The article is about the new paradigm of Generative Design and applications of Topology Optimisation. This article was originally written in Medium and can be found here.
When we look at all the things that surrounded us, we can see a strong commonality. We see simple geometric figures; we see versions of circles, squares, and triangles. These are carefully designed and engineered products designed and manufactured from different parts of the world. But still, they strike a similarity.
What makes them similar is that they are all designed by a human and are manufactured by standard machines. Are these designs the best? Can we do any better than the current design forms? Let us ask the wisest and the most experienced designer around, nature. So re-framing the question, does nature do it this way? Not. Well look at humans, birds, trees, and mountains, how similar are these compared to the buildings or bridges we build.
When a product takes life, it takes shape from the designer’s intuitions on how the product should look and feel. The most experienced designer thinks through all the possibilities and learns from the feedback. This experience introduces bias in the design process diverging from what it should be, to what the designer thinks it should be as. So what we call a good design might not be an optimal one. So I ask the question again, can we do better? As humans, we have a limited computational power to make design decisions. What if we could augment the intuition with more powerful tools to make better decisions.
Topology Optimization is one of those tools. We have built many structures through time. Some remain and some have gone. But many prominent natural structures remain, and we see them as wonders now. Topology Optimization helps us build better structures more natural in some respects. This tool helps us build structures as tough as metal but as light as plastic. Topology Optimization is a method where an algorithm decides the form or shape of the structure given the requirements. It judges if there is a need for material in a given location of the component thus carving out the most optimal structure eventually. Simply put given a big block of material the computer carves out the best structure for your needs, say for a building or a table stand or anything you can think of.
Consider our bones, they take the load, but they look completely different from any of those pillars we’ve seen around. The designs produced by such an algorithm beat the conventional designs not only in performance, weight, strength but also carry a unique aesthetic appeal. This begins mark to a completely new era of design.
Companies like Autodesk, SolidWorks have already realized the potential and have jumped into research in this field. The community has already shown some amazing examples to demonstrate the capability of this tool is. The below image is the Light Rider produced as a result of collaboration between Altair and APWorks.
Light rider. Source: DE Airbus has designed something called a bionic partition to reduce the weight of the plane.
Bionic Partition. Source: DE Though this is an old tool, the current computational capability allows us to solve more complex and tough problems. Additive manufacturing has unlocked the potential to make these complicated designs a reality. Taking advantage of the powerful deep learning architectures further boosts the design possibilities. Maurice in this TED has shown some spectacular example of an engineered component looking similar to that of nature. This page on Generative Design by Autodesk has many more examples and details.
Not so far away in the future, we can imagine moving away completely from an intuition based to optimisation based design strategies. These might look a bit weird in the beginning, but we’ll catch up with them soon.