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AI-powered quality control systems can identify defects and anomalies in textile products, ensuring consistent quality standards and reducing the need for manual inspection. AI algorithms can analyze historical quality data to identify root causes of defects and provide insights for process improvements, leading to enhanced product quality. AI technology plays a role in inventory management in textile factories. AI algorithms can analyze sales data, market trends, and production capacity to optimize inventory levels and ensure timely replenishment. AI-powered systems can assist in demand forecasting by analyzing historical sales data, customer trends, and external factors, enabling textile factories to plan production and inventory levels accordingly. AI algorithms can analyze customer feedback and market trends to identify emerging patterns and preferences, enabling textile factories to develop products that align with customer expectations. AI technology enables intelligent pricing strategies in textile factories. By analyzing market data, competitor prices, and customer behavior, AI algorithms can suggest optimal pricing strategies to maximize profitability.

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