Intelligent Inventory and Knowledge Management in Healthcare Supply Chains

In this paper, the significance of supply chain management in healthcare logistics is emphasized by addressing the challenges of fluctuating demand and controlled drug production. To overcome these issues, the proposed system monitors the quantity of manufactured drugs through a combination of centralized and individual hub establishments that manage product distribution efficiently. An Artificial Intelligence (AI)-based automatic product clustering mechanism is integrated to analyze demand expectations and associated risk factors. The clustered products are then systematically arranged, and the internal connectivity between local suppliers is optimized to ensure minimal demand imbalance. Furthermore, to enhance the stability of the healthcare supply chain, proportional connections among hubs are evaluated, enabling data-driven and optimized decision-making. The performance of the proposed AI model is validated using four case studies, demonstrating its capability to achieve high connectivity and scalability. The model can be implemented in real time with a minimal operational cost of approximately 1635 dollars, confirming its practicality and cost effectiveness.