Date of Award

9-1998

Document Type

Thesis

Degree Name

Master of Science

Abstract

The Colombian Air Force recently installed a logistics operating system to improve the logistics system. However, the inventory cost and turnover have not stopped growing; subsequently, the operational readiness has been affected. The purpose of the study was to compare the performance of several forecasting techniques to improve the current planning process of aircraft parts in the CAF. The research used five phases. The first phase identified the relevant factors and the forecasting techniques selected for the experiment. The factors were repairability, demandability and uniqueness. The forecasting methods were single and double exponential, moving average, autoregression and linear regression. The third and fourth phases simulate additional demand data. It was found that single exponential and moving average perform better than the others. The fifth phase found that the forecasting system can provide substantial savings to the logistics system. Finally, it can be concluded that demand for most spare parts cannot be predicted because forecasts always contain errors. Then, it is necessary to consider additional improvements in logistics operations to make it easier to live with demand uncertainty. Among such improvements would be a shortening of the resupply time, the procurement lead time, and of the repair cycle for spare parts.

AFIT Designator

AFIT-GLM-LAL-98S-10

DTIC Accession Number

ADA354207

Comments

Presented to the Faculty of the Graduate School of Logistics and Acquisition Management of the Air Force Institute of Technology

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