Service Parts Management

1. Front Matter

   Pages i-xiv

   PDF

2. Intermittent Demand: Estimation and Statistical Properties

   • Aris A. Syntetos, John E. Boylan

   Pages 1-30

3. Distributional Assumptions for Parametric Forecasting of Intermittent Demand

   • Aris A. Syntetos, Babai M. Zied, David Lengu, Nezih Altay

   Pages 31-52

4. Decision Trees for Forecasting Trended Demand

   • Natasha N. Atanackov, John E. Boylan

   Pages 53-87

5. The Impact of Aggregation Level on Lumpy Demand Management

   • Emilio Bartezzaghi, Matteo Kalchschmidt

   Pages 89-104

6. Bayesian Forecasting of Spare Parts Using Simulation

   • David F. Muñoz, Diego F. Muñoz

   Pages 105-123

7. A Review of Bootstrapping for Spare Parts Forecasting

   • Marilyn Smith, M. Zied Babai

   Pages 125-141

8. A New Inventory Model for Aircraft Spares

   • Michael MacDonnell, Ben Clegg

   Pages 143-156

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

   • Stefan Minner

   Pages 157-169

10. A Decision Making Framework for Managing Maintenance Spare Parts in Case of Lumpy Demand: Action Research in the Avionic Sector

    • M. Macchi, L. Fumagalli, R. Pinto, S. Cavalieri

    Pages 171-202

11. Configuring Single-Echelon Systems Using Demand Categorization

    • David Bucher, Joern Meissner

    Pages 203-219

12. Optimal and Heuristic Solutions for the Spare Parts Inventory Control Problem

    • Ibrahim S. Kurtulus

    Pages 221-231

13. Reliable Stopping Rules for Stocking Spare Parts with Observed Demand of No More Than One Unit

    • Matthew Lindsey, Robert Pavur

    Pages 233-249

14. Reactive Tabu Search for Large Scale Service Parts Logistics Network Design and Inventory Problems

    • Yi Sui, Erhan Kutanoglu, J. Wesley Barnes

    Pages 251-278

15. Common Mistakes and Guidelines for Change in Service Parts Management

    • Andrew J. Huber

    Pages 279-307

16. Back Matter

    Pages 309-311

    PDF

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.

• Forecasting
• Intermittent Demand
• Inventory
• Spare Parts
• Engineering Economics

From the reviews:

“Service Parts Management: Demand Forecasting and Inventory Control covers a wide spectrum of relevant issues on spare parts management. With contributions from some of the most active researchers in this field, the book provides a great foundation for academics who want to explore this field in detail and offers useful advice to managers. … In conclusion, the book offers practitioners and researchers a reasonably complete and good overview of relevant issues in spare parts management.” (Ruud Teunter, Interfaces, Vol. 42 (1), January-February, 2012)

• , Department of Management, DePaul University, Chicago, USA

  Nezih Altay

• , Robins School of Business, University of Richmond, Richmond, USA

  Lewis A. Litteral

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.

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