Data Analysis for Inventory Management in a Multi-echelon Supply Chain

The inventory management of multi-echelon repairable items systems is a major problem as these items are relatively expensive and slow-moving, so, inventory management can be a real problem due to mathematical complexities. In this work, a study was performed in a complex high-value products manufacturer, whose repairable items are both expensive and critical. Data of parts’ failure, storage and repair system structure were collected. We present statistical analysis methods that can be exploited in data reduction and classification to facilitate the inventory management procedures. Statistical methods used in this work include; DOE, regression analysis, distribution fitting, and ARIMA models.