Innovation @ E2Expo

Machine Learning to reduce waste in fashion industry

Updated : December 2020


  • Production professionals
  • Textile and fashion designers
  • Textile industry sustainability professionals
Research collective Synflux has developed a system of digitised couture that reduces the amount of fabric needed to make clothes by creating garments that exactly fit the wearer’s body. Called Algorithimic Couture, the project was presented at Design Indaba and involves 3D-scanning a body to determine its exact proportions, which are used to create customised clothing.

Read more: Machine Learning to reduce waste in fashion industry


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  1. Machine Learning to reduce waste in fashion industry




| Japan

Year Established


Highlights and sustainability benefits

By utilising 3D-scanning technology alongside computer-aided design (CAD) software, the research collective able to optimise garments to the unique body types of the user


Synflux’s system also allows the user to customise the shape, fabric and colour of the final garment to reflect their personal style.

About the Work

Synflux runs machine-learning algorithms over the data collected to find the optimum garment pattern that reduces fabric waste to zero. The programme then generates optimised fashion pattern modules comprised of 2D rectangles and straight lines. These 2D modules that make up the overall garment are then modelled using computer-aided design (CAD) software to produce a fashion pattern for an item of clothing that is both comfortable and sustainable.

About the Innovator

Algorithmic Couture is a collaboration between project lead and fashion designer Kazuya Kawasaki, Shimizu, designer Kotaro Sano and machine learning engineer Yusuke Fujihira, who together make up Synflux. Algorithmic Couture aims to democratise haute couture customisation culture prevalent in the 19th-century, by revitalising personalisation in the digital design process.

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