062 – “Next Generation Supply Chain Modeling”

Author: CDR Walter W. Kulzy
Company: NAVSUP Weapon Systems Support
Phone: (717) 605-4873
Email: walter.kulzy@navy.mil

Investing in the right material at the right time to support fleet requirements, both planned and unplanned, is the primary responsibility of the Navy’s Program Support Inventory Control Point (PSICP), Naval Supply Systems Command Weapon Systems Support (NAVSUP WSS). WSS maintains over $34B in inventory managing 500K annual requisitions across Naval aviation, maritime, and expeditionary units. This material supports more than 3,700 operational aircraft and 286 ships and submarines.

WSS managed material has a diverse demand profile with many customers; shipboard maintainers, supply departments, and depots. While some material has predictable steady customer demand in the hundreds or thousands of units every year, a large proportion of items have irregular, episodic, or very limited demand, with intervals between demands often measured in years. Legacy modeling approaches relying on planning factors, forecasts, and closed form equations have not performed well on a large proportion of Navy’s low or highly variable demand items.

Leveraging the computational power and the volume of transactional data from the Navy Enterprise Resource Planning (NERP), WSS is building with Naval Postgraduate School (NPS) the next generation of Navy owned and developed inventory models. The new Wholesale Inventory Optimization Model v5.0 (WIOM) combines an advanced discrete event simulation assessment tool with a sophisticated optimization model to prescribe recommended inventory investment strategies for Navy wholesale material.

The simulation component of WIOM, Distributed Requirements Planning Simulation (DRPSim), provides a predictive capability by analyzing thousands of “what-if” future scenarios by combining current asset postures with the NERP’s transactional data to include demand, procurement, and repair times. The simulation architecture is not reliant on planning factors, forecasts, or closed form equations, making it revolutionary in analyzing the performance of items with unpredictable demand patterns. The simulation output provides multiple measures, to include but not limited to, material availability, total inventory, and contracting workload.

The WIOM optimization engine uses a sophisticated linear program, which takes into account trade-offs between metrics of interest and prescribes an inventory plan best able to meet the required objectives. The multi metric approach in WIOM 5.0 allows for more efficient and effective inventory policy tradeoffs to be made between often competing organizational objectives.