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AI Repair Module: Repurposing machines in the textile industry for automated repair

Reference number
Coordinator RecoMended AB
Funding from Vinnova SEK 803 080
Project duration September 2023 - June 2024
Status Completed
Venture Emerging technology solutions
Call Emerging technology solutions stage 1 2023

Important results from the project

** Denna text är maskinöversatt ** The project aims to automate sewing machines, leading to increased efficiency and productivity. By reducing the skill requirements, profitability for companies in the industry can increase. Sustainability is taken into account by enabling repair and reuse. The results show that it is possible to make programmable machines available to mend textile products where the mending pattern is automatically generated. The machines can perform repairs independently while the operator prepares the next product, increasing efficiency and quality.

Expected long term effects

** Denna text är maskinöversatt ** Results: Camera can be connected Assembly of clothes works AI and algorithms developed and creates repair patterns. Repair patterns are sent to machine The machine sews according to calibrated coordinate system with camera and software. Expected effects: Useful 1-2 years through commercialization in collaboration with machine manufacturers where software and hardware offer repair machines. Textile companies become primary users of automated machines for repair. More user-friendly machines lower skill requirements, for equality.

Approach and implementation

** Denna text är maskinöversatt ** Through collaborations with Science Park Borås and Wargön, we have secured the latest research for a solid project start. Under AP 1 we held four workshops with UX and AI developers and started software development to identify bottlenecks. We used process mapping and flowcharts to map the entire process and create an MVP. In work package 2, we also used process mapping to validate development areas and identify bottlenecks. Work Package 3 focused on testing patches on jeans to identify practical bottlenecks and reach TRL 2.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 2 August 2024

Reference number 2023-01479