generated sayl | 2021
How might designers use generative tools in their workflow to produce new ideas? This is a question I’ve been asking myself since completing Generated: a series of 100 experiments created with code. With Herman Miller releasing the 3D files of the Sayl Chair, I wanted to explore how new colorways could be created developed based on generative results.
material: urethane plastic, heather fabric
type: personal
status: concept
status: concept
This project was created using Processing to generate the colorways and Keyshot to render out high fidelity versions of the chair. Creating the palettes is the link that connects these two programs. To quickly generate results, the program masks over specified components of the chair and fills the layers with colors pulled from the source images.
For this initial test, three colors were used to create visual balance among the components. With future iterations, I see the tool being able to choose the colors for each part of the chair.
A tool like this has an interesting business application whether it is client facing or simply an internal resource. Giving customers the ability to personalize their products has been proven to be successful with tools like NikeID and Xbox Design Labs. With Covid increasing the amount e-commerce transitions, there is an opportunity to create new exciting shopping experiences not previously explored. Design teams could also benefit from using a tool like this in their workflow to process mood boards and generate results based on trend predictions.
What makes the program so powerful is its ability to produce thousands of results in seconds, however, this may also be its biggest weakness. Since results must be processed manually, reviewing generated outputs requires a great deal of time. Currently, I'm working through how to best filter results and share ones that might help the user develop unique solutions. Please reach out if you are interested in developing a tool like this for your team.
