Safety Inventory under a Periodic Review System

Abstract:

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The objective of this paper is to derive and verify a formula for calculating safety inventory that satisfies a desired cycle service level in a periodic review system. Stochastic variables, including customer demand and supplier’s lead time, are assumed to be normally distributed. Independent demand items are considered and backorders are not allowed. After deriving the formula, a computerized model simulating a periodic review system is developed by utilizing Microsoft Excel. Hypothesis testing is employed to compare the desired cycle service level with the simulated cycle service level. The result of this paper shows that there is strong agreement between the derived formula and the simulation model. In other words, the derived formula is verified. Furthermore, this simulation model also allows prompt identification of the impact of changes in inventory policy on cycle service level and inventory cost.

Info:

Periodical:

Advanced Materials Research (Volumes 591-593)

Edited by:

Liangchi Zhang, Chunliang Zhang, Jeng-Haur Horng and Zichen Chen

Pages:

545-552

Citation:

A. B. Ma'aram and L. T. T. Kien, "Safety Inventory under a Periodic Review System", Advanced Materials Research, Vols. 591-593, pp. 545-552, 2012

Online since:

November 2012

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Price:

$38.00

[1] Chopra, S. and Meindl, P. (2010). Supply Chain Management: Strategy, Planning, and Operation. (4th ed. ). Upper Saddle River, N. J.: Prentice Hall.

DOI: https://doi.org/10.1108/ijppm.2007.56.4.369.1

[2] Garcia, E. S., Silva, C. F. and Saliby, E. (2002). A Simulation Model to Validate and Evaluate the Adequacy of an Analytical Expression for Proper Safety Stock Sizing. Proceedings of the 2002 Winter Simulation Conference. 1282-1288.

DOI: https://doi.org/10.1109/wsc.2002.1166389

[3] Montgomery, D. C. (2009). Statistical Quality Control: A Modern Introduction. (6th ed. ). John Wiley & Sons, Inc.

[4] Tersine, R. J. (1994). Principles of Inventory and Materials Management. (4th ed. ). Prentice Hall International, Inc.

[5] Zabawa, J. and Mielczarek, B. (2002). Tools of Monte Carlo Simulation in Inventory Management Problems. Wrocław University of Technology.