Abstract
Today, the management of the inventory used in the aircraft maintenance-repair industry is an important issue. Spare parts inventory, in other words component inventory, constitutes the main capital resource of this type of companies. For this reason, it is an important and sensitive issue for organizations engaged in aircraft maintenance to effectively manage their spare parts stock. Effective and rational management of spare parts inventory will provide companies with significant cost advantages. While trying to increase service levels, companies aim to keep their inventory costs at minimum levels. In order to effectively manage the spare parts inventory, first of all, the demand forecast for the future must be made correctly. For this, techniques suitable for the part structure should be used. The next step after forecasting is to keep stock at a sufficient level of confidence to avoid running out of stock in the future. Because of this, demands are formulated by fitting distributions. In this study, component data of a local company that provides maintenance and spare parts services to the aircraft of airline companies in the aviation maintenance and repair sector was used. Demand patterns related to the data set were examined and discrete forecasting methods were applied to them. Afterwards, comparisons were made by using various distributions to determine the amount of spares that should be kept in stock. The results were interpreted and evaluated. It is assessed that this study will shed light on and benefit organizations operating in the aviation sector and other sectors in terms of spare part stock management and demand forecasting.
Publisher
Turk Hava Kurumu Universitesi
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