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<p>This thesis examines the nature of the repairable part demand-carcass return relationship at the Navy Ships' Parts Control Center and proposes an alternate forecasting method for predicting the number of carcasses arriving at the Depot Overhaul Points in the coming quarter. The analysis begins with graphical and correlation review of the variables and then uses regression, and exponential smoothing to model carcass returns. These methods are compared to the model currently in use by an analysis of the forecasts errors. The comparison suggests that the exponential smoothing model results in the most accurate forecasts. The thesis concludes with some recommendations for model implementation.
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<br>Subjects: demand; carcass return; MAD; Bias; exponential smoothing; regression; MAD minimizing parameter set; unrestricted range model; restricted range model</div>
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Vassian, Robert Bruce</div>
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