Date of Award:


Document Type:


Degree Name:

Master of Science (MS)


Mathematics and Statistics

Department name when degree awarded

Applied Statistics

Committee Chair(s)

David White


David White


Anita Flippen


This thesis describes a computer simulation model for determining effective spares stock levels for recoverable items at Air Force bases and depots. The simulation model is based on the following fundamental inventory theory; whenever a demand arises, it is satisfied from stock on hand, and the quantity equal to that demand is recorded immediately; when a demand exceeds stock on hand, the excess demand is backordered immediately and when item life expires procurement action is initiated at depot level. The resulting product of the model cam be used as a guide for the optimum distribution of available spares or as a computation of the necessary spares which will meet a desired percent fill rate. Outputs from the simulation model will also enable evaluation of the spares level effects as a result of change in other logistic parameters.

The purpose of this thesis is two-fold to the extent that it presents: (a) A computer simulation model of an Air Force logistic system; and (b) A discussion of compound Monte-Carlo demand generation involving various analytic failure distributions.

The specific nature of the problem to which the simulation model is applied is described and the model construction and output are discussed in detail.