Inventory management for spare parts

Management Science

Keywords

Intermittent Demand, Spare parts, Forecasting, Stock Control

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Published

Standard

Inventory management for spare parts. / Syntetos, Aris A.; Boylan, John.
Proceedings of the 2nd World Conference on POM and 15th Annual POM Conference. 2004. ( World Conference on Production and Operations Management).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Syntetos, AA & Boylan, J 2004, Inventory management for spare parts. in Proceedings of the 2nd World Conference on POM and 15th Annual POM Conference. World Conference on Production and Operations Management, 2nd World Conference on POM, 15th Annual POM Conference, Cancun, Mexico, 30/04/04. <http://www.pomsmeetings.org/ConfProceedings/002/POMS_CD/Browse%20This%20CD/PAPERS/002-0173.pdf>

APA

Syntetos, A. A., & Boylan, J. (2004). Inventory management for spare parts. In Proceedings of the 2nd World Conference on POM and 15th Annual POM Conference ( World Conference on Production and Operations Management). http://www.pomsmeetings.org/ConfProceedings/002/POMS_CD/Browse%20This%20CD/PAPERS/002-0173.pdf

Vancouver

Syntetos AA, Boylan J. Inventory management for spare parts. In Proceedings of the 2nd World Conference on POM and 15th Annual POM Conference. 2004. ( World Conference on Production and Operations Management).

Author

Syntetos, Aris A. ; Boylan, John. / Inventory management for spare parts. Proceedings of the 2nd World Conference on POM and 15th Annual POM Conference. 2004. ( World Conference on Production and Operations Management).

Bibtex

@inproceedings{11ea50e4fae54716977f0d7dfc73a1d6,

title = "Inventory management for spare parts",

abstract = "Intermittent demand patterns are very difficult to forecast and subsequently manage regarding stock and they are, most commonly, associated with spare parts{\textquoteright} requirements. The purpose of this paper is to assess the empirical “stock control” performance of intermittent demand estimation procedures. The forecasting methods considered are the simple exponential smoothing, simple moving average, Croston{\textquoteright}s method and a new method recently developed bythe authors of this paper. We first discuss the nature of the empirical demand data set (3,000 Stock Keeping Units, Automotive Industry) and we specify the stock control model to be used for experimentation purposes. Technical simulation details are then presented to allow for replication of our results and performance measures are carefully selected to report Customer Service Level and stock volume differences. The empirical results demonstrate the superior stock control performance of the new intermittent demand forecasting method",

keywords = "Intermittent Demand, Spare parts, Forecasting, Stock Control",

author = "Syntetos, {Aris A.} and John Boylan",

year = "2004",

language = "English",

series = " World Conference on Production and Operations Management",

booktitle = "Proceedings of the 2nd World Conference on POM and 15th Annual POM Conference",

note = "2nd World Conference on POM, 15th Annual POM Conference ; Conference date: 30-04-2004 Through 03-05-2004",

}

RIS

TY - GEN

T1 - Inventory management for spare parts

AU - Syntetos, Aris A.

AU - Boylan, John

PY - 2004

Y1 - 2004

N2 - Intermittent demand patterns are very difficult to forecast and subsequently manage regarding stock and they are, most commonly, associated with spare parts’ requirements. The purpose of this paper is to assess the empirical “stock control” performance of intermittent demand estimation procedures. The forecasting methods considered are the simple exponential smoothing, simple moving average, Croston’s method and a new method recently developed bythe authors of this paper. We first discuss the nature of the empirical demand data set (3,000 Stock Keeping Units, Automotive Industry) and we specify the stock control model to be used for experimentation purposes. Technical simulation details are then presented to allow for replication of our results and performance measures are carefully selected to report Customer Service Level and stock volume differences. The empirical results demonstrate the superior stock control performance of the new intermittent demand forecasting method

AB - Intermittent demand patterns are very difficult to forecast and subsequently manage regarding stock and they are, most commonly, associated with spare parts’ requirements. The purpose of this paper is to assess the empirical “stock control” performance of intermittent demand estimation procedures. The forecasting methods considered are the simple exponential smoothing, simple moving average, Croston’s method and a new method recently developed bythe authors of this paper. We first discuss the nature of the empirical demand data set (3,000 Stock Keeping Units, Automotive Industry) and we specify the stock control model to be used for experimentation purposes. Technical simulation details are then presented to allow for replication of our results and performance measures are carefully selected to report Customer Service Level and stock volume differences. The empirical results demonstrate the superior stock control performance of the new intermittent demand forecasting method

KW - Intermittent Demand

KW - Spare parts

KW - Forecasting

KW - Stock Control

M3 - Conference contribution/Paper

T3 - World Conference on Production and Operations Management

BT - Proceedings of the 2nd World Conference on POM and 15th Annual POM Conference

T2 - 2nd World Conference on POM, 15th Annual POM Conference

Y2 - 30 April 2004 through 3 May 2004

ER -

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