10057775Co-Designing an AI Factory Flow Manager for On-demand Apparel Manufacturing with Garment WorkersClosedGrant for R&DInnovate UK**Business Need** * Pattern Project is focused on transitioning the global fashion industry to an on-demand no-stock model. * Our hardware and software pipeline is designed for the "pull" dynamic model, in which production is based on customer demand with an automated factory flow. Garments are personalised or custom-fit, and staff is trained on micro-batches of five. * The most difficult challenge is managing the workflow of machinists for weekly on-demand production. We currently produce 12 styles for five brands and welcome new brands each week. Each style has between 9 - 30 individual steps and employs 2 - 5 different machines. Production is batched weekly, and quantity per style can vary between 1 - 50 pcs. * We manually schedule a production roster based on the order queue and determine, given a list of items and their quantities and involving the least switchover time for machinists. **New idea - AI Factory Flow Manager** We want to create an artificial intelligence factory flow manager for on-demand apparel manufacturing that can optimise the production process for various styles. This AI will be capable of optimising for the following variables: * Logistic factors - Size of garment batch, Desired date of delivery of the batch, Machine set up and switchover times * Garment style factors - Synergies across styles for seam finishes * Garment Workers factors - The current skillset of the machinist, The learning ladder of individual machinists, Relative speeds of machinists, Machinists' current product skillset concerning resilience in the production line, Quality of life and meaningful work, Response to Challenge **Benefits** * Serves management by improving overall quality and productivity and making on-demand production cost-effective. * Benefits garment workers by involving them in the design and control of their work, increasing their motivation and job satisfaction. * Serves the interests of the entire organisation - by creating a formal system to encourage learning and capture and communicate improvements in methods. Inspiration -[NUMMI plant transition][0]. **EDI Challenge** Women account for 80% of all garment workers worldwide. Still, men continue to dominate the invention and design of manufacturing technologies/systems. This is concerning since productivity software, automation, and the use of robotics directly impact the lived experience of garment workers and their employment prospects. **EDI Impact** * Better quality of life for garment workers through a dynamic and cooperative culture, training integrated into daily work. * On-demand custom-fit production can double margins for the labour-intensive industry - safeguarding and creating better jobs. [0]: https://sloanreview.mit.edu/article/how-to-change-a-culture-lessons-from-nummi/