INVENTORY COST MINIMIZATION OF SPARE PARTS IN AVIATION INDUSTRY

Abstract

Due to high competition in the aviation industry, cost reduction comes into prominence and becomes more critical each day. An efficient maintenance and spare part inventory management system that operates based on a reliable demand forecasting mechanism can significantly reduce operation costs. However, the conventional forecasting methods in the literature are insufficient to estimate the quantity and occurrence times of the non-smooth demand. When cost minimization is directly targeted, these traditional forecasting methods often give misleading results. This study aims to provide an inventory cost management framework for irregular demand in the aviation industry. It compares recent non-smooth demand forecasting techniques with conventional ones by employing cost-based performance measures to minimize cost. The research with 100 different stock keeping units from the inventory of a commercial airline revealed that non-traditional methods are still in their development phases and need further improvements.