Risk Management Strategies Based On Artificial Intelligence In The Textile Industry
DOI:
https://doi.org/10.55640/eijp-05-11-20Keywords:
Artificial intelligence, risk management, textile industry, machine learningAbstract
As global market dynamics, supply chain disruptions, and technological challenges increase uncertainty, effective risk management becomes crucial for textile enterprises. AI technologies such as machine learning, predictive analytics, and real-time data monitoring offer innovative solutions for identifying, assessing, and mitigating various operational, financial, and market-related risks. The study analyses how AI-based systems can enhance decision-making, optimize production processes, and reduce vulnerabilities in textile manufacturing, with a focus on practical implementation and expected outcomes.
References
World Bank. (2020). Uzbekistan: Modernizing the Textile Industry for Export-Led Growth. Washington, D.C.: World Bank Group. Retrieved from https://www.worldbank.org
Asian Development Bank. (2021). Economic Reforms and Industrial Diversification in Uzbekistan: Challenges and Opportunities in the Textile Sector. Manila: ADB Publications.
FAO & ILO. (2019). Sustainability and Labor Practices in Uzbekistan’s Cotton and Textile Industry. Rome: Food and Agriculture Organization of the United Nations.
United Nations Economic Commission for Europe (UNECE). (2022). Sustainable Textile and Apparel Value Chains in Central Asia: The Case of Uzbekistan. Geneva: United Nations.
Turaev, B., & Yusupova, G. (2018). Development of Textile Industry and Export Potential of Uzbekistan in the Context of Economic Liberalization. Journal of Central Asian Studies, 25(3), 145–160.
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