Sponsor:

U.S. Army Defense Ammunition Center

Research Team:

M.C. Altan, B. Mustafa Pulat, Zahed Siddique

Universities Involved:

University of Oklahoma

Start Date:

02/26/07

End Date:

02/25/08

Summary:

The objective of this project is to design a user friendly web-based Load Building Tool to be used at the Defense Ammunition Center (DAC) to configure the loading of a desired ammunition shipment connecting to the existing database (CAUPULDI).
This work outlines the requirements to produce a functional, web-based interactive tool, to calculate various configurations of container ammunition loads for use by DoD ammunition transporters. The load building tool will also be the basis for determining economical use of storage magazine space.

The software tool will allow users via the DAC website to plan for an ISO container out-load of one or many different items. Various criteria may be selected by the user, such as container weight limit and mode of transport. The sources of the information used to populate this tool would include, but not be limited to, databases such as Joint hazard Classification System (JHCS), Conventional Ammunition Packaging and Unit Load Data Index (CAPULDI), as well as Joint Service ammunition catalog data. This web site could also include information such as out-loading drawings, links to AIDPMO (container office), and links to the JHCS.
We have performed volume and weight efficiency analyses of three software packages, Cube IQ, Cube Master and the one developed for the current project, Load Building Tool. The purpose of these comparisons is to see how our software performs compared to its commercial counterparts. Cube Master’s low performance and hints of errors during loading makes Cube Master a very unfavorable package. Load Building Tool performed superior to Cube Master in all cases. Cube IQ on the other hand displayed the best performance of the three, with lowest number of containers required to design the same loading. However, Load Building Tool’s performance was very close to that of Cube IQ and matched up the number of containers in some cases. Therefore, the software and the algorithm we designed for the purposes of the project compares favorably with commercial applications.