Date of Award

3-23-2018

Document Type

Thesis

Degree Name

Master of Science in Logistics and Supply Chain Management

Department

Department of Operational Sciences

First Advisor

Jason R. Anderson, PhD.

Abstract

United States Transportation Command (TRANSCOM) along with Air Mobility Command (AMC) provide airlift assets that accomplish thousands of missions around the world every week for cargo distribution. The current unit of measure is a short ton, which is the primary metric used in decision making. However, the short ton measurement does not adequately predict the amount of work necessary to properly prepare different cargo types for airlift. Utilizing the short ton metric leads to inadequate forecasting times for cargo preparation and aircraft loading, which leads to delayed missions. The root of the problem is that the metric used does not provide enough fidelity for accurate forecasts, and in essence, all tons of cargo moved are not created equal concerning preparation and loading. For example, a ton of hazardous material takes more preparation than a ton of standard cargo. This research utilizes a stepwise regression model that accounts for the different cargo types, such as loose stock, palletized cargo, rolling stock, standard cargo, pallet trains of size 2, 3, 4, 5, and 6, hazardous cargo classifications, and special handling codes (classified). This model can be used by AMC to increase the efficiency of planning for cargo preparation and cargo load times by providing greater fidelity on different load-types than just their weight. Seven of the cargo characteristics are found to be statistically significant and are validated with split data and implementation at Travis, AFB. This analysis has led to a new metric called the working ton. The working ton metric is created utilizing the stepwise regression model’s standardized betas. The values of these coefficients indicate the relative effect of each variable. Hazard category one and the standard pallet are shown to be the most significant variables, having the greatest effect on the amount of time it takes to load an aircraft. This research proposes a new metric for AMC and TRANSCOM to use that will significantly aid in their ability to predict work-levels and improve future mission timelines.

AFIT Designator

AFIT-ENS-MS-18-M-151

DTIC Accession Number

AD1056381

Download

Share

COinS