Generative Design: A Transformation in How Products Are Made

In modern manufacturing, an innovative new process sees the designer create a system and that system actually generate the product. The process is known as generative design and it represents over a paradigm shift in product design.

3D printed generative easter eggs

photo credit: Behance

Here is a look at how generative design works and the revolution underway in modern product design.

What Is Generative Design?

The end result of generative design, whether it’s a chair, an image, an animation or an architectural model, is the byproduct of an algorithm. A set of rules entered in to a computer program and uses highly complex protocols of parametric modeling to generate and test different variations of a product design.

It is data driven. Humans participate in this process by creating the algorithm. That’s why Shapeways calls the new way of designing ‘dasign,’ a takeoff on design.

Cellular bowl

photo credit: Shapeways

In the traditional design, the initial drawings moves come from a person’s brain and are transmitted to a blueprint or CAD image. From there a prototype is put together in the factory or by the craftsperson.

In generative design, human designs are still necessary. But their role has shifted to creating design requirements and setting rules while an algorithm generates the actual design.

Comparing this approach to an artist working with canvas and oil paints, with generative design the human doesn’t actually apply the paint. Instead he or she designs the automated tool that will apply the paint to the canvas, whether it is a brush or some other method of painting.

Revolutionizing Design

Many innovators think generative design simplifies the design process by systemizing it. The marriage of tech and design, they feel, has the potential to create true and beautiful design. It is the next logical step to simulation tools that let users explore features and model various options.

For engineers, generative design gets rid of much of the grunt work and lets new possibilities shine through. Time can be better spent on objectives and constraints, while the computer or algorithm handles repetitive processes. This approach uses the engineer’s time more efficiently.

Generative design is also more efficient from a business point of view. It automates the complicated processes involved in designing. This lets the engineer come up with more effective and precise designs.

Who’s Designing What?

Generative design is not just revolutionizing design; it’s also confusing designers. For example, who designed the Bone Chair? Joris Laarman is credited with its design. To do so, he used a custom tool to simulate bone growth. The tool itself was actually created by General Motors. They originally designed it to model more efficient structures for making cars.

Did Laarman design the chair? Or did the car company? Or the researcher who created the algorithm for the bone growth software? Or the software engineers who made the tool? It’s a conundrum.

Generative Design in Action

Jeff Kowalski of Autodesk explored the possibilities of generative design in a recent blog post where he described iterating a new roll hoop for a racecar. He gave a powerful software program a set of rules for what he wanted to achieve in his design. He added in the constraints that were involved. Then the computer came up with a large number of possible solutions.

The output featured hundreds of design options in the time it would take a human to come up with just a few. Kowalski could then easily check pros and cons and compare and contrast designs. The result of this part of the process let him redefine what he wanted to achieve. He then started the entire process again. And again. With each iteration, the goal was refined and the constraints made more exact. The final design was the result of this cumulative process.

With generative design, the computer becomes a person’s partner in the design process. The computer, in effect, comes up with ideas of its own, in service to the human’s overall need for an answer. At this point, the human still selects the solution.

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