Public Funding for Pattern Project Ltd

**Objective:** Our project aims to optimize and refine Manny, an AI assistant prototype utilizing digital twin technology in batch manufacturing, initially focusing on the apparel industry. Our goal is to slash the man-hours required during the new style production flow setup phase, everyday task assignment, line management, calibration and training by 50%, enhancing operational efficiency and the effectiveness of just-in-time small batch production. **Innovation:** Manny introduces a paradigm shift in manufacturing management, combining AI with digital twin technology to streamline workflow and personnel coordination. This innovation not only boosts productivity but also fosters a more sustainable, cost-effective manufacturing model by making Just-in-Time manufacturing a reality. **Development Phases:** The project encompasses a series of ten work packages designed to enhance 'Manny', our innovative AI-driven tool for manufacturing management. Key focuses include refining Manny's algorithm for greater factory efficiency, developing a decision-support feature for assessing new orders, and creating easy-to-use tools for digital twin creation. The plan involves rigorous testing and integration of these features, followed by real-world deployment across an expanding network of factories. This approach aims to streamline production processes and enhance decision-making capabilities in manufacturing settings. The project will culminate in a comprehensive evaluation and documentation of all developments and findings, laying the groundwork for future advancements in manufacturing technology. **Outcome:** This project will deliver an advanced, efficient Manny, ready for broader application across various manufacturing sectors. Manny's enhanced capabilities will be instrumental in revolutionizing factory operations, achieving significant time and resource savings, and establishing new efficiency standards in the manufacturing industry. **Impact and Future Economy Alignment:** Manny aligns with Innovate UK's future economy vision by contributing to net-zero goals through efficient resource management and advancing next-generation digital technologies.

**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/

Background Pattern Project is a Smart Grant funded clothing micro-factory startup. We have developed proprietary machinery and a patent-pending process to enable clean, on-demand manufacturing of customized clothing. Vision Our vision is for clean-energy driven, on-demand micro-factories which produce custom-fit / customised clothing on every high-street, available online for home delivery to replace fast fashion stores across the country. For our proprietary low-emission fabric cutting machine and software to help digitise traditional tailors and small fashion houses. For people to have a deeper relationship with 'their style' and sense of ownership with their clothing, and to know their clothes inside out. For Britain to lead the world in a hybrid of craft, digital fabrication and human-centred automation. **Key Objectives** We are proposing conducting design research with the following objectives - * Better understand the needs, motivations and clothing buying and customisation behaviours of people with non-average and extreme body shapes. Understanding the key pain points with off-the-rack sizes. Conducting this research for both instore and online audiences (followers of [@patternprojectuk][0]). * Define the problem statement and generate ideas for an experiential clothing micro-factory that provides customisation and custom-fit garments moments after they are ordered. * Pinpoint the characteristics necessary to make the solution desirable and fit for purpose for both online and instore audiences (multi-channel revenue model). **Research Outcome** As an outcome, we will deliver a clearly communicated concept for a high-street experiential clothing micro-factory that offers customisation/custom fit to both online and in-store audiences. The concept would have been validated through fast, low-cost prototyping and user-testing and is ready for further technical R&D. [0]: https://www.instagram.com/patternprojectuk/

Pattern Project will re-imagine the UK's relationship with clothing. We will make well designed, custom-fit, contemporary garments made from high quality fabrics that are affordable to many people, not just the few. Our aim is to increase functional and emotional durability of clothing. We will harness the UK's talent in user experience, software development & technical fashion design to produce digitally-aided bespoke garments. Our Project has three focus areas: * Product Innovation \> Design of PP Ready-to-assemble clothing & the learning experience. We will be developing and testing augmented reality learning filters and sew along videos. Testing fabrics with diverse fibre compositions, identifying the impact of engraving on fibres. Developing a PP material library. _Contact us if you are interested in testing our first product. * Digital customer segmentation \> Digital customer segmentation to identity and size target audiences and how the product can be adapted to reach those audiences * Technological Innovation \> Design & develop back-end platform including proprietary layout optimisation algorithms & automation scripts for seamless integration between website front-end & laser cutting machine software. Conducting a time/motion Study for Production Process Optimisation by Identifying focused interventions to reduce errors, optimise the workflow, health and safety of the operator. Our application has been supported by Future Fashion Factory, which is part of the Creative Industries Cluster Programme, funded by the [Arts & Humanities Research Council][0] and part of the [Industrial Strategy][1]. [0]: https://ahrc.ukri.org/ [1]: https://www.gov.uk/government/topical-events/the-uks-industrial-strategy