BY LIT Lukasiewicz - Lodz Institute of Technology

January 2024 Introduction

AI is crucial in the competitive textile industry. Traditional methods based on human experience are insufficient compared to AI's capabilities. Embracing AI is essential for innovation and competitiveness. Failing to digitize and automate hampers progress. Exploring AI in production and effective factory management is crucial for success. The concept of a fully autonomous AI-run factory is no longer just science fiction [1].

AI in production

AI and modern tech are crucial for industry innovation. Without digitization and automation, industries face stagnation and reduced competitiveness. Defining AI's role in production and its effective use in factory management is key. The concept of a fully autonomous factory, depicted in sci-fi, seems unlikely in practical manufacturing. In the context of manufacturing, artificial intelligence is defined as the ability of machines to perform tasks assigned to humans. Machines are programmed to respond to various events and predict them automatically. The introduction of artificial intelligence into production allows machines to detect problems such as tool wear or errors that are about to occur and automatically respond to them. In manufacturing, artificial intelligence enables machines to perform human-assigned tasks, respond to events, and predict issues like tool wear or errors automatically. AI automates tasks, making specialist work easier and freeing up time for creative tasks. This reduces errors and costs for companies. While industrial robots need human supervision, AI, like machine learning, enhances collaboration for safer and more effective work. Robots handle repetitive tasks, allowing humans to focus on analytical work, product development, and customer relationships. Despite automation, new positions emerge for specialists in programming, operating, or servicing these technologies [1].

AI as a tool for forecasting trends and demand

AI has the ability to forecast trends and demand, which is currently important in the context of analysing changing fashion trends. Analysing these trends becomes a challenge due to the large amount of rapidly evolving data that is shaped by various factors such as social media, its users and fashion bloggers. AI enables the collection and analysis of a significant amount of data in the area of the so-called cultural trends, which allows you to quickly respond to these trends when creating collections. Additionally, a tool such as Google Trends, which was created to monitor the number of user queries entered into the Google search engine, is helpful in analysing trends. Thanks to this tool, clothing brands can effectively control the popularity of searches for specific products in the context of time. This, in turn, allows you to assess the impact of various factors on the popularity of specific search queries [2].

Design with artificial intelligence

AI is revolutionizing the design process through the use of machine learning algorithms. For example, these systems analyse vast amounts of data about the history of fashion trends, consumer preferences, and even cultural influences. This allows designers to predict which patterns and styles will become popular in the future, avoiding the risks associated with blind design. Additionally, generative artificial intelligence models can create original patterns and concepts that can be used by designers as inspiration. This tool stimulates creativity, helping to create unique collections that attract the attention of consumers looking for modern and innovative solutions in the world of fashion.

Generative Content Networks (GANs) are an advanced artificial intelligence-based technique that allows a computer to simulate the human imagination. Thanks to GAN, it is possible to generate new clothing designs based on images that are gaining popularity, especially on social media. The use of this technology enables real-time operation, which is particularly beneficial in situations where there is a high demand for specific products on the market. This, in turn, allows brands to quickly adapt to changing customer preferences. It is worth noting, however, that computer programs do not have the full ability to understand human behaviour, emotions, or the full needs of consumers. Their main task is to provide information that forms the basis for subsequent stages of clothing design, such as the selection of materials or fashionable styles. Artificial intelligence also does not have the subjective sense of aesthetics typical of humans [2].

The use of AI in the process of sorting waste for recycling

Innovative technology for intelligent sorting of textile waste was developed by the Refiberd team. This is a key tool in overcoming the main problem associated with recycling clothes - the lack of effective methods for accurately identifying their composition. Thanks to a patented method based on artificial intelligence and a hyperspectral system, it is possible to direct as much as 70% of textile waste to recycling processes. In the first step, artificial intelligence helps quickly separate clothes by colour. Then, a camera placed above the textile waste belt transmits the image to a computer, which instantly recognizes the type of fibres present in the waste.

Thanks to this, intelligent sorting is able to separate clothes that can be recycled, eliminating those that contain polyester or nylon admixtures exceeding 2% of the fabric content. The identification process is carried out using a hyperspectral system that analyses the material's reaction to light - different components reflect light in different ways, which allows for precise classification of the material. After carefully identifying the material, machines cut the fabrics into shreds, clean them of impurities and transform them into threads [3].

Examples of the use of AI in the TCLF industry

Chat GPT helped prepare this paragraph. This is a real example showing the possibilities that AI offers for all people the use of artificial intelligence. Additionally, some of the photos used in this article are created using artificial intelligence. Below we present examples of aspects in which artificial intelligence can be used.

1. Design optimization: AI algorithms analyse fashion trends, customer preferences, and market data to optimize the design process in textile and clothing production. This leads to more targeted and successful designs.

2. Supply chain management: AI is employed to enhance supply chain efficiency by predicting demand, optimizing inventory levels, and improving logistics. This results in reduced costs and better responsiveness to market fluctuations.

3. Quality control: AI-powered computer vision systems are used for quality control in textile and footwear manufacturing. These systems can quickly identify defects, ensuring that only high-quality products reach the market.

4. Personalized customer experience: AI-driven recommendation engines analyse customer behaviour and preferences, providing personalized recommendations for clothing and footwear. This enhances the overall customer experience and increases satisfaction.

5. Predictive maintenance: AI is applied to predict machinery maintenance needs in the leather industry. By monitoring equipment conditions, AI can anticipate potential issues, reducing downtime and extending the lifespan of machinery.

6. Smart textiles: AI is integrated into the development of smart textiles, where fabrics are embedded with sensors and connected devices. This innovation allows for the creation of responsive and adaptive clothing with applications in healthcare, sports, and beyond.

7. Automated production planning: AI algorithms assist in optimizing production schedules, taking into account various factors such as machine efficiency, resource availability, and order priorities. This leads to more efficient and streamlined production processes.

8. Virtual try-on solutions: AI-powered virtual try-on solutions use computer vision to allow customers to virtually try on clothing and footwear items before making a purchase. This reduces returns and enhances the online shopping experience.

Summary

The introduction of artificial intelligence to the TCLF industry is not only an adaptation to market changes, but a real revolution that is transforming the way clothes are designed and production is carried out. Thanks to this, this sector can not only meet consumer expectations, but also conduct business in a more effective, innovative and sustainable way. It is this trio of values that makes the use of artificial intelligence a key factor determining the future of the TCLF industry.

In a short time, traditional design and production methods may be insufficient compared to the benefits offered by artificial intelligence. In the context of production, the benefits of using artificial intelligence may include detecting problems, automatically responding to them, reducing the number of errors and reducing costs. Additionally, cooperation between humans and robots has become more effective in recent years, allowing employees to focus on more analytical and creative tasks. In the area of forecasting fashion trends and demand, artificial intelligence allows brands to adapt to changing customer preferences. In the context of design, artificial intelligence is presented as a tool that analyses data about trends, consumer preferences and cultural influences, helping designers predict the popularity of patterns and styles.

References

[1] https://polskiprzemysl.com.pl/technologie/przemysl-40-w-produkcji/ [access: 18.01.2024] [2] https://ciuchyimoda.pl/sztuczna-inteligencja-w-branzy-mody/ [access: 18.01.2024] [3] https://fashionbiznes.pl/moda-na-start-up-jak-sztuczna-inteligencja-moze-wspomoc-recykling-odziezy/ [access: 18.01.2024]

BY LIT Lukasiewicz - Lodz Institute of Technology