Improving Gear Provisioning Efficiency at the Individual Issue Facility (IIF) Throught Size-Specific Inventory Simulation

Abstract

As the U.S. expeditionary force in readiness, the Marine Corps depends on properly sized, serviceable individual combat equipment to maintain readiness. The Individual Issue Facility (IIF) currently stocks gear using sizing tariffs based on outdated anthropometric data, and replenishment occurs irregularly and without a consistent reordering policy. These practices contribute to shortages of high-demand sizes and excess inventory of others. This thesis uses helmets as a representative case and analyzes three years of Enterprise Logistics Management System (ELMS) issue and return data, developing a discrete-event simulation (DES) using SimPy to model the flow of helmets through the IIF. The data reveals size-demand patterns, return behavior, and loss rates, which are used to derive realistic model inputs. Baseline test results show that the model closely matches observed system behavior, and sensitivity tests demonstrate how longer retention periods and seasonal arrival patterns affect inventory levels. This research shows that a DES approach provides a practical tool for evaluating reorder strategies and improving size-specific inventory management that can be broadly applied to similar logistics systems facing long lead times, irregular returns, and size-specific demand. The model allows decision-makers to assess alternative policies and ‘what-if’ scenarios in advance, giving them a data-driven basis for setting reorder points and determining starting inventories.