Service Parts Management [electronic resource] : Demand Forecasting and Inventory Control /
Altay, Nezih.editor.
Litteral, Lewis A.editor.
With 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 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 reference for key concepts and a leading resource for further research. Demand forecasting techniques are presented for parametric and nonparametric approaches, and multi echelon cases and inventory pooling are also considered. Inventory control is examined in the continuous and periodic review cases, while the following are all examined in the context of forecasting: • error measures, • distributional assumptions, and • decision trees. Service Parts Management provides the reader with an overview and a detailed treatment of the current state of the research available on the forecasting and inventory management of items with intermittent demand. It is a comprehensive review of service parts management and provides a starting point for researchers, postgraduate students, and anyone interested in forecasting or managing inventory.
Description based upon print version of record.
Includes bibliographical references and index.
1. Intermittent Demand: Estimation and Statistical Properties -- 2. Distributional Assumptions for Parametric Forecasting of Intermittent Demand -- 3. Decision Trees for Forecasting Trended Demand -- 4. The Impact of Aggregation Level on Lumpy Demand Management -- 5. Bayesian Forecasting of Spare Parts Using Simulation -- 6. A Review of Bootstrapping for Spare Parts Forecasting -- 7. A New Inventory Model for Aircraft Spares -- 8. Forecasting and Inventory Management for Spare Parts: An Installed Base Approach -- 9. A Decision Making Framework for Managing Maintenance Spare Parts In Case of Lumpy Demand: Action Research in the Avionic Sector -- 10. Configuring Single-Echelon Systems using Demand Categorization -- 11. Optimal and Heuristic Solutions for the Spare Parts Inventory Control Problem -- 12. Reliable Stopping Rules for Stocking Spare Parts with Observed Demand of No More Than One Unit -- 13. Reactive Tabu Search for Large Scale Service Parts Logistics Network Design and Inventory Problems -- 14. Common Mistakes and Guidelines for Change in Service Parts Management.
With 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 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 reference for key concepts and a leading resource for further research. Demand forecasting techniques are presented for parametric and nonparametric approaches, and multi echelon cases and inventory pooling are also considered. Inventory control is examined in the continuous and periodic review cases, while the following are all examined in the context of forecasting: • error measures, • distributional assumptions, and • decision trees. Service Parts Management provides the reader with an overview and a detailed treatment of the current state of the research available on the forecasting and inventory management of items with intermittent demand. It is a comprehensive review of service parts management and provides a starting point for researchers, postgraduate students, and anyone interested in forecasting or managing inventory.
Engineering economics.
Engineering economy.
Manufactures.
Operations research.
Decision making.
Engineering Economics, Organization, Logistics, Marketing.
Manufacturing, Machines, Tools, Processes.
Operations Research/Decision Theory.