In recent years, artificial intelligence (AI), including technologies such as machine perception, machine learning, and machine thinking, has been applied locally in certain areas of the textile industry, achieving initial progress and establishing a solid foundation. In particular, in the past two years, a series of developments and applications have been carried out in areas such as intelligent manufacturing, attracting significant attention.
1. Intelligent Manufacturing
AI technology promotes the development of new models, methods, and systems in intelligent manufacturing. It is a core technology and the most widely used area for intelligent textile manufacturing. These areas include production process feature extraction, production process optimization, production planning and scheduling, equipment scheduling algorithms, production process optimization and control, quality inspection and management, intelligent integration of production operations and handling, and equipment fault location and diagnosis. Remarkable results have been achieved in areas such as product feature recognition, quality inspection, and production logistics.
In current textile intelligent manufacturing projects, intelligent functions such as knowledge acquisition, knowledge base construction, deep learning, and optimized decision-making are still lacking. These functions require further development in the next phase. Building on automation, digitization, and networking, we must raise the level of intelligence to truly achieve intelligent manufacturing.
II. Textile Analysis and Design
In recent years, artificial intelligence technology has been applied to textile design, fabric defect identification and analysis, fabric performance evaluation, cotton impurity classification and rating, pilling grading, and dye uptake calculation. It can also be used to analyze and predict various textile properties, such as breathability, wrinkle resistance, and abrasion resistance. For example, the use of machine vision and machine learning technologies to detect and analyze defects, color differences, patterns, and pilling in printed and colored fabrics can overcome long-standing technical difficulties and significantly improve identification and analysis capabilities.
In the next phase, artificial intelligence technology will be introduced into textile design systems, empowering them with logical reasoning and decision-making capabilities. Driven by computers, relying on knowledge bases and autonomous learning systems, they will integrate a large number of design examples, experience, and guidelines, continuously narrowing the scope of exploration based on design goals to achieve the desired design results.
III. Trend Research
Based on the vast amount of data currently accumulated online, artificial intelligence technology has great potential for development in the field of textile and apparel fashion trends. For example, by analyzing massive amounts of photos with computer vision and image processing technology, users' preferred colors, patterns, and styles can be quickly retrieved. For example, based on consumer clothing color preferences and consumption habits, the colors commonly worn by different age groups can be analyzed, summarizing different popular colors. In terms of trend forecasting, the application of artificial intelligence technology will significantly outperform current modeling methods. Not only will it accurately solve many complex problems, it will also become an ideal tool for the next stage of innovation in textile and apparel fashion.
IV. Expert Systems
The "Outline for Scientific and Technological Progress in the Textile Industry during the 12th Five-Year Plan Period" proposed the application of artificial intelligence technology to develop and establish expert systems for the textile industry and a textile macroeconomic decision-making support system. Work has already been carried out at the industry and enterprise levels in areas such as process design, quality management, enterprise diagnostics, and textile knowledge bases, and some experience has been gained. In the coming years, with the wider application of machine learning methods, expert systems will be a key component of artificial intelligence applications in the textile industry. They will pool the knowledge and experience of industry experts, accumulate and update a wealth of information and technologies, address key issues in textile product design, processes, raw materials, production, and equipment, and provide effective support for related decision-making.
