Digital Automation for Custom-to-fit 3D Weft-Knitted Garments

Automated flatbed weft-knitting technology holds the potential to significantly increase product variety, allow for customization, and reduce production stages. Computer numerically Controlled (CNC) knitting machines can produce a knit-to-wear garment, tailored to one's specific size, based on given digital parameters. This research aims to POC a new 3D knitting workflow using Machine Learning (ML) to produce knitting instructions. We aim to prove that it is possible to reverse engineer knitting instructions from a height map provided by the designer.

In this project Guy Austern serves as a PhD. advisor