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Maintenance planning is a major aspect for the aircraft manufacturers and airlines. Not having adequate spare parts in the inventory for the scheduled maintenance could result in costly flight cancellation with a negative impact on airline performance. An excess of spare parts inventory, on the other hand, leads to a high holding cost. Since airline industries involve with a large number of parts and some of them are quite expensive, it is important to classify critical parts needed to be kept in the inventory with minimal system costs. This study focuses on classifying spare parts into three groups by using traditional, analytic hierarchy process (AHP), and data envelopment analysis (DEA) methods based on factors associated with spare parts: unit price, usage rate, lead time, and reliability. Results show that it is advantageous to use DEA method to classify the inventory.

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