Transmission Spare Parts Inventory Management Strategy Based on Poisson Demand Estimation and Inter-Warehouse Coordination Through Risk Pooling

Abstract

Spare parts inventory management, particularly for slow-moving transmission components, presents a significant challenge for utility companies due to unpredictable and infrequent demand patterns, high asset value, and the need to maintain operational reliability. Excessive inventory levels tie up substantial working capital, increase carrying costs, and elevate the risk of obsolescence, whereas insufficient stock availability may result in equipment downtime and service disruptions. This study aimed to optimize inventory management for slow-moving transmission spare parts by balancing operational reliability and inventory cost efficiency over a ten-year planning horizon. A Poisson-based forecasting approach, using equipment failure rates as the primary demand driver, was implemented. Additionally, three risk-pooling schemes (no risk pooling, full risk pooling, and partial risk pooling) were evaluated through simulation to assess fill rates, disruption response, and inventory holding costs. The Poisson-based approach reduced projected spare parts requirements by 36% and lowered ending inventory levels by 55% compared with the existing policy. The simulation results indicated that while no risk pooling provided higher fill rates and full risk pooling minimized holding costs, partial risk pooling achieved the optimal trade-off across key performance metrics. Implementing a Poisson-based demand model combined with partial risk pooling enables organizations to significantly reduce procurement expenditures and inventory holding costs without compromising operational reliability.