Titlebook: Service Parts Management; Demand Forecasting a Nezih Altay,Lewis A. Litteral Book 2011 Springer-Verlag London Limited 2011 Forecasting.Inte

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A Review of Bootstrapping for Spare Parts Forecasting,rk using bootstrap compares results to Croston. After describing several models that use bootstrap for spare parts inventory forecasting, a few areas for more work are mentioned. Details related to the implementation of the bootstrapping methods discussed in this chapter are presented in Appendix A.

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Optimal and Heuristic Solutions for the Spare Parts Inventory Control Problem,st obtained from our procedure based on the Archibald and Silver’s optimizing algorithm. For some problems with very small mean demand and small average number of demand occurrences, finding the optimal solution required an inordinate amount of CPU time, thus justifying the need to use heuristics.

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management comprehensively in a single volume.Guides researcWith the pressure of time-based competition increasing, and customers demanding faster service, availability of service parts becomes a critical component of manufacturing and servicing operations. Service Parts Management first focuses on

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Book 2011nent of manufacturing and servicing operations. Service Parts Management first focuses on intermittent demand forecasting and then on the management of service parts inventories. It guides researchers and practitioners in finding better management solutions to their problems and is both an excellent

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The Impact of Aggregation Level on Lumpy Demand Management,and distributes on each single company serving a specific market. The supply chain structure is also a significant cause of demand unsteadiness: the bullwhip effect (Lee et al. .) is a common phenomenon in different industrial contexts, leading to an increase in the variability of the demand over supply chain stages.

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

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Reliable Stopping Rules for Stocking Spare Parts with Observed Demand of No More Than One Unit, If a product has not had a demand over a specified duration of time, its demand would be projected to be zero based on many of the popular forecasting models, such as simple exponential smoothing or moving averages. Yet, this product may still be required and be worth carrying, particularly if the inventory cost is well managed.

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