How To Problem Solve and Streamline Workflows with Generative Design

Nautilus shell patternEvolution tests out many different possibilities over millions of years, some mutations provide no advantages and aren’t passed along. Others become so beneficial that soon an entire species adapts a new trait that lets them thrive. What if this same trial and error approach could be used to find an optimal form in our design processes, only in a vastly shorter amount of time?

Generative design uses machine learning to generate multiple design suggestions based on a given set of parameters such as size, weight, manufacturing method and material. Intelligent software presents many options for an engineer to consider, including unconventional designs that a human would be unlikely to ever come up with. In combination with simulations and 3D printing, teams are able to identify the shapes that will perform best for their needs. More and more industries are taking advantage of generative design to solve problems and streamline their workflow.

Read the full article An Intro to Generative Design in Industry Week.

Meaghan Murphy

Meaghan holds her Bachelor’s degree in Psychology from Sarah Lawrence College in Bronxville, NY. Prior to Dassault Systèmes, she worked as regional marketing manager and occasional freelance script writer on the side. She has a passion for writing, education, nature, science, and technology. She is currently pursuing her dual MBA/MSM from Suffolk University in Boston. Outside of the office you may bump into her on the North Shore of Massachusetts photographing beach scenes, lush flowers, or her latest smoothie bowl.