Applications of spare parts management in an international tv manufacturing company

The aim of this study is to reduce inventory and transportation costs at the spare parts warehouse of a TV manufacturing company. This aim can be reached by proper forecasting method and optimum storage of the spare parts. In this concern, first, features of spare parts and complexities in spare parts management are explained. Then, related forecasting methods are introduced and compared. In the analysis, we employ Trend Analysis, Single Exponential Smoothing, Double Exponential Smoothing and Auto-Regressive Integrated Moving Average (ARIMA) methods. The results are evaluated comparatively by using Mean Absolute Percentage Error. Finally, using the best forecast values, the automated warehouse system, which is called ?Kardex?, is optimized by using a linear programming model.