Revolutionising Waterless Textile Dyeing through Optical Colour Mixing and Machine Learning Colour-recipe Prediction

通过光学混色和机器学习颜色配方预测彻底改变无水纺织品染色

• 批准号: 10079762
• 金额: $ 69.83万
• 依托单位: AMPHIBIO LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10079762
• 关键词: Revolutionising; Waterless; Textile; Dyeing; through

**Public Description:**Conventional textile dyeing is a significant environmental concern, utilising vast quantities of water, estimated at 92 billion m3 annually, and involving substantial chemical usage. It generates a large amount of wastewater, and valuable dyes worth around 800 billion GBP are discarded as effluents every year. Moreover, the traditional colour creation process is often error-prone and wasteful, heavily relying on colourist's expertise and analogue lab dips. Our groundbreaking project, in collaboration with Amphico and the University of Leeds, aims to revolutionise the textile industry through our innovative waterless coloured textile production and a data-driven, machine learning (ML) based textile colour creation approach. By cleverly combining a colour creation method with dope dyeing, we are able to develop a low minimum order quantity, low impact, low carbon and low cost waterless coloured textile.Amphico is a material science company, with expertise in advanced polymer blending and performance textile development, committed to transforming the textile industry through innovative, sustainable material and manufacturing technology aimed at increasing resource efficiency and reducing chemical-pollution. With Innovate UK's support, we aim to bring about a sustainable shift in textile production:**• Planet:** Our innovative colouration method, which introduces colour at the polymer solution phase before yarn extrusion, dramatically reduces water usage by 90% and CO2 emissions by a substantial 96% compared to traditional water bath dyeing methods. The integration of our ML colour-recipe prediction system into the colour creation process minimises waste, significantly enhances design efficiency and aligns with global sustainability goals.**• People:** Our project offers significant advantages for end users. We enhance product aesthetics and lifespan with improved colour quality and durability, reducing the need for frequent replacements. Our low-MOQ production provides a variety of colours from fewer primary coloured yarns, expanding customer choice. Our Machine Learning colour-recipe prediction software will allow textile manufacturers and brands to tailors production to market needs, enabling personalisation. Importantly, our eco-friendly dyeing process allows consumers to align purchases with sustainability goals, balancing consumer satisfaction with environmental responsibility.**• Profit:** Through our partnership with leading academic institutions and potential alliances with industrial stakeholders, our innovative waterless coloured textile and ML software provide apparel brands with opportunities to achieve their sustainability targets, reduce their environmental impact while improving their margins. By producing high-quality textiles suitable for scaling in global markets in partnership with our brand partners, we create a profitable solution, contributing to the UK textile and apparel economy.

**公开描述：**传统纺织染色是一个重大环境问题，每年消耗大量水，估计为 920 亿立方米，并涉及大量化学品的使用。它产生大量废水，每年价值约 8000 亿英镑的有价值染料作为废水被丢弃。此外，传统的色彩创建过程往往容易出错且浪费，严重依赖调色师的专业知识和模拟实验室的经验。我们与 Amphico 和利兹大学合作的开创性项目旨在通过我们创新的无水有色纺织品生产和数据驱动、基于机器学习 (ML) 的纺织品色彩创建方法来彻底改变纺织行业。通过巧妙地将色彩创造方法与原液染色相结合，我们能够开发出低起订量、低影响、低碳和低成本的无水彩色纺织品。Amphico 是一家材料科学公司，拥有先进聚合物共混和高性能纺织品开发方面的专业知识，致力于通过创新、可持续的材料和制造技术来改变纺织行业，旨在提高资源效率和减少化学污染。在 Innovate UK 的支持下，我们的目标是实现纺织品生产的可持续转变：**• Planet：** 我们的创新染色方法在纱线挤出前的聚合物溶液阶段引入颜色，与传统水浴染色方法相比，可大幅减少 90% 的用水量和 96% 的二氧化碳排放量。将我们的机器学习颜色配方预测系统集成到颜色创建过程中可以最大限度地减少浪费，显着提高设计效率并符合全球可持续发展目标。**• 人员：** 我们的项目为最终用户提供了显着的优势。我们通过提高颜色质量和耐用性来提高产品的美观性和使用寿命，从而减少频繁更换的需要。我们的低最小起订量生产可以用更少的原色纱线提供多种颜色，从而扩大了客户的选择范围。我们的机器学习颜色配方预测软件将使纺织品制造商和品牌能够根据市场需求定制生产，从而实现个性化。重要的是，我们的环保染色工艺使消费者能够将购买与可持续发展目标结合起来，平衡消费者满意度与环境责任。**• 利润：** 通过我们与领先学术机构的合作以及与行业利益相关者的潜在联盟，我们创新的无水有色纺织品和机器学习软件为服装品牌提供了实现其可持续发展目标、减少对环境影响的机会，同时提高了利润。通过与我们的品牌合作伙伴合作生产适合在全球市场扩展的高质量纺织品，我们创造了一个有利可图的解决方案，为英国纺织和服装经济做出了贡献。