Uncertainty in availability generated by inventory management controls in a generic repairable item sustainment system

Authors

  • Gregory Daniel Sherman DSTO Edinburgh
  • Kerryn Rhys Owen DSTO Edinburgh
  • Adrian Pincombe DSTO Edinburgh
  • Axel Bender DSTO Edinburgh

DOI:

https://doi.org/10.21914/anziamj.v53i0.5237

Abstract

For defence logistics, strategic planning is typically based on mean values. Supply flows are estimated from average throughputs, and supply chain resources are allocated to meet average demands. Operations management is also based on mean values. Mean-value based inventory management techniques are the preferred way to maintain the availability of spare parts. Recent research suggests that defence maintenance systems using such inventory management techniques are sensitive to stochastic variability in stock demand. We illustrate that these deliberate planning actions can lead to increased uncertainty in the prediction of output measures such as operational availability. We use Discrete Event Simulation as well as Design of Experiments methods to model a maintenance system for a single type of repairable item. We demonstrate that the inclusion of inventory management leads to increased average availability of spare parts for a vehicle fleet. However, in some cases the variation in availability decreases the system's apparent reliability. References
  • Anscombe, F. J. (1948) The Validity of Comparative Experiments. Journal of the Royal Statistical Society. Series A (General) 111 (3): 181--211. doi:10.2307/2984159 MR30181.
  • Bender A., Pincombe A. H., Sherman G. D. (2009) Effects of decay uncertainty in the prediction of life-cycle costings for large scale military capability projects 18th World IMACS / MODSIM Congress, Cairns, Australia 13--17 July 2009.
  • Brown, R. G Statistical Forecasting for Inventory Control McGraw-Hill, New York, 1959
  • Brown, Robert Goodell Smoothing Forecasting and Prediction of Discrete Time Series Englewood Cliffs, NJ: Prentice-Hall , 1963
  • Gardner, E. S., Jr., and McKenzie, E. Forecasting trends in time series Management Science, 31, 1237--1246, 1985
  • Jie Wan, Cong Zhao, Simulation Research on Multi-Echelon Inventory System in Supply Chain Based on Arena, icise, pp.397--400, First International Conference on Information Science and Engineering, 2009
  • Hartmut Bossel Systems and models: Complexity, Dynamics, Evolution, Sustainability Books on Demand GmbH, 2007
  • Piasecki, David J. Inventory Management Explained: A focus on Forecasting, Lot Sizing, Safety Stock, and Ordering Systems OPS Publishing, 2009.
  • Sherman G. D., Pincombe A. H., Bender A. (2009) Determining some of the triggers for early life cycle failure in decay affected logistic queueing simulation, Proceedings of the 9th Biennial Engineering Mathematics and Applications Conference, EMAC-2009 ANZIAM J., 51(E):C715--C729, 2010. http://journal.austms.org.au/ojs/index.php/ANZIAMJ/article/view/2604.

Published

2012-11-15

Issue

Section

Proceedings Engineering Mathematics and Applications Conference