Generative design for AEC

Imagine you are planning the interior for an office building. In one scenario, your first step is to define the design parameters by describing the amount of light you want for desks depending on the season, the desired views for conference rooms, and the maximum amount you want to spend for construction. After you define the criteria, your design tools generate all the best possible outcomes with a single analysis and evaluate the alternatives. This all takes place in a fraction of the time that it normally takes you to manually arrive at one or two best-guess approximations.

In the other scenario, you sit down and manually calculate how your design parameters impact other aspects of the office building like energy loads and construction costs. You tediously go through the hundreds of location variables—kitchens, bathrooms, desks, or communal space placements—produced by your choices as the design develops. This entire process takes days or weeks as you review the options.

What is generative design?

How might it change the way you design if, like in the first scenario, your software could help discover the implications of the goals you define instead? Now think about a typical construction project and shift your approach to the actual procedure of building—and not just what you’re building, but how it is built.

Cost overruns and waste are always the enemies of construction. What if you could mitigate these potential risk factors with better recommendations on materials or by scheduling and sequencing job site work? What is the right strategy for placing precast concrete panels? Or the optimum placement of a crane? A software algorithm can test numerous scenarios for potential solutions to find the best one.

These are the objectives of generative design; a technique that uses computation to augment the designer’s ability to define, explore, and choose alternatives through automation.

Generative design   / gen·er·a·tive de·sign/    noun
A goal-driven approach to design that uses automation to give designers and engineers better insight so they can make faster, more informed design decisions.

Your specific design parameters are defined to generate many—even thousands —of potential solutions. You tell the software the results you want. With your guidance it arrives at the optimal design along with the data to prove which design performs best.

Generative design is more than a methodology; it embodies many applications and techniques. It will continue to grow more potent and useful with technological advancements such as artificial intelligence and machine learning. But, at its heart, generative design is about providing practitioners with the ability to quickly explore, optimize, and make informed decisions to complex design problems.

Think of generative design software as an assistant that helps with creating, testing, and evaluating options.

And it may well provide scenarios you might have never imagined, allowing you to do even more with less—whether that’s less time or resources. But, ultimately, it’s up to you to make the decision of what’s right for your project and the priorities.

While all of this may sound wildly futuristic, generative design is already changing how decisions are made during all phases of the design and construction process. Here, we’ll explore what generative design means to the AEC industry.