance, products across a variety of industries incorporate more software, and integrate more connectivity than ever before. This demand therefore requires systems engineering teams to manage exponentially greater complexity. Traditional document-driven approaches simply cannot scale. We need a better way to architect, design, analyse, validate, and integrate the myriad of components that underpin modern systems architecture.

This is where model-based engineering comes in.

Model Based Engineering, or MBE as it is more commonly known, enables teams to develop ’virtual models’ representing a system’s physical, functional, and behavioural characteristics.

These digital twins act as a single source of truth across the lifecycle, supporting requirements management, design, simulation, testing, integration, and more.

At Arcticus Systems, we are pioneers in model-based methodologies for embedded systems design. For over 25 years, we’ve developed innovative tools leveraging model-driven and model-based techniques to help organisations streamline development and deliver higher-quality products, faster.

In short, model-based engineering is the cornerstone to delivering transformative value.

But what are the core benefits of such a process?

Improved communication and collaboration.

Models provide a common language across disciplines. Hardware, software, systems engineers, and other stakeholders can understand a system’s architecture and behaviour more intuitively through diagrams and simulations rather than static documents. Misalignment risks are reduced.

Early verification and validation.

With MBE, engineers can simulate and analyse system models well before physical prototypes are built. Issues can be identified and corrected earlier, when changes are cheaper. This reduces costly late-stage rework.

Enhanced productivity.

MBE enables efficient reuse of models and automation of repetitive tasks like generating code and tests. Studies show developers are often twice as productive using models compared to traditional hand coding.

Continuous integration and testing.

 Models make it easier to divide up work across distributed teams while maintaining integration. Individual components can be independently modelled, simulated, and verified, then integrated into the overall system model. Automated model-based testing replaces manual processes.

Moreover, there is also much greater support for certification. I’ve written before about mine, and Arcticus’ belief in stronger certification. For safety-critical applications like medical devices and autonomous vehicles, regulatory approval requires evidence of comprehensive testing and design traceability. The rigor of model-based approaches facilitates generating ’certification artifacts’.

At Arcticus, all our solutions are model-centric while remaining pragmatic to deploy. A core part of our technology is the Arcticus Component Model (ACM) – an intuitive modelling structure that is optimised for complex embedded software systems. Engineers model components representing functional blocks and their communications to capture system behaviour and architecture.

The ACM is supplemented by powerful analysis tools leveraging formal methods to exhaustively verify system models. This allows catching design flaws impossible to find via testing alone. We also integrate with other widely used modelling tools. Rather than forcing a proprietary end-to-end approach, we interoperate with existing customer environments to maximise flexibility.

But, and it’s a big but, adopting any kind of MBE to the level that is required means revamping processes, training engineers, and gaining more in-depth experience in the process. The transition can be gradual, starting with pilot projects targeting pain points before expanding across an organisation. That is why we work closely with our customers and academia throughout the engineering journey, leveraging our expertise to tailor solutions fitting their specific needs and constraints.

We are still early in exploring MBE’s full potential. Emerging trends like digital twinning, model-based requirements management, and greater integration of AI into modelling toolchains will further expand capabilities in the years ahead.

I am confident, and will be excited, to see model-based methodologies increasingly become the “new normal” across safety-critical industries like automotive, aerospace, rail, and medical.

At Arcticus, we have been proud pioneers in model-based engineering for over two decades. Our solutions have helped leading companies deliver innovative products shaped by our philosophy of “mastering software complexity”. As MBE gains mainstream adoption, it represents an indispensable pillar enabling engineering organisations to thrive in the face of escalating systems complexity.

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