Technology has ensured that life is no longer hard or uncomfortable. It is therefore a constant endeavor to achieve perfect satisfaction and fulfillment. Smart textiles are the way to fill the market gap that appears due to the popularity of wearable technology and fitness trackers.
Based on a report by M. Shahbandeh in Statista, the market is expected to reach $1 trillion by 2023. 2020 to $2 trillion and beyond. 25 trillion in 2025. Thus, the demand for both clothes and shoes is increasing worldwide.
The textile industry is employing robotization and AI to reduce the costs of labor and manufacturing and meet the clients’ requirements associated with the strive to provide high-quality products.
This has undermined the textile industry, which was once a work-intensive sector, with the growth of new technologies like AI and IoT. Technology is now present in most textile firms, and it is far easier to mechanize the large-scale production of such specified designs as is the case with hand labor.
I am always on the lookout for new products in smart clothing. Through integration with IoT BLE, edge computing, and the cloud, smart textiles will carry out the exchange of data, including biometric data such as the user’s blood pressure, heart rate, or similar; humidity; temperature, and other data.
This article mentions the impact of AI on the textile industry, some of the latest use cases, and the need for ultra-low power to accommodate AI at the edge.
Artificial Intelligence in the Textile Sector
Textile manufacturers are reshaping AI’s entire business management and production process. Artificial intelligence has the ability to retrieve and gather operational and historical data instantly, as well as offer insights that can improve operational effectiveness. If you have a thorough understanding of your operations, it is easier to modify processes to boost the capability of human workers.
AI has an impact on every aspect of life, including product prices, textile fabrication, quality assurance, just-in-time production, data collection, and computer-integrated manufacturing. Pattern recognition, color matching for textile production, and flaw detection are more often incorporated in AI applications.
The use of artificial intelligence (AI) has made it possible to offer better experiences for “Smart Clothes,” or IoT and electrical sensor-based apparel. With these technologies, smart clothing can offer a more enjoyable and health-oriented experience. Now let’s talk about some creative uses of artificial intelligence in the textile industry.
Yarn Production
The application of AI completely transformed every stage of the production process, from the blow room to the carding, drawing, lap formation, combing, speed framework, ring spinning, winding, packing, and conditioning. AI-based control panels identify all necessary production parameters with minimal human intervention.
This has improved quality and reduced costs while also fortifying the process. The precision of predicting yarn by computing spins has increased. Artificial intelligence has helped to improve textile grading by reducing yarn grading errors to as little as 60%. AI has simplified the process of measuring a fabric’s physical characteristics and provides an objective classification of textile comfort.
Examining the patterns on the cloth
The use of artificial neural network (ANN) technology facilitates the identification of flaws in models such as knitting and weaving. AI-enabled view-based inspections can increase efficiency by lowering human error rates. One example of an AI system that can automatically analyze fabric patterning is Cognex ViDi, developed by Cognex Corp.
AI-enabled fabric pattern inspection reduces pattern errors with the least amount of work and the highest level of accuracy, which speeds up manufacturing. AI can also be used to find fabric flaws, which were formerly found by laborers, by carefully analyzing each material’s quality on an individual basis. Manual detection requires a lot of effort and time in order to expedite the process and reduce incursions.
Color coordination
To confirm that the final textile color matches the original color design, data color is frequently used in color management. Datacolor suggests adding historical data from the visual assessment results of human operators to its AI function in order to provide tolerances that lead to contributing inspections that look a lot like the visual inspection samples.
The Data Color System dispenser holds dough, media, liquid pigments, and colored dyes. In a short time, prepare the most correct solutions for each location.
Fabric grading
Machine learning has enabled more objective fabric grading and consistent results in the textile production industry. The precise measurements of the fine, solid, and staple fiber lengths made with an artificial neural network are advantageous to AI.
With the help of an electric motor, the machine creates a high-performance LED lighting bar with a powerfully coupled high-resolution camera. This is used to keep an eye on the fabric.
Creating patterns
In the textile industry, model cutting, and design creation are crucial processes that include cutting materials according to a pattern and creating different patterns on the fabric. CAD is a subset of AI that allows designers to create computerized patterns by building and digitizing the patterns’ basic structure.
Patterns are cut using CAD, and the provision of 3D images of fabric and ideas facilitates easier exposition.
The management of supply chains and retailing
AI can be used in the textile industry to automate packaging and transportation. The smooth flow of goods between retailers and material producers depends on supply chain management. Robust storage spaces, enhanced warehouse operations, product segregation, and enhanced communication are necessary for effective supply chain administration. AI can provide all these advantages through robotics, RPA, machine learning, IoT, and other technologies.
Using AI to analyze and process data fragments, tailor customer experiences, track consumer behavior, and forecast market trends is another area where merchandising may be used. AI enables the best possible communication between manufacturers, merchants, and customers through technologies like data analytics, natural language processing, and virtual assistants.
AI’s Effect on the Textile Sector
Recognizing trends
Given the speed at which fashion trends change, predicting future trends is undoubtedly a challenging and time-consuming task. Analysts have to carefully look through client preferences, social media trends, and previously popular styles to find the next big thing. Experts might or might not predict precisely what they are doing.
The AI tool analyzes historical fashion data, evaluates competitor moves, assesses customer requirements and preferences, and spots market trends. It has been trained in both the amount and quality of data.
After evaluating the data, the AI technology offers precise information about popular designs in a matter of minutes. With AI, fashion companies can quickly—often within days or even months—improve their clothesline by keeping up with the newest trends in the industry.
Design helped by machines
A whole new style could be created on its own by analyzing AI tools and learning from the images of the deceased. Since AI in design has proven to be so promising, many industry titans have already made significant progress in implementing the technology. For instance, a team of experts at Amazon created an AI tool that can comprehend and analyze images and create an entirely new fashion design on its own.
Furthermore, the massive Amazon corporation developed additional AI software that evaluates and examines the provided photographs to determine whether or not a particular style is in style. Hundreds of other digital behemoths, including Amazon, have already embarked on an AI journey and completely optimized their design processes.
Together with Tommy Hilfiger and the Fashion Institute of Technology (FIT), IBM is utilizing AI to enable designers to expedite the product development cycle.
The experience of the client
Customers continue to be irritated and complain about not getting prompt assistance or service; thus, fashion companies are under constant pressure to meet their demands almost immediately. Because of this advanced technology, fashion brands are working to emphasize customization while customers are making purchases.
From personalized advertising notifications to price reductions, chatbots may answer queries and doubts and even help with personal styling. AI can deliver instantaneous client recommendations, enabling fashion firms to achieve their objective of improving customer satisfaction.
Users can click on photographs or browse garments online with AI stylist applications available on the market. The program suggests the best style when these photos are displayed as inputs, taking into account the user’s preferences, type, and complexity, and honoring current fashion trends.
Given that AI may serve as both a personal stylist and a creative assistant for designers, it is clear that technology is having a greater impact than we ever could have imagined.
Permitting Novel Applications
Just as fitness trackers empower their users to lead healthier, more focused lives, smart clothing paired with electric sensing technologies can do the same. Nonetheless, because you interact with your body more than a smartwatch does, your clothing can provide more physiological signal monitoring options than a smartwatch.
Smart clothes can enable continuous biometric monitoring, including heart rate tracking. More useful long-term surveillance would help medical professionals detect or diagnose potential cardiac conditions more accurately. Patients can track chronic cardiovascular disorders, gather comprehensive cardiovascular data, and improve cardiac detection and diagnosis through regular, long-term monitoring by wearing smart clothes.
Consumers used fashionable clothing and wearable technology to emphasize healthcare and medical treatment after the COVID-19 pandemic. Fabric-based sensors should be combined with BLE-based wrap sensors that can sense and control data, hence increasing the entire wearing experience.
Future of AI in Textile Industry
The future of artificial intelligence in the textile and garment industries seems promising. AI is capable of much more, including increased production, help with fiber identification, better working conditions, and demand forecasting. A Forbes piece on the fashion industry states, “Fashion brands are utilizing AI and machine learning increasingly to maximize customer shopping experience, boost sales system efficiency through smart automation, and improve sales processes by employing predictive analyses and guided sales processes.”
For the textile sector, artificial intelligence will undoubtedly have a significant impact on how businesses expand and how sustainable fashion is produced over the coming years. I hope I was able to clarify some of your confusion about artificial intelligence’s function in the textile sector.
