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(Group 5) Mid Evaluation

This document presents a study on the textile industry, utilizing AI-driven predictive models to analyze data and forecast trends in international markets. It highlights the growth of global textile exports, key exporting and importing countries, and the environmental impact of the industry. The study aims to provide insights for strategic planning and future growth in the textile sector.

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Muneeb igi
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0% found this document useful (0 votes)
28 views15 pages

(Group 5) Mid Evaluation

This document presents a study on the textile industry, utilizing AI-driven predictive models to analyze data and forecast trends in international markets. It highlights the growth of global textile exports, key exporting and importing countries, and the environmental impact of the industry. The study aims to provide insights for strategic planning and future growth in the textile sector.

Uploaded by

Muneeb igi
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© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Team Members:

Analyzing and
Forecasting Textile • Muhammad Umar

Industry Related • Raja Zain Ali


Data Using AI- • Shreiyar Ali
Driven Predictive
• Mujeeb Ur Rehman
Models
• Danish Hassan
Presented The
Title At Dow
University of
Health & Science
21 International
Conference on
Statistical
Sciences
Abstract
The textile industry is a fundamental pillar of the global
economy, employing millions of individuals worldwide and
contributing signifi cantly to international trade and export
revenues. This study utilizes AI techniques to analyze textile-
related data across a range of international markets. By
applying AI models, the study achieves highly accurate
forecasting results. The aim is to elucidate the dynamic trends
and performance of the global textile sector in major
international markets. This analysis provides valuable insights
into export patterns and supports strategic planning for future
growth in the textile industry.

Keywords: Textile Sector, Export Analysis, Moving Average


Forecasting, MINITAB Software, Export Performance Trend
Methodology
This study analyzes historical data to understand trends in the
textile industry. Key steps include:

Data Collection: Industry data is gathered from reliable sources on


production volumes, market dynamics, and environmental metrics.

Data Cleaning: Standardized by addressing missing values and


inconsistencies to ensure reliability.

Exploratory Analysis: Patterns in production growth, market


performance, and sustainability are identified using Python and
Excel.

Visualization and Graphs: Graphs will highlight key trends,


including production growth, market shifts, and environmental
impact, enabling a clearer understanding of the data. Tools like
Power BI and Excel charts are used for visual representation.
Global Textile Export
Trends (2015-2022)
• Global textile exports grew from $630 billion
in 2015 to $715 billion in 2022. A decline
occurred in 2020 due to the pandemic, but
recovery was strong by 2021.

• Global textile exports declined in 2016 due


to economic slowdowns, currency
fluctuations, intense competition, and
shifting consumer preferences. Additional
challenges like trade barriers and
geopolitical uncertainties further impacted
trade volumes.
Top Textile
Exporting
Countries (2022)
• China: $150 billion – Largest exporter
with cost-effi cient mass production.

• India: $37 billion – Rich in raw


materials and skilled labor.

• Bangladesh: $34 billion – Focus on


low-cost ready-made garments.

• Vietnam: $30 billion – Hub for global


apparel brands.
Top Textile
Importing
Countries (2022)
• USA: $120 billion – Largest market
due to high demand.

• Germany: $80 billion – Imports


luxury and industrial textiles.

• Japan: $70 billion – Specialized in


high-tech and advanced textiles.
Top Cotton
Producing Leading
Countries Producers
• China: 27.5 million bales –
(2022)
Integrates cotton into its textile
manufacturing.
• India: 26.2 million bales –
Leveraging its agricultural
capacity.
• USA: 18.5 million bales –
Focused on premium cotton
quality.
Fiber Production
Trends (2015-
2022)

• Total fiber production


grew from 90 million tons
in 2015 to 105 million
tons in 2022.

• Synthetic fibers (e.g.,


polyester) account for
over 70% of global
production.
Synthetic Fibers:
Global Fiber Production
• Trend: Synthetic fi ber production has shown
Forecast (2015-2029)
a steady increase from 63 million metric
tons in 2015 to approximately 75 million
metric tons by 2024.

• Forecast: Production is projected to grow


further, reaching about 84 million
metric tons by 2029..

Natural Fibers:

• Trend: Natural fi ber production, primarily


cotton, wool, and others, has remained
relatively stable, growing modestly from 30
million metric tons in 2015 to around 33
million metric tons in 2024

• .Forecast: Production is expected to show


slight growth, reaching about 34 million
metric tons by 2029.
Future Predictions
for Textile Market
Size (2023–2030)

• The graph illustrates a steady


increase in the global textile
market size from $1.8 trillion
in 2023 to over $2.6 trillion by
2030.

• This growth reflects a


consistent upward trend,
indicating significant market
expansion opportunities.
Environmental
Impact of the
Textile Industry
• Contributes 10% of global
carbon emissions.

• Significant water
consumption for cotton
farming.

• Pollution from synthetic


fibers and dyes.
Challenges Facing the Textile
Industry
References

• Bacchetta, M., & Bora, B. Industrial Tariff • Nayak, R.; Padhye, R. (Eds.) 5—Artifi cial intelligence and
its application in the apparel industry. In Automation in
Liberalization and the Doha Development
Garment Manufacturing; Woodhead Publishing: Sawston,
Agenda. WTO. UK, 2018; pp. 109–138. [Google Scholar]

• • Xue, Z.; Zeng, X.; Koehl, L. Artifi cial Intelligence Applied


Statista. Worldwide Textile Market Overview.
to Multisensory Studies of Textile Products. In Artifi cial
Trend Economy. Textile Trade Trends.
Intelligence for Fashion Industry in the Big Data Era;

• Trademap. Import & Export Dataset Thomassey, S., Zeng, X., Eds.; Springer Singapore:
Singapore, 2018; pp. 211–244. [Google Scholar]
• OEC. Global Textile Trade Analysis. • Akbar. (2013). Demand forecasting in textile industry-A
case study. Academic Press.
• WTO. Textile Trade Statistics.
• Brenton, P., & Hoppe, M. (2007). Clothing and Export
• International Journal for Textile Research. Diversifi cation: Still a Route to Growth for Low Income
Countries. Policy Research Working Paper No. 4343,
Sustainable Practices in Textiles. International Trade.
Thank you

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