Über den Autor
Nezih Altay is Associate Professor of Operations Management. He holds a PhD in Operations Management from Texas A&M University and an MBA from the University of Texas - Pan American. His research focusing on forecasting and inventory control of spare parts has been highlighted in major academic conferences and published in leading journals, such as the International Journal of Production Economics. His work in this area resulted in a Royal Society grant through which he started new projects on the management of spare parts with colleagues in the UK. Currently in the USA, he is in collaboration with the Defense Logistics Agency on improving service parts forecasts and inventory control. Dr. Altay sits on the editorial boards of Production and Inventory Management Journal and the International Journal of Services Sciences, and is an active member of APICS, POMS, DSI, ISM, and INFORMS. Lewis A. Litteral is a member of the faculty of the University of Richmond. He holds a PhD in Management Science from Clemson University, where he also earned a Master of Science degree in mathematical sciences with a concentration in statistics. He currently teaches courses in statistical analysis although he has taught a wide variety of other quantitative courses over the past 30 years. His current research interests include enterprise resource planning, forecasting intermittent demand, and statistical quality control. The common thread in this work is that it all lies at the intersection of information technology and operations management. His work in these areas has been published by various journals including Production and Inventory Management, Quality Engineering, the International Journal of Production Economics and the International Journal of Quality and Standards. Prior to beginning an academic career, he was employed by a large building materials supply company where his positions included all aspects of operations management, as well as sales.
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.
Provides an overview and detailed treatment on forecasting and inventory management of items with intermittent demand
Reviews service parts management comprehensively in a single volume
Guides researchers and practitioners in finding better management solutions to their problems