4.5 AI and textiles

The integration of Artificial Intelligence (AI) in the textile industry marks a pivotal shift towards more sustainable and efficient manufacturing practices. As Soomro et al. (2021) have pointed out, AI offers a plethora of opportunities to revolutionize textile production, from optimizing processes and reducing waste to enhancing overall sustainability. Let’s delve into the ways AI can be harnessed in the textile industry, the strategies for its implementation, and the key considerations that need to be addressed.

AI technologies can significantly contribute to making textile manufacturing processes more sustainable. By analyzing vast amounts of data and learning from it, AI can optimize every stage of the production process, leading to substantial reductions in energy consumption, material waste, and environmental impact. For instance, AI algorithms can predict the exact amount of fabric needed for a production run, minimizing waste. Additionally, AI can optimize energy use in manufacturing facilities, ensuring machines operate at peak efficiency and reducing the carbon footprint of textile production.

Strategies for AI Implementation in the Textile Industry

Improving Production Efficiency

AI technologies can streamline production processes, from the initial design phase to the final product. Machine learning algorithms can analyze historical production data to identify inefficiencies and suggest improvements, potentially automating certain aspects of production to achieve higher precision and lower waste.

AI’s ability to streamline production processes significantly impacts efficiency and sustainability. For example, Adidas implemented automated Speedfactories, which use AI and robotics to shorten production times and bring manufacturing closer to consumers. Machine learning algorithms can predict and automate the optimal settings for knitting machines, reducing fabric waste. Another example is SoftWear Automation’s Sewbot, an AI-powered sewing robot that automates fabric handling and stitching, ensuring precision and minimizing waste.

https://www.supplychaindive.com/news/adidas-speedfactory-blunder-distributed-operations/571678

AI systems are also being deployed for quality control purposes in textile manufacturing. By analyzing images of fabrics, these systems can detect anomalies, defects, or variations in pattern and color that deviate from the standard.

Example: Several manufacturers use AI-powered visual inspection systems to monitor textile quality in real-time during the production process. These systems can identify issues like stains, tears, or incorrect stitching, allowing for immediate correction and reducing waste.

Textile identification and sorting

Textile identifying AI refers to the application of artificial intelligence technologies designed to recognize, classify, and analyze various types of textiles. This technology can play a crucial role in several aspects of the textile industry, from improving recycling processes to enhancing quality control in manufacturing. By utilizing machine learning and computer vision, these AI systems can distinguish between different fabric types, fiber compositions, and even detect defects or patterns on textiles.

One of the most promising applications of textile identifying AI is in the recycling sector. Traditional textile recycling processes have relied heavily on manual sorting, which is time-consuming and prone to errors. AI-driven systems, however, can accurately identify textiles based on their material composition, color, and condition.

Example: The Fibersort machine is an innovative technology that uses near-infrared (NIR) spectroscopy combined with AI to automatically sort textiles by fiber composition. This capability is crucial for recycling textiles into new high-quality materials, as different fibers require different recycling processes.

Moreover, innovations like Worn Again Technologies use AI to analyze the content of textile waste, optimizing the process of separating and extracting polyester and cotton for recycling. This technology enhances the ability to recycle blended textiles, traditionally challenging to process, and supports the creation of a circular textile economy. https://www.circle-economy.com/programmes/textiles/fibersort

Determining the exact composition of a fabric, especially in blends, can be challenging yet essential for various applications, including recycling and quality assurance. AI algorithms can analyze the characteristics of textiles to infer their composition accurately.

Example: Companies like Circle Economy are developing AI tools to analyze the composition of textile waste streams. By understanding the material makeup, they can facilitate the correct routing of textiles for either reuse, recycling, or other forms of recovery.

Best practices related to AI and textiles

Name:	Seddi Textura AI
Link:	https://textura.ai/
Industry sector:	AI & Textiles
Location:	Madrid, Spain
Description:	Seddi Textura AI is a revolutionary digital textile technology. It uses AI to generate realistic digital fabrics based on actual textile data, enabling users to upload fabrics to the cloud and visualize how they drape and move on digital forms. This technology is designed to transform the fashion industry by digitizing the foundation of garments and streamlining the fashion design and manufacturing workflows.
Environmental benefits:	By reducing the need for physical fabric samples and enabling digital workflows, Seddi Textura AI contributes to more sustainable and eco-friendly practices in the fashion industry. It helps in minimizing waste and the environmental impact associated with the production and shipping of physical samples.
Social & economic benefits:	The technology aids in enhancing the efficiency and productivity of the fashion supply chain. It enables brands, manufacturers, and consumers to make confident decisions based on digital simulations, thus improving the overall quality and speed of fashion production.
Technological & innovative benefits:	Seddi Textura AI represents a significant advancement in fashion technology, merging AI with fashion design. It allows for the accurate simulation of fabric behavior and appearance, aiding in virtual garment prototyping and fitting. This technology paves the way for more innovation in digital fashion and the potential for custom 3D avatars and virtual fitting experiences.

Name:	Smartex AI x Clothuis
Link:	https://www.smartex.ai/clothius-case-study https://www.smartex.ai/
Industry sector:	AI & Textiles
Location:	Portugal
Description:	Smartex is a company that harnesses artificial intelligence to empower textile factories with full traceability and zero waste. Their mission is to enhance quality, increase productivity, and boost sustainability in the textile industry.
Impact in numbers:	For the Clothius case study: Saved 16,626 kg of fabric, 1,862,112 liters of water, 149,634 kWh of energy, and prevented 37,258 kg of CO2 emissions. Overall impact of Smartex powered machines: Saved 961,000 kg of fabric, 8.6 million kWh of energy, 101 million liters of water, and prevented 2.1 million kg of CO2 emissions.
Environmental benefits:	Smartex’s technology contributes to a significant reduction in textile waste and the associated environmental impact. By preventing defects and waste at the source, Smartex not only saves resources but also reduces greenhouse gas emissions, supporting a more sustainable textile industry.
Social & economic benefits:	The Clothius case study shows a payback period of 6.5 months and a 6x return on investment over the contract period, indicating strong economic benefits. Additionally, by improving fabric quality, Smartex strengthens customer satisfaction and supports the textile industry’s shift towards more sustainable practices.
Technological & innovative benefits:	Smartex’s use of AI and machine learning in Clothius’s operations led to a significant reduction in manual labor, saving time and resources while ensuring cleaner production with 100% automatic inspection. Their systems provided real-time defect detection, which is critical in maintaining high-quality standards and fostering innovation in textile manufacturing. Clothius, equipped with Smartex machines, leveraged advanced technology to manage and guarantee the quality of their fabrics with adjustable quality control, demonstrating Smartex’s capacity to modernize traditional industries with cutting-edge solutions.

Name:	WiseEye
Link:	https://www.aidlab.hk/en/research/31
Industry sector:	AI & Textiles
Location:	Hong Kong, China
Description:	WiseEye is an AI-based technology designed for textile material inspection. It automatically and accurately detects fabric defects and color shading in both knitted and woven fabrics. This technology is capable of high-speed, real-time inspection environments.
Impact in numbers:	WiseEye boasts an inspection accuracy of over 95% and can operate at speeds greater than 60 meters per minute.
Environmental benefits:	By improving the accuracy of fabric inspections and reducing waste, WiseEye contributes to more sustainable textile production processes. It addresses the issues of inconsistency in manual inspections and helps in minimizing downstream wastage.
Social & economic benefits:	This technology alleviates the shortage of skilled quality inspectors in the textile industry, potentially leading to more efficient production processes and reduced operational costs.
Technological & innovative benefits:	WiseEye represents a significant advancement in textile inspection, integrating AI to handle a variety of fabrics and patterns, including plain, twill, single jersey, double jersey, stripes, and checks. Its ability to adapt flexibly to different materials, including leather, showcases its versatility and innovation in textile quality control.

Name:	Textile Classifier App
Link:	https://blogit.lab.fi/labfocus/en/identifying-textiles-using-computer-vision-in-a-mobile-app/
Industry sector:	AI & Textiles
Location:	Lahti, Finland
Description:	The Textile Identifier App is an innovative tool designed to assist in textile recycling efforts. Developed as part of the AI-mill project, the app utilizes computer vision and machine learning algorithms to classify textiles based on their structure (weft or knit) and color. The goal is to improve sorting accuracy and ease the recycling process for workers.
Impact in numbers:	A dataset of approximately 3,000 textile images was used for training the AI model. Released a free test version for Android devices in June 2021.
Environmental benefits:	The app reduces the need for recoloring recycled textile fibers by accurately sorting textiles by color, consequently saving water and decreasing environmental impact, also improving the recycling sorting process.
Social & economic benefits:	By streamlining the sorting process, the Textile Identifier App aids recycling center workers, potentially reducing labor and associated costs. It also contributes to the efficiency and effectiveness of textile recycling, thereby supporting the circular economy in the textile industry.
Technological & innovative benefits:	The app represents a significant advancement in recycling technology, applying real-time classification through a user’s smartphone camera. The project explores the potential for integration with sorting machines, utilizing microcomputers for automated sorting.