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September 5, 2025Open Access

Predictive Supply Chain Analytics: MIS-Integrated AI Models for U.S. Manufacturing Resilience

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This analysis demonstrates a 35% improvement in demand forecasting in U.S. manufacturing, highlighting robust MIS integration with AI models.

The proposed framework enhances supply chain resilience by improving decision-making with AI-driven analytics.
Experimental results indicate a 35% improvement in demand prediction accuracy and a 22% reduction in operational delays.
Machine learning techniques are utilized to create a predictive model for effective risk assessment and inventory optimization.
Integrating MIS with AI models significantly enhances visibility and agility in supply chain management.

Mohammed Tafiqur Rahman (2025) studied this question.

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This analysis demonstrates a 35% improvement in demand forecasting in U.S. manufacturing, highlighting robust MIS integration with AI models.