This document discusses the application of artificial intelligence (AI) in the textile industry, highlighting its role in enhancing production quality, reducing operating costs, and optimizing manufacturing processes. It outlines various AI techniques, including expert systems and artificial neural networks, which have begun to significantly impact areas such as fabric inspection and garment planning. The document emphasizes the importance of integrating AI to leverage data for improved decision-making and efficiency in textile production.

1. Welcome To Our Presentation
Presentation Topic:
Artificial intelligence in Textile Industry
Students Name & ID
Md Mosfikul Islam (08)
Asif –Bin Sayed (10)
Imran Hossen (11)
Rayhan Chowdhury (12)

2. Artificial intelligence
 Definition:
AI (artificial intelligence) is the simulation of human
intelligence processes by machines, especially
computer systems. These processes include
learning (the acquisition of information and rules for
using the information), reasoning (using the rules to
reach approximate or definite conclusions) and self-
correction. Particular applications of AI include
expert systems, speech recognition and machine
vision.

3. Applications of Artificial
intelligence
 AI in healthcare.
 AI in business
 AI in education
 AI in finance
 AI in law.
 AI in manufacturing

4. Artificial intelligence in Textile
Industry
 Artificial intelligence is becoming an important tool
for the processors to enhance quality, increase
production, lower operating costs and exercise in-
house control over production amounting to shorter
lead times.

5.  Textile industry in developed countries has
started exploiting artificial intelligent (AI)
techniques to their advantage. It is time that we
should use these techniques. AI systems are one
of the hopeful benefits available to textile
industry to integrate the elements such as
production, quality, cost, information, statistical
process control, and just-in-time manufacturing.
The textile industry must constantly seek to
improve quality, increase production and lower
operating cost. A decade ago, the main
emphasis was only on production but not any
more. Now along with the production, quality,
cost, information, statistical process control, just-
in-time manufacturing and computer integrated
manufacturing all play an equally important role.

6.  AI techniques transform large amounts of
quantitative data into intelligible classification, by
spotting trends and patterns. Until recently the
primary means of spotting trends was through the
statistical methods such as statistical clustering and
regression. Now, AI techniques are in many cases
outperforming traditional statistical techniques.
Textile industry and research institutions have
started realising the potential of these techniques,
especially in the areas such as fabric inspection and
planning in garment manufacturing, where even very
marginal improvements in performance translate into
large financial gains.

7. Classification of Artificial
Intelligence
AI systems can be broken into several different disciplines.
They are each unique, but often they intermix to accomplish a
programming task. The different disciplines are:
1. Expert systems,
2. Artificial Neural Networks (ANN),
3. Fuzzy logic,
4. Genetic algorithms and
5. Natural language.
Among these, expert systems and artificial neural networks are
finding application in textile industry.

13. Artificial intelligence in the
colour and textile industry
INTRODUCTION
The use of computers in the colour textile industry dates
back to 1960s. A significant number of papers have been
published over the years describing the application of
computer control in various fields of textiles including fibre
production , yarn formation , fabric formation, and dyeing
processes and machinery. Although the term ' artificial
intelligence " was coined in 1956, it was during the last
decade of the 20th century that textile researchers actively
investigated its application in various fields.

14.  Some earlier developments in artificial intelligence
have been reported for the textiles industry . textile
finishing and the colour industry. One of the earlier
applications of artificial intelligence in textile
coloration was robotics , which was explored in the
quest for automation and control However , more
recently . artificial neural networks, fuzzy logic and
some expert or knowledge - based systems have
attracted the attention researchers in different
sectors of the colour and textile industry The aim of
this paper is to review some recent cations of
artificial intelligence in finding better solution app
various problems different areas of the colour textile
industry The intention and is to describe the
application rather briefly thorough of account specific

15. EXPERT SYSTEMS
 Expert systems ' is a branch of artificial
intelligence that makes extensive use of
specialized knowledge to solve problems at level
of a human expert . Feisenbaum has defined an
expert system as an intelligent computer program
that uses knowledge and inference procedures to
solve problems that are difficult enough to require
significant human expertise for their solutions. An
expert is a person who has expertise in a certain
area i.e the expert has knowledge or special
skills.

16. Wet processing & application
of artificial intelligence
 Artificial intelligence is becoming an important tool
for the processors to enhance quality, increase
production, lower operating costs and exercise in-
house control over production amounting to
shorter lead times.

17.  Textile industry in developed countries has started
exploiting artificial intelligent (AI) techniques to their
advantage. It is time that we should use these
techniques. AI systems are one of the hopeful
benefits available to textile industry to integrate the
elements such as production, quality, cost,
information, statistical process control, and just-in-
time manufacturing. The textile industry must
constantly seek to improve quality, increase
production and lower operating cost. A decade ago,
the main emphasis was only on production but not
any more. Now along with the production, quality,
cost, information, statistical process control, just-in-
time manufacturing and computer integrated
manufacturing all play an equally important role.

18.  AI techniques transform large amounts of
quantitative data into intelligible classification, by
spotting trends and patterns. Until recently the
primary means of spotting trends was through the
statistical methods such as statistical clustering and
regression. Now, AI techniques are in many cases
outperforming traditional statistical techniques.
Textile industry and research institutions have
started realising the potential of these techniques,
especially in the areas such as fabric inspection and
planning in garment manufacturing, where even very
marginal improvements in performance translate into
large financial gains.

19. Limitations of AI Systems
1. Requires a broad set of training examples,
which are not easily available in many cases.
2. Problems are encountered while determining,
the optimum number of training cycles, as there
are no prescribed set of guidelines for selection of
training algorithm or the number of neurons
hidden in the layers.
3. Validations outside the training range are
necessary for extrapolation.

20. Conclusion
 Artificial intelligence is now making its mark in
Textile industry. Developed countries have started
using them. One fabric inspection unit has been
made for commercial use by the User. Much
progress is going on in this field and in near
future it will become an important tool for the
processors, for enhancing quality, increasing
production, lowering operating costs and
exercising in-house control over production
amounting to shorter lead times.