Application of Artificial Intelligence (AI) in Textile and Apparel Industry
Introduction:
Today Artificial intelligence is becoming an important and powerful tool for manufacturers to improve quality, increase production, minimize operating costs, and exercise in-house control over production amounting to lesser lead times. Even, many developed countries have started implementing artificial intelligence (AI) techniques to their advantage. It is time for everyone to use this tool. AI systems are one of the hopeful benefits available to the textile and apparel industry to blend elements such as production, quality, cost, information, statistical process control, and just-in-time manufacturing.
What is Artificial Intelligence (AI)?
Artificial intelligence refers to a simulation of human intelligence in smart machines which are programmed to think like humans, and mimic their actions. It is a wide-ranging branch of computer science which concerned with building machines capable of performing tasks that typically require human intelligence. The term AI can also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Why AI Used in Textile Industries?
The high demand for the quality increased leading to the application of automated artificial intelligence in textile industries recent years. The automation with applications of artificial intelligence in textile production is becoming much popular due to the technical developments and the use of modeling and simulation.
Artificial intelligence (AI) is gaining impetus over the last two decades, in the textile industry. The automation of various instruments by the application of artificial intelligence in spreading, cutting, sewing, and material handling can reduce the production cost and minimize faults in the overall textile production.
In many instances of textiles production, there are huge chances of error. The application of the AI can deal with the production process without error. As a result, over the last decade, the use of AI is rapidly growing in textile industries for various applications.
Application of AI in the Textile and Apparel Industry:
Yarn Manufacturing:
Nowadays, due to the emergence of AI, each phase of the production process has been changed directly from blow room to carding, drawing, lap formation, combing, speed framework, ring spinning, winding, packing, and conditioning. Now whatever the required production parameters are there with little human participation are recognized and finalized by AI-based control panels.
It also has the benefit of cost reduction and quality. It is also found that the yarn prediction by enumerating spins has gained more precision. Because of the application of AI, it has minimized yarn grading mistakes to as much as 60%, which directly leads to enhanced textile grading. Due to AI, it’s possible to measure the physical characteristics of a fabric more easily and classify the comfort of textiles objectively.
Pattern inspection:
Fabric pattern may have multiple aspects such like: weaving, knitting, braiding, finishing, and printing, etc. By replacing visual inspection with vision-based inspection could help manufacturers avoid human fatigue and errors in the detection of novelties and defects. AI techniques like ANN are applied for defect identification in fabric inspection of the textile industry. The fabric picture to be analyzed is obtained from the image acquisition system and saved in relevant standard image format (.JPEG, .JPG, .PNG etc.). Different Multi-Layer back propagation algorithm is used to train and test this ANN system. The system learns the weaving pattern, yarn properties, colors and tolerable imperfections from these images.
Fabric grading:
In the textile industry, it is possible to grade fabrics more objectively and to manufacture more consistent results due to machine learning. Because of the AI role in the garments industry, the fine, solid, and staple fiber lengths are more precisely determined. For e.g., nowadays, wise eye technology is available which is capable of detecting fabric faults. Today, for monitoring the fabric accurately, a high-performance LED lighting device is produced by the machine with a powerfully coupling high-resolution camera to be mounted up to 90% by an electric motor.
CAD systems:
One of the important steps in textile production is pattern making. In this process, basic patterns are made by the designers and subsequently digitized to computer. Various CAD software are used in the textile industry for pattern-making, digitizing, grading, and marker planning. The CAD software helps in achieving high productivity and improved quality of the product.
Sewn seam:
In the sewing process, basically, seams and stitches are used to join two or more pieces of fabric together. There is an important attribute called “sew-ability” which simply means the seam formation and the performance of the seam. The factors that can affect sew-ability are fabric low-stress mechanical properties such as tensile, shear, bending, etc. So, here AI comes into the picture, where it can be used to find the sew-ability of different fabrics during production.
Production planning and control:
Production planning and control (PPC) coordinates between various departments of production so that delivery dates can met and buyer orders are delivered on time. AI can be used to solve of the machine layout, operation assignment, sewing line balancing, etc. AI can help in achieving the main purpose of PPC.
Supply Chain Management (SCM):
Supply Chain Management in the textile and apparel industry includes the flow of fibers, yarns, fabrics, garments, trims, and accessories between different production points or to final retail. SCM combines various business processes, activities, information, and resources for creating and enhancing value for the buyers. So, with the help of AI, this function can be performed very smoothly and can manage the cost and business competitiveness.
Final inspection:
The inspection of finished and semi-finished textile product during their production is essential to get fewer rejections. The final quality inspection of finished garments is mainly done by experienced people, which is very time-consuming and may be influenced by the physical and mental condition of the inspector. As a result, automated AI inspection is essential to achieve the efficiency and accurate results. Automated inspection can be performed by the use of AI and image processing for inspection of the quality of the product.
Conclusion:
Even in industrialized nations, the use of AI in textile technologies is still not very common. Potential AI technologies could greatly help the production and quality control issues that plague the textile sector in emerging nations. The textile sector is increasingly using AI technologies. Being seen as being capable of accurately and rapidly handling complicated problems is essential to remaining competitive. Many tasks, including production and quality control, are mostly handled by human hands in the labor-intensive textile business. With AI innovation, efforts are undertaken to create solutions that will increase such activities’ efficiency and efficacy. The fundamental operations of detection, identification, inspection, grading, machine vision, prediction, etc. form the foundation of AI technology.
