Improving Integrated Management of Industrial Enterprises Through Erp Systems: A Dynamic Inventory Control and AI-Assisted Decision Support Framework

This study proposes an organizational and economic framework for improving ERP-based integrated management in industrial enterprises, with particular emphasis on Uzbekistan's machinery manufacturing sector. It examines opportunities to enhance the integration of information systems, strengthen coordination among procurement, warehousing, and production operations, and improve the adaptability of conventional static inventory management policies. The proposed framework combines the integration of existing Enterprise Resource Planning (ERP) functions, multi-model bills of materials (BOMs), feedback from Manufacturing Execution Systems (MES), dynamic calculations of safety stock and reorder points, and artificial intelligence (AI)-assisted decision support under human supervision. An economic optimization model incorporates inventory holding costs, procurement costs, material shortage costs, and costs associated with production interruptions. Static and dynamic inventory management policies are compared using operational and economic performance indicators. The study presents a conceptual framework and an analytical evaluation methodology; empirical validation at the enterprise level requires actual production, inventory, and procurement data.