Inventory cost reduction for spare parts case study for dry pet food production company

Abstract

Inventory management played a crucial role in reducing costs and enhancing production efficiency. This study examined inventory management using classification methods such as FSN Analysis and ABZ Classification. The research employed the OUL-T Model and QR Model to determine optimal inventory levels, aiming to improve spare parts management and reduce associated costs. The study was based on a case study of a company operating in Thailand, focusing on analyzing five years of historical data and applying Monte Carlo simulation to forecast future demand. The findings revealed that classification and demand forecasting significantly enhanced inventory management accuracy and reduced the cost of excess inventory by 543,139 THB. Furthermore, the results of this research could be adapted for other industries to improve inventory management efficiency.