Reducing Inventory Costs in Uncertain Supply Chains: A JIT and Stochastic Lead Time Model

This study explores a production-inventory model that integrates stochastic lead times and Just-In-Time (JIT) setup costs, aiming to optimize inventory management in environments characterized by demand variability and uncertain supply chains. The model addresses the critical trade-offs between holding costs, setup costs, and stockout risks, particularly under conditions where lead times are unpredictable. By incorporating JIT principles, the model reduces unnecessary inventory while maintaining high service levels, thereby minimizing total costs. Through the application of this model, optimal order quantities and safety stock levels are determined, which balance the need for inventory availability against the costs of frequent setups and the risk of stockouts. Sensitivity analysis further highlights the robustness of the model under varying cost parameters, providing insights into effective inventory control strategies that align with modern production requirements. This model offers a practical framework for companies looking to streamline their inventory practices while navigating the complexities of global supply chains.