MECE 460, the senior design project course, is great to teach. In just a few months, I have interacted with people who want engineering students to design new bicycles for children with disabilities, robots for tailings ponds, and even advanced footwear.

Teaching design is also very challenging. Most engineering courses teach structured methods for solving idealized problems of applied physics. Solving problem sets can be lots of fun and very satisfying, because there is a correct answer. Design has no single right answer. Problems are complex, open-ended, and require iterative approaches to developing solutions.

Experiential learning is an ideal way for students to explore the design process, to work as a team, and to come up with designs that will meet (or exceed!) a client’s needs. Most engineering students have little experience this style of learning, and yet this type of work is as close to the way that engineers work than the structured methods for solving problem sets of idealized physical systems.

Design teams tackle problems that are too complex for individuals to solve in a single term. For this reason, a team must form close working relationships and work effectively immediately, with both common purpose & division of labour, which demands good project planning & close coordination. The students have to work with a client, who may or may not have a clear idea of how the solution might look. (It’s generally more difficult to work with a client who has a fixed idea of what the design should be, because this limits innovative thinking.) Engineers have to be vulnerable to new ideas.

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In this regard, engineering design isn’t really any different from invention, art, or any other large creative endeavour. What differentiates engineering design is the application of scientific knowledge and engineering analysis to predict how a design will behave before it is built, using empirical knowledge and analytical methods (which increasingly includes numerical simulations rather than just hand calculations or dimensionally scaled physical models). A validated numerical models can quickly analyze the response of a multiphysics system. A poor model can produce a very pretty false picture. The challenge is to know the difference.

Once the team has a great idea, and confidence in the methods for analyzing how well the concept will work, then these creators can explore how to make the design elegant. One aspect of elegance is to combine features so that a single part of a system contributes to more than one attribute. An example would be a material in a shape that delivers structural strength in an appealing form with a suitable colour and finish. Sensitivity analysis (using design of experiment methods) allows the analyst to examine the effect of changes in design parameters on performance. This is the new empiricism, combinatorial design.

But elegance is much more than simplicity. It is naturalness. A person should appreciate good design by how intuitively it works and how good it looks. Good design is an experience of a person interacting with an artifact, be it a bicycle, or a shoe.