Modelling the way with academia and industry

When I visit companies around the world, I see some recurring themes. The systems they are developing are more complex and perform more functions than ever before. These systems typically include combinations of existing subsystems, off-the-shelf components and custom subsystems. The development is performed through collaborations of engineering teams representing multiple disciplines, often in different companies or locations around the world.

These companies have found that their traditional development processes are insufficient to address increasing system complexity, the pressure to shorten time to market and customer demands for more functionality with higher quality. As a result, they have modified or completely transformed their development processes to exploit the use of models. They have stopped relying on paper-based specifications and instead use models as executable specifications that clarify and communicate requirements and specifications. They use multidomain models to simulate the system-level behaviour of their designs. They simulate the subsystems adjacent to their design when the real subsystems are not available or haven’t yet been developed. They automatically generate code for embedded systems from algorithmic models. And they leverage models as test cases and hardware-in-the-loop simulations to test and verify their products and systems. This approach, known as ‘model-based design’, is being used in diverse applications, for large and small projects, with co-located and geographically distributed engineering teams.

Companies are looking to engineering schools to produce engineering graduates with the skills to take full advantage of model-based design. Engineers are asked to think about engineering at a systems level rather than only being a specialist in a single domain. They require stronger modelling and analytical skills, not simply an ability to prototype. And, of course, those newly hired engineers must also have a strong foundation in engineering concepts and mathematics.

But large gaps exist between industry needs and engineering education when it comes to modelling. The consensus across academia and industry about the areas for improvement include: hands-on experience, industry-focused design, computer hardware and software, and mathematical modelling of dynamic systems.

There are also discrepancies between what is needed and what is delivered in university courses. Industry commentators have noted that simulation models for system verification or product design, nonlinear models, real-time models for hardware-in-the-loop verification and experimental system identification methods are useful and valuable skills for control engineers in industry. Yet many university students feel that these skills are not typically covered in entry-level engineering courses.

Some universities have taken significant steps to expose engineering students to modelling and simulation techniques, particularly in controls, signal processing and mechatronics labs. Senior-year design projects are increasingly team-based, not individual, and frequently involve building and sharing models. GM, the primary sponsor of the ChallengeX and EcoCAR student competitions for fuel-efficient vehicle design, considers modelling and analysis to be so important in its own processes that it requires the student teams to model, simulate and analyse their design extensively for a year of the three-year competition before even having access to vehicles.

However, since industry gains leverage by re-using models, not only for analysis, but also for automatic code generation, hardware-in-the-loop simulations and design trade studies, engineering students should learn to use models in these ways as well. Since these models are often multidomain, they can also help instructors to give engineering students a broader systems perspective - for example, to understand the interaction between electronic, mechanical and embedded-system components of a mechatronic system in order to create an optimal system design.

While modelling and simulation are important skills to develop in the engineers of tomorrow, modelling and simulation can also play a role in attracting more students to engineering. Currently, an engineering student’s first semesters are dominated by mathematics and physics. When the student declares a major, the choice is often made without having much of an idea what engineers actually do. More importantly, the student may not even know whether they would like doing what engineers do.

However, if students interact with prepared simulations early in their academic career, they get a clearer idea of the engaging and complex problems that engineers tackle, in the same way that engineers today use models to show management or clients how a design will behave without having to show the underlying complexity. This early exposure is important and models can provide it without the cost, time and complexity of real experiments.

Modelling and simulation, and model-based design techniques that build on it, will have a key role in how students are attracted to the field of engineering, how engineering is taught and how engineers apply their skills to accelerate the pace of innovation.