FABRIQUE recycles unused scraps left over from the clothing production process and creates new clothes with the assistance of AI in the design aspect. The AI assists in, or rather produces, designs that utilize mismatching scraps of different colors and fabrics to create aesthetic design patterns (which will be based on the users' preferences and sizes) that the user can then use to stitch the scraps together.
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Isola SET | N5 | P.zza Città di Lombardia | Milano |
Context
More clothing is being produced than ever, as retailers and their customers churn through styles at a rapid pace. Estimates suggest the number of garments produced each year has at least doubled since 2000.
That said, with the industry trying to get the newest styles on the market as fast as possible so that consumers can consume them while they are still at the height of their popularity, only to discard them after a few wears, only a fraction of what’s manufactured gets recycled (Rauturier, 2022).
Eighty-seven percent of the total fiber input used for clothing is ultimately incinerated or sent to a landfill. Fashion brands have come under criticism for practices such as destroying unsold products and sending piles of clothes to landfills across the Global South. Though sustainability measures are growing in popularity, so far, they’re no match for the speed and sheer weight of apparel piling up on the planet (Dottle et al., 2022).
When considering the aspect of scraps that result after fashion productions, the fashion industry only generates 25% of such textile waste that could still use pre-treatment before being used again as a resource for next round of fashion production, with the fraction consisting of >20% being bigger fabric pieces and rest being fibers that can be reused in textile weaving (Reverse Resources, 2021).
Background
As the project works within the scope of AI and its applications to enhance aesthetics while adhering to ethics, scoping, and positioning into the current use of AI in the fashion industry in terms of waste reduction and utilizing cloth efficiently had been performed.
At present, AI-enabled tools can create clothing designs by using data such as images from the brand’s previous offerings or from other designers, data regarding customers’ tastes (color and style choices), and current fashion trends, though not always reliable.
AIs like Dall-E are also being used to project garments on wearers for a virtual fitting experience and “try on” clothes before purchase; this could ensure that consumers don’t end up buying things they don’t like and might return or discard, both of which are unsustainable buying habits.
AI is also being used for enabling automation in the manual apparel production processes, with the main focus being helping overcome ethical challenges of the questionable working conditions workers in the industry have been notoriously put through.
AI is moreover being used to accurately predict fashion trends using different types of data, whereas in the past, such trends would have been identified by designers and trend forecasters using similar data but taking more time; accurate rapid identification of such trends can ensure high purchase rates and in turn, reducing wastage of outdated fashion pieces.
Effective stock management in retail stores and warehouses have also been made more efficient with the assistance of AI-powered systems and applications (Javaid, 2022)
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