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Forecasting and Inventory Management for Spare Parts: An Installed Base Approach

  • Stefan Minner
Chapter

Abstract

High demand variability and uncertainty that is driven by different phases of a product’s and its critical components life-cycles make spare parts demand forecasting and safety inventory management a major challenge. Mainstream stochastic inventory management approaches for spare parts make use of distributional assumptions for demands. In reality, distributions and their parameters are hardly known and need to be estimated. In this paper we pursue a causal demand modeling approach that combines theoretical models from reliability and inventory theory to derive improved service parts demand forecasts. Based on a small simulation experiment we illustrate the benefits of this accurate but more complex approach over simple time series based forecasting techniques and forecast error driven safety stock approaches for different life-cycle patterns and different phases of a product life-cycle.

Keywords

Inventory Management Service Level Agreement Spare Part Replacement Policy Exponential Smoothing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.University of ViennaViennaAustria

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