This research provides insight into the cargo unloading and loading process and times at three airfields in Afghanistan. Using a linear regression model and its prediction capability, a more stabilized environment is produced. This uses the times from seven historical months of continuous operations in Afghanistan and uses this information for the prediction expressions. Using this model, no throughput is lowered and early and late times are lowered by an average of seven minutes per mission. Over the course of a month, this increases planning stability by 74.1 hours. This not only impacts the planning at the downrange location, but also impacts worldwide operations and cargo movement
With the dissolution of the Warsaw Pact and the fall of the Soviet Union, the number of alert aircra...
This research provides forecasting models that will enable the AMC Directorate of Logistics analysis...
This thesis explores the changes in insights that result from using different types of models to ass...
The United States Transportation Command (USTRANSCOM) is currently responsible for the daily shipmen...
The Air Force can save thousands of dollars by reducing the number of blade hours on the CH-47 throu...
Aerial Refueling: AR) is the act of offloading fuel from one aircraft: the tanker) to another aircra...
This thesis develops five analytical models to understand the current ground refueling process, to o...
Purpose: The United States Air Force often provides effective airlift for cargo distribution, but is...
Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Researc...
United States Transportation Command (TRANSCOM) along with Air Mobility Command (AMC) provide airlif...
This research represents an attempt to develop a quantitative tool that could be used to forecast Tr...
Current aircraft forecasting methods of the Air Mobility Command (AMC) Directorate of Logistics are ...
Accurate forecasting of contingency workload demand for USTRANSCOM (USTC) is a herculean effort. Tra...
This thesis developed models to forecast the KC-135R monthly Consumables (CONS) and Depot Level Repa...
Lean Logistics is an innovative proposal designed to reduce the costs associated with reparable inve...
With the dissolution of the Warsaw Pact and the fall of the Soviet Union, the number of alert aircra...
This research provides forecasting models that will enable the AMC Directorate of Logistics analysis...
This thesis explores the changes in insights that result from using different types of models to ass...
The United States Transportation Command (USTRANSCOM) is currently responsible for the daily shipmen...
The Air Force can save thousands of dollars by reducing the number of blade hours on the CH-47 throu...
Aerial Refueling: AR) is the act of offloading fuel from one aircraft: the tanker) to another aircra...
This thesis develops five analytical models to understand the current ground refueling process, to o...
Purpose: The United States Air Force often provides effective airlift for cargo distribution, but is...
Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Researc...
United States Transportation Command (TRANSCOM) along with Air Mobility Command (AMC) provide airlif...
This research represents an attempt to develop a quantitative tool that could be used to forecast Tr...
Current aircraft forecasting methods of the Air Mobility Command (AMC) Directorate of Logistics are ...
Accurate forecasting of contingency workload demand for USTRANSCOM (USTC) is a herculean effort. Tra...
This thesis developed models to forecast the KC-135R monthly Consumables (CONS) and Depot Level Repa...
Lean Logistics is an innovative proposal designed to reduce the costs associated with reparable inve...
With the dissolution of the Warsaw Pact and the fall of the Soviet Union, the number of alert aircra...
This research provides forecasting models that will enable the AMC Directorate of Logistics analysis...
This thesis explores the changes in insights that result from using different types of models to ass...