Fabric Pattern Inspection
Some AI techniques like Artificial Neural Networks can be used to detect defects in various processes such as fabric inspection, knitting, weaving. Inspection of fabric patterns at various stages like knitting, braiding, weaving etc. by AI techniques helps reduce the workload and reduce pattern errors with precision. Also an AI-enabled view- based inspection can improve efficiency and reduce human error. An example of AI technology is Cognex ViDi which can automatically check fabric patterning.

Color Management
Color matching is another area where artificial intelligence is being used in the textile
industry to ensure that the original color design matches the color of the finished textile.
The Color of any product is an important factor in the textile industry. The Appearance of
a textile product indicates its quality. If the color of the product is not correct, it is judged
as unsatisfactory. To solve this problem, AI techniques can be used which helps in
improving accuracy and efficiency.
AI in Design
Designers in the textile industry can use AI to create new designs. Designers working
with AI analyze data about customer preferences and trends to create new ideas that are
more likely to sell well. Ai’s speed and efficiency allow designers to create designs faster
and more cheaply.
Yarn Manufacturing
Manufacturing has been completely transformed by the use of AI in almost every process
of yarn production, from blow room, carding, drawing to packing. AI-based control panels
have also helped in increasing the quality and reducing the cost of production by setting
all the necessary parameters of production. Yarn grading errors have been reduced
through the application of artificial intelligence which has enabled better fabric
grading. As a result, the physical properties of the textile are improved.
Quality Control
Quality control is traditionally achieved through physical inspection of skilled workers in
the textile industry. There are many uses of AI to ensure uniformity and quality in this
sector such as yarn manufacturing and garments. Top production and quality are
ensured with the latest machines and technologies like TPI Tester, Autoburst 70, Digital
Tachometer CE, Moisture Meter Digital and Stroboscope. Premier Art-II instruments are
used to test raw cotton properties like MIC, color, length, strength, uniformity etc. Uster
Tetser-6 is a complete test center system used for process measurement and control
from carding to winding.
Sales and Marketing
The use of AI in sales and marketing of textile products has become increasingly
important in today’s fast-paced business environment. Using AI in sales can analyze
large amounts of customer data to identify potential customers. Also facilitates the sales
process by promoting products to customers. It uses software tools that process large
datasets to save time, sell efficiently and increase conversions.
Fabric Grading:
Various AI techniques in the textile industry have enabled excellent fabric grading
processes for consistent results. For example, through the use of artificial neural networks
it will be possible to accurately measure the fineness, strength and length of the fiber.
AI in Pattern Generation
An important step in textile production is pattern making which enables computerized
pattern making by designers. Designers help design the structure of the pattern and also
provide 3-D images of the fabric and design which makes visualization easier. CAD
software is used in the textile industry for digitizing, pattern making, grading and marker
planning which helps in increasing productivity and improving product quality.
Supply Chain Management
Supply chain management in fashion integrates various business processes, activities,
information and resources. Standard supply chain management provides a smooth flow
of materials between retailers and manufacturers that can manage costs and business
competitiveness. Hence it requires large storage space, transportation, a well-equipped
warehouse, documentation etc. AI-enabled technologies such as NLP, virtual
assistance; AI robotics etc. can help automate transportation and packaging in the textile
industry.
Challenges
Although the use of artificial intelligence is very beneficial for our textile industry but still it
has some disadvantages. The biggest problem is that many people involved in the textile
industry will lose their jobs. In addition, there is a shortage of skilled manpower in the use
of artificial intelligence machines. These are the issues to be faced in the use of artificial
intelligence in the textile industry. As a solution to these problems, first of all we have to
arrange employment in other industries or elsewhere for the manpower involved in the
textile industry whose jobs will be reduced due to the use of artificial
intelligence. Secondly, those who do not have the skills to use artificial intelligence should
be trained through various workshops.